From 4da6924202da49a739e33d305ed6f59bee5c0fc4 Mon Sep 17 00:00:00 2001
From: Dong Yu <dongyu@microsoft.com>
Date: Thu, 23 Apr 2015 21:37:01 +0800
Subject: [PATCH 01/49] add ICASSP 2015 CNTK tutorial slides under the papers
 folder.

---
 papers/CNTK-Tutorial-ICASSP2015.pdf | Bin 0 -> 2556196 bytes
 1 file changed, 0 insertions(+), 0 deletions(-)
 create mode 100644 papers/CNTK-Tutorial-ICASSP2015.pdf

diff --git a/papers/CNTK-Tutorial-ICASSP2015.pdf b/papers/CNTK-Tutorial-ICASSP2015.pdf
new file mode 100644
index 0000000000000000000000000000000000000000..2d78497faf97ad7fd5dcb06ce006c12f35c1ff27
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zT)C(R{2Y9^8~AV?Lp|W<;KP**9q@DT;mU;$_&NA+wQr~g{2Y9^axp*P=MVTf_;8&M
zI^gHv!_{&^2mJhj{v3R`&WC!SKYzf_!H4U7m>=+S@ZmzMV_d<{!G|jsI^gHv!<CDA
z;Q2ZDaJBZR2iDsk@N@9tIv;ev&%uW)7dqhQ;KQ{X0Uhvj@ZrkE{D7Z7;OF4Obw22T
zpMwwA5(;#{&%uW)7dqhQ;KP**|A3!^4_EH`Aoy@M@ZmbP{sBH*aXYTShbwM%fDc#P
z&U5hLTB_Q5fDcz3bYQ(5e7JJ=cgYie4nADD(1G=K@Znl=+xr#xaK-Jo0w1n8=s<rC
zK3uubf&LtPxRwc_1AY!ZT)7xm@N@9t%H4SmK3s8_AMkVV;o1%Z;|hKbK3ut|2iDuc
zhbtHLz<N9Qa4pB89`JMU;mSol;O9^HIrwm$4?5uI;KQ|q3?1-u@ZrjZ4){6vaOGlL
z!Oy{mYYP<Iui)oT_&NA+oew(T=itMY3mx!t@ZnmPhYt8T_;BUoeg!`VAFf>Z2mBm-
zxN<Si;pgDP^~eG99DWWyT)CL%@N@9t%EkPEpMwwAmN`2=z=tbt>j6GoajOG-xZ-wP
zfe%;Q)&qRF9^*g<{2Y9^a(8}!4_DldEAZip+j@Wx*JGxgAK=3kx8n+YxZ<D#e*S`=
zgAdpFpaXvX!t-<R;o4#eI<VgUf}evA*ZEKn_&NA+<zigH&%uZ5u^)86&%uW)7xM#t
z4nADDs0aM~h5j6TxE@tP2iDuchbtF4;OF4Ol?xs4bMWEXY76rme*VIGJNR&&4?3{k
z4nADD(1G=K@Zoy=3mx!t@ZrkEJcply4_7YkyYO@H;d(rc`xX2ge7JJqAMo=R`g8E%
zIv;ePKL;P~20mQJP!ISy_;BT-9`JMU;mU;$_&NA+y#}!L03WWno#)`g6}LLThbwOH
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zbj-2&ckV^@SNGGeb9<Ad-z8ri>n*Kc_gnOTj{W@8pZ@YMKm7Fh({FzB%^&~rpFe!L
zg^&B@4?q6+^Ow%{<qzNd-CzIw<Ck;mr(gc#yMOx4{qf!JzWc64tKYsl*X{d$dVl}B
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z^QZql+MoXU)Bn>S_{~53^uxb@`P<+1%|HI(hd=-E=YQ?LfBEP8_}BNgKqK&PfBk;}
D3HX(#

literal 0
HcmV?d00001


From 63b252b3b1dc30211cd65c84a91300c46b41fb3d Mon Sep 17 00:00:00 2001
From: Jasha Droppo <jdroppo@microsoft.com>
Date: Fri, 24 Apr 2015 00:39:54 -0700
Subject: [PATCH 02/49] Fixing race condition in BestGpu

---
 Common/BestGpu.cpp | 90 +++++++++++++++++++++++-----------------------
 1 file changed, 44 insertions(+), 46 deletions(-)

diff --git a/Common/BestGpu.cpp b/Common/BestGpu.cpp
index 7333e4cde..1296208d3 100644
--- a/Common/BestGpu.cpp
+++ b/Common/BestGpu.cpp
@@ -63,11 +63,15 @@ enum BestGpuFlags
     bestGpuFavorMemory = 2, // favor memory
     bestGpuFavorUtilization = 4, // favor low utilization
     bestGpuFavorSpeed = 8, // favor fastest processor
+    bestGpuExclusiveLock = 16, // obtain mutex for selected GPU
     bestGpuRequery = 256, // rerun the last query, updating statistics
 };
 
 class BestGpu
 {
+#ifdef WIN32
+    std::map<int, HANDLE> m_GPUMutex;
+#endif
 private:
     bool m_initialized; // initialized
     bool m_nvmlData; // nvml Data is valid
@@ -99,6 +103,7 @@ public:
     static const int AllDevices = -1;  // can be used to specify all GPUs in GetDevices() call
     static const int RequeryDevices = -2;  // Requery refreshing statistics and picking the same number as last query
     std::vector<int> GetDevices(int number = AllDevices, BestGpuFlags flags = bestGpuNormal ); // get multiple devices
+private:
 	bool LockDevice(int deviceID, bool trial=true);
 };
     
@@ -167,49 +172,22 @@ DEVICEID_TYPE DeviceFromConfig(const ConfigParameters& config)
             }
         }
 #else
-        std::vector<int> devices = g_bestGpu->GetDevices(1,  bestGpuAvoidSharing);
-		// to return a vector of AVAILABLE devices and sorted by score 
-        deviceId = (DEVICEID_TYPE)devices[0];
-		if (bLockGPU)
-		{
-			if (!g_bestGpu->LockDevice(deviceId, false)) // formally lock it 
-			{
-				string message = msra::strfun::strprintf("DeviceFromConfig: Cannot capture and lock Device %d\n", deviceId);
-				throw std::runtime_error(message.c_str());
-			}
-		}
+        deviceId = (DEVICEID_TYPE)
+            g_bestGpu->GetDevice(BestGpuFlags(bLockGPU ? (bestGpuAvoidSharing | bestGpuExclusiveLock) : bestGpuAvoidSharing));
 #endif
     }
     else if (!_stricmp(val.c_str(), "All"))
     {
-        std::vector<int> devices = g_bestGpu->GetDevices(BestGpu::AllDevices, bestGpuNormal);
+        std::vector<int> devices =
+            g_bestGpu->GetDevices(BestGpu::AllDevices, BestGpuFlags(bLockGPU ? bestGpuNormal | bestGpuExclusiveLock : bestGpuNormal));
         deviceId = (DEVICEID_TYPE)devices[0];
-		if (bLockGPU) {
-			for (auto i : devices)
-			{
-				if (!g_bestGpu->LockDevice(i, false))
-				{
-					string message = msra::strfun::strprintf("DeviceFromConfig: Cannot capture and lock Device %d\n", i);
-					throw std::runtime_error(message.c_str());
-				}				
-			}
-		}
     }
     else if (val.size() == 2 && val[0] == '*' && isdigit(val[1]))
     {
         int number = (int)(val[1] - '0');
-        std::vector<int> devices = g_bestGpu->GetDevices(number, bestGpuNormal);
+        std::vector<int> devices =
+            g_bestGpu->GetDevices(number, BestGpuFlags(bLockGPU ? bestGpuNormal | bestGpuExclusiveLock : bestGpuNormal));
         deviceId = (DEVICEID_TYPE)devices[0];
-		if (bLockGPU){
-			for (size_t i = 0; i < number; i++)
-			{
-				if (!g_bestGpu->LockDevice((int)i, false))
-				{
-					string message = msra::strfun::strprintf("DeviceFromConfig: Cannot capture and lock Device %d\n", i);
-					throw std::runtime_error(message.c_str());
-				}
-			}
-		}
     }
     else
     {
@@ -222,19 +200,10 @@ DEVICEID_TYPE DeviceFromConfig(const ConfigParameters& config)
         {
             argvector<int> allowed = arr;
             g_bestGpu->SetAllowedDevices(allowed);
-            std::vector<int> devices = g_bestGpu->GetDevices(BestGpu::AllDevices, bestGpuNormal);
+
+            std::vector<int> devices =
+                g_bestGpu->GetDevices(BestGpu::AllDevices, BestGpuFlags(bLockGPU ? bestGpuNormal | bestGpuExclusiveLock : bestGpuNormal));
             deviceId = (DEVICEID_TYPE)devices[0];
-			if (bLockGPU)
-			{
-				for (auto i : devices)
-				{
-					if (!g_bestGpu->LockDevice(i, false))
-					{
-						string message = msra::strfun::strprintf("DeviceFromConfig: Cannot capture and lock Device %d\n", i);
-						throw std::runtime_error(message.c_str());
-					}
-				}
-			}
         }
     }
     return deviceId;
@@ -342,6 +311,12 @@ BestGpu::~BestGpu()
     {
         nvmlShutdown();
     }
+#ifdef WIN32
+    for (auto it : m_GPUMutex)
+    {
+        ::CloseHandle(it.second);
+    }
+#endif
 }
 
 // GetNvmlData - Get data from the Nvidia Management Library
@@ -504,7 +479,18 @@ std::vector<int> BestGpu::GetDevices(int number, BestGpuFlags p_bestFlags)
             break;
     }
 
-	{ 
+#ifdef WIN32
+    // this code allows only one process to run concurrently on a machine
+    wchar_t buffer[80];
+    wsprintf(buffer, L"Global\\DBN.exe GPGPU querying lock");
+    HANDLE h = ::CreateMutex(NULL, FALSE, buffer);
+    if (h == NULL)  // failure  --this should not really happen
+        throw std::runtime_error("DeviceFromConfig: unexpected failure");
+    if (bestFlags & bestGpuExclusiveLock) // only wait if we will be locking devices
+        ::WaitForSingleObject(h, INFINITE);
+#endif
+    
+    {
 	// even if user do not want to lock the GPU, we still need to check whether a particular GPU is locked or not, 
 	// to respect other users' exclusive lock.
 
@@ -534,6 +520,17 @@ std::vector<int> BestGpu::GetDevices(int number, BestGpuFlags p_bestFlags)
         best.push_back(-1);
     }
 
+    for (int z = 0; z<best.size() && z < number; z++)
+    {
+        LockDevice(best[z], false);
+    }
+
+#ifdef WIN32
+    // we have our device - let other processors play now
+    ::ReleaseMutex(h);
+    ::CloseHandle(h);
+#endif
+
     return best; // return the array of the best GPUs
 }
 
@@ -680,6 +677,7 @@ bool BestGpu::LockDevice(int deviceID, bool trial)
 		{
 			fprintf(stderr, "LockDevice: Capture device %d and lock it for exclusive use\n", deviceID);
 		}
+        m_GPUMutex[deviceID] = h;
 		return true;
 	}
 	::CloseHandle(h);

From 3a89639d40862324a6a3ef69525e00cee57672cb Mon Sep 17 00:00:00 2001
From: kaisheny <ksyao@hotmail.com>
Date: Mon, 27 Apr 2015 22:22:17 -0700
Subject: [PATCH 03/49] Add nogpu  functions for RCRF related functions

---
 DataReader/LMSequenceReader/SequenceReader.cpp | 10 +++++++++-
 Math/Math/NoGPU.cpp                            | 16 ++++++++++++++++
 2 files changed, 25 insertions(+), 1 deletion(-)

diff --git a/DataReader/LMSequenceReader/SequenceReader.cpp b/DataReader/LMSequenceReader/SequenceReader.cpp
index 0924e5cfe..256b6584a 100644
--- a/DataReader/LMSequenceReader/SequenceReader.cpp
+++ b/DataReader/LMSequenceReader/SequenceReader.cpp
@@ -970,9 +970,11 @@ bool SequenceReader<ElemType>::SentenceEnd()
     return false; 
 }
 
-/// the output label is a [2 x T] matrix.
+/// the output label is a [4 x T] matrix, where T is the number of words observed
 /// the first row is the word index
 /// the second row is the class id of this word
+/// the third row is begining index of the class for this word
+/// the fourth row is the ending index + 1 of the class for this word
 template<class ElemType>
 void SequenceReader<ElemType>::GetLabelOutput(std::map<std::wstring, Matrix<ElemType>*>& matrices, 
                                               size_t m_mbStartSample, size_t actualmbsize)
@@ -1910,6 +1912,12 @@ bool BatchSequenceReader<ElemType>::DataEnd(EndDataType endDataType)
 
 }
 
+/// labels are in [4 x T] matrix
+/// 1st row is the word id
+/// 2nd row is the class id of this word
+/// 3rd and 4th rows are the begining and ending indices of this class
+/// notice that indices are defined as follows [begining ending_indx) of the class 
+/// i.e., the ending_index is 1 plus of the true ending index
 template<class ElemType>
 void BatchSequenceReader<ElemType>::GetLabelOutput(std::map<std::wstring, 
     Matrix<ElemType>*>& matrices, 
diff --git a/Math/Math/NoGPU.cpp b/Math/Math/NoGPU.cpp
index 10e97b86f..85bc01dcc 100644
--- a/Math/Math/NoGPU.cpp
+++ b/Math/Math/NoGPU.cpp
@@ -724,6 +724,22 @@ namespace Microsoft {
                 return (*this);
             }
 
+            template<class ElemType>
+            ElemType GPUMatrix<ElemType>::LogAddSumOfElements() const { return -1; };
+
+            template<class ElemType> void GPUMatrix<ElemType>::RCRFBackwardCompute(
+                const GPUMatrix<ElemType>& alpha, GPUMatrix<ElemType>& beta,
+                const GPUMatrix<ElemType>& lbls,
+                const GPUMatrix<ElemType>& pos_scores, const GPUMatrix<ElemType>& pair_scores, const int shift = 1) {};
+
+            template<class ElemType> void GPUMatrix<ElemType>::RCRFTransGrdCompute(const GPUMatrix<ElemType>& lbls,
+                const GPUMatrix<ElemType>&   alpha,
+                const GPUMatrix<ElemType>& beta,
+                const GPUMatrix<ElemType>& pair_scores,
+                GPUMatrix<ElemType>& grd,
+                const int startLbl, /// the time 0 start symbol in the output layer
+                const int shift) {};
+
             template<class ElemType>
             GPUMatrix<ElemType>& GPUMatrix<ElemType>::AssignElementProductOfWithShiftNeg(const GPUMatrix<ElemType>& a, const GPUMatrix<ElemType>& b, const size_t shift, const size_t nt)
             {

From 2f09a1e6ccc58a23031a825b912eb0b5c4ba6109 Mon Sep 17 00:00:00 2001
From: erw <erw@microsoft.com>
Date: Tue, 28 Apr 2015 21:46:05 -0700
Subject: [PATCH 04/49] Revise string output for plot function. %s -> %ls for
 better portability.

---
 MachineLearning/cn/ComputationNetwork.h | 20 ++++++++++----------
 1 file changed, 10 insertions(+), 10 deletions(-)

diff --git a/MachineLearning/cn/ComputationNetwork.h b/MachineLearning/cn/ComputationNetwork.h
index 1fef9c976..79e749ec7 100644
--- a/MachineLearning/cn/ComputationNetwork.h
+++ b/MachineLearning/cn/ComputationNetwork.h
@@ -172,7 +172,7 @@ private:	// [erw] added for Toplological Plot only
             }
 			wstring str = style; 
 			for (auto x : specialNodes){
-				str = str + msra::strfun::wstrprintf(L"\"%s\" ", x->GetName().c_str());
+				str = str + msra::strfun::wstrprintf(L"\"%ls\" ", x->GetName().c_str());
 			}
 			return str + L"; \n";
 		}
@@ -243,7 +243,7 @@ public:
 				line.clear(); 
                 size_t nrows = x->FunctionValues().GetNumRows();
                 size_t ncols = x->FunctionValues().GetNumCols();
-				line = msra::strfun::wstrprintf(L" \"%s\" [ label = \"%s [%d,%d]\\n%s\" ] ;\n", 
+				line = msra::strfun::wstrprintf(L" \"%ls\" [ label = \"%ls [%d,%d]\\n%ls\" ] ;\n", 
                     x->GetName().c_str(), x->GetName().c_str(), nrows, ncols,  x->OperationName().c_str());
 				fstream << line;
 			}
@@ -257,7 +257,7 @@ public:
 			line.clear(); 
 			for (auto x : m_features)
 			{
-				line = line + msra::strfun::wstrprintf(L"\"%s\" ", x->GetName().c_str());
+				line = line + msra::strfun::wstrprintf(L"\"%ls\" ", x->GetName().c_str());
 			}
 			fstream << line << L"\n}\n"; 
 			// subgraph eval/output/criteria
@@ -266,15 +266,15 @@ public:
 			line.clear(); 
 			for (auto x : m_finalCriteria)
 			{
-				line = line + msra::strfun::wstrprintf(L"\"%s\" ", x->GetName().c_str());
+				line = line + msra::strfun::wstrprintf(L"\"%ls\" ", x->GetName().c_str());
 			}
 			for (auto x : m_outputNodes)
 			{
-				line = line + msra::strfun::wstrprintf(L"\"%s\" ", x->GetName().c_str());
+				line = line + msra::strfun::wstrprintf(L"\"%ls\" ", x->GetName().c_str());
 			}
 			for (auto x : m_evalNodes)
 			{
-				line = line + msra::strfun::wstrprintf(L"\"%s\" ", x->GetName().c_str());
+				line = line + msra::strfun::wstrprintf(L"\"%ls\" ", x->GetName().c_str());
 			}
 			fstream << line << L"\n}\n"; 
 
@@ -296,20 +296,20 @@ public:
 					// create a dummy node 
 					ComputationNodePtr delayedNode = des;
 					wstring dummyName = des->GetName() + L".dummy";
-					wstring out = msra::strfun::wstrprintf(L"node [ shape = box3d  , color = lightgray, style = \"filled\" , label = \"%s\" ] ; \"%s\"\n",
+                    wstring out = msra::strfun::wstrprintf(L"node [ shape = box3d  , color = lightgray, style = \"filled\" , label = \"%ls\" ] ; \"%ls\"\n",
 						(delayedNode->GetName() + L"\\n(delayed)").c_str(), dummyName.c_str());
 					line = out; 
-					line += msra::strfun::wstrprintf(L"\"%s\" -> \"%s\" ; \n", dummyName.c_str(), srcname.c_str());
+					line += msra::strfun::wstrprintf(L"\"%ls\" -> \"%ls\" ; \n", dummyName.c_str(), srcname.c_str());
 				}
 				else
 				{
-					line = msra::strfun::wstrprintf(L"\"%s\" -> \"%s\" ; \n", desname.c_str(), srcname.c_str());
+					line = msra::strfun::wstrprintf(L"\"%ls\" -> \"%ls\" ; \n", desname.c_str(), srcname.c_str());
 				}
 
 
 				fstream << line; 
 			}
-			fstream << "\n}\n";
+			fstream << L"\n}\n";
 
 
 			

From 09504d9a803563016c1df984f586ca2bfda4bbc4 Mon Sep 17 00:00:00 2001
From: erw <erw@microsoft.com>
Date: Thu, 30 Apr 2015 12:22:20 -0700
Subject: [PATCH 05/49] Remove MKL dependency of Math Project

---
 Math/Math/Math.vcxproj | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/Math/Math/Math.vcxproj b/Math/Math/Math.vcxproj
index 6b4757e76..742b4c5b8 100644
--- a/Math/Math/Math.vcxproj
+++ b/Math/Math/Math.vcxproj
@@ -38,7 +38,7 @@
     <PlatformToolset>v120</PlatformToolset>
     <WholeProgramOptimization>true</WholeProgramOptimization>
     <CharacterSet>Unicode</CharacterSet>
-    <UseIntelMKL>Parallel</UseIntelMKL>
+    <UseIntelMKL>No</UseIntelMKL>
     <UseIntelIPP>false</UseIntelIPP>
   </PropertyGroup>
   <Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
@@ -132,7 +132,7 @@
       </AdditionalLibraryDirectories>
       <AdditionalDependencies>libacml_mp_dll.lib;%(AdditionalDependencies)</AdditionalDependencies>
       <Profile>true</Profile>
-      <DelayLoadDLLs>cublas64_65.dll;cusparse64_65.dll;curand64_65.dll;cudart64_65.dll;libacml_dll.dll;libacml_mp_dll.dll;%(DelayLoadDLLs)</DelayLoadDLLs>
+      <DelayLoadDLLs>libacml_mp_dll.dll;%(DelayLoadDLLs)</DelayLoadDLLs>
     </Link>
     <PostBuildEvent>
       <Command>xcopy /D /I /Y "$(ACML_PATH)\lib\*.dll" $(OutputPath)</Command>

From 0b72e35836fdaa1e561720902903d6005c2790a8 Mon Sep 17 00:00:00 2001
From: erw <erw@microsoft.com>
Date: Thu, 30 Apr 2015 14:14:51 -0700
Subject: [PATCH 06/49] Further depress the message in HKTMLFReader

---
 DataReader/HTKMLFReader/utterancesourcemulti.h | 1 +
 1 file changed, 1 insertion(+)

diff --git a/DataReader/HTKMLFReader/utterancesourcemulti.h b/DataReader/HTKMLFReader/utterancesourcemulti.h
index 510e7bc32..4af5c9ec1 100644
--- a/DataReader/HTKMLFReader/utterancesourcemulti.h
+++ b/DataReader/HTKMLFReader/utterancesourcemulti.h
@@ -879,6 +879,7 @@ private:
             auto & chunkdata = randomizedchunks[m][k].getchunkdata();
             if (chunkdata.isinram())
             {
+                if (verbosity)
                 fprintf (stderr, "releaserandomizedchunk: paging out randomized chunk %d (frame range [%d..%d]), %d resident in RAM\n",
                      k, randomizedchunks[m][k].globalts, randomizedchunks[m][k].globalte()-1, chunksinram-1);
                 chunkdata.releasedata();

From 5edc126127a9506481ba5db42af3b4acb685e700 Mon Sep 17 00:00:00 2001
From: erw <erw@microsoft.com>
Date: Thu, 7 May 2015 10:23:07 -0700
Subject: [PATCH 07/49] Add error check after calling cudaGetDeviceCount

---
 Common/BestGpu.cpp | 11 ++++++++++-
 1 file changed, 10 insertions(+), 1 deletion(-)

diff --git a/Common/BestGpu.cpp b/Common/BestGpu.cpp
index 1296208d3..cc3676d5f 100644
--- a/Common/BestGpu.cpp
+++ b/Common/BestGpu.cpp
@@ -279,8 +279,17 @@ void BestGpu::Init()
         return;
 
     //get the count of objects
-    //cudaError_t err =
+    cudaError_t err =
     cudaGetDeviceCount(&m_deviceCount);
+    // TODO: use CUDA_CALL here
+    if (err != cudaSuccess)
+    {
+        const char* errmsg = cudaGetErrorString(err);
+        fprintf(stderr, "!!!!!!!!CUDA EXCEPTION: %s\n", errmsg);
+        throw std::runtime_error(errmsg);
+    }
+
+
 
     ProcessorData pdEmpty = { 0 };
     for (int i = 0; i < m_deviceCount; i++)

From 7575f940999c1ae92b909b32e9a7bc96bff226fa Mon Sep 17 00:00:00 2001
From: erw <erw@microsoft.com>
Date: Wed, 18 Mar 2015 17:47:08 -0700
Subject: [PATCH 08/49] Add support of SVD decomposition for Learnable
 Parameters

An example of using this command:

command=svd

svd=[
    action=SVD
    modelPath=train\lstm.model.67
    outputmodelPath=train\lstm.model.svd
    SVDConfig=NodeConfigs
]

A brief explanation:

- modelPath               specifies where to load the initial model
- outputmodelPath         specifies where to save the revised model
- SVDConfig               is a config file which specifies how the SVD is performed for different groups of nodes.
                          This config is in a two-column  format:

                          <NodeNameRegex>               <float>

                          The first column is a regex which will match the node name in one group
                          The second column is a float indicates what percentage of svd-energy will be kept after svd.

                          (svd-energy is defined as the sum of singular values )

                          An example :

                          LSTMoutput[1-3].Wx[ifco]        0.4
                          LSTMoutput[1-3].Wh[ifco]        0.6

                          Using this config will cause a more aggressive SVD (0.4) for the non-recurrent connections (from x to i,f,c,o gates) in LSTM
                          and less aggressive SVD for recurrent connection (from h to i,f,c,o gates)
---
 MachineLearning/cn/ComputationNetwork.h | 159 +++++++++++++++++++++++-
 MachineLearning/cn/cn.cpp               |  95 +++++++++++++-
 2 files changed, 252 insertions(+), 2 deletions(-)

diff --git a/MachineLearning/cn/ComputationNetwork.h b/MachineLearning/cn/ComputationNetwork.h
index 79e749ec7..1ac287e58 100644
--- a/MachineLearning/cn/ComputationNetwork.h
+++ b/MachineLearning/cn/ComputationNetwork.h
@@ -25,6 +25,8 @@
 #include "Matrix.h"
 #include "commandArgUtil.h"
 #include <iostream>
+#include <regex>
+#include <chrono>
 
 namespace Microsoft { namespace MSR { namespace CNTK {
     template<class ElemType>
@@ -1938,7 +1940,28 @@ public:
                     m_outputNodes[i] = newNode;
             } 
         }
-
+    
+        // replace the old node with the current node, assuming the old node is a leaf node 
+        // need to update those nodes who use oldNode as their child 
+        void ReplaceLeafNode(wstring oldNodeName, ComputationNodePtr newNode)
+        {
+            ComputationNodePtr oldNode = GetNodeFromName(oldNodeName);
+            
+            // change the input of those nodes whose child is oldNode
+            for (auto nodeIter = m_nameToNodeMap.begin(); nodeIter != m_nameToNodeMap.end(); nodeIter++)
+            {
+                ComputationNodePtr node = nodeIter->second;
+                for (int i = 0; i < node->ChildrenSize(); i++)
+                {
+                    if (node->Inputs(i) == oldNode)
+                        node->SetInput(i, newNode);
+                }
+            }
+            m_nameToNodeMap[newNode->GetName()] = newNode;
+            // now the old node becomes a orphan node , remove it 
+            DeleteNode(oldNodeName);
+            //RemoveOrphanNode(oldNode);
+        }
         std::vector<ComputationNodePtr> GetAllNodes() const
         {
             std::vector<ComputationNodePtr> nodes;
@@ -2087,6 +2110,140 @@ public:
             }
         }
 
+        //========================================
+        // This function performs SVD decomposition for different groups of learnable  parameters 
+        // we perform SVD decomposition such that 
+        //  A \approx B*C, where rank(B)=rank(C)=r < rank(A)
+        // After SVD decomposition, the node A will become an intermediate node whose children are B,C ; 
+        // B and C are two learnable parameters 
+        //========================================
+        void PerformSVDecomposition(const map<wstring, float>& SVDConfig)   
+        {
+            vector<pair<vector<wstring>,float> > nodeGroups; 
+            wregex NameFilter; 
+
+            for (auto e : SVDConfig)
+            {
+                wstring regexStr = e.first; 
+                float   keepRatio = e.second; 
+                vector<wstring>     NamesInGroup;
+
+                NameFilter.assign(regexStr);
+
+                for (auto n = m_nameToNodeMap.begin(); n != m_nameToNodeMap.end(); n++)
+                {
+                    if (!regexStr.empty() && !regex_match(n->first, NameFilter))
+                        continue;           // if regexStr is not empty and the the node node does not match with the regexStr
+                    ComputationNodePtr ptr = n->second; 
+                    if (ptr->OperationName() != LearnableParameter<ElemType>::TypeName())
+                        continue;
+                    Matrix<ElemType>  W = ptr->FunctionValues();
+                    if (W.GetNumCols() == 1 || W.GetNumRows() == 1)
+                        continue;
+                    // still here ? 
+                    NamesInGroup.push_back(n->first);
+                }
+                nodeGroups.push_back(make_pair(NamesInGroup, keepRatio));
+            }
+
+            size_t groupID = 0;
+            for (auto& group : nodeGroups)
+            {
+                float keepratio = group.second; 
+                fprintf(stderr, "--------------------------------------------------------------------------------------------\n");
+                fprintf(stderr, "ParameterSVD: start to process group %d with KeepRatio=%.2f\n", groupID++, keepratio);
+                fprintf(stderr, "--------------------------------------------------------------------------------------------\n");
+                for (auto name : group.first)
+                {
+                    if (m_nameToNodeMap.find(name) == m_nameToNodeMap.end())
+                    {
+                        // could be deleted in the previous groups
+                        continue;
+                    }
+                    ComputationNodePtr pNode = m_nameToNodeMap[name];
+                    //========================================
+                    // Step 1. do SVD decomposition 
+                    //========================================
+                    Matrix<ElemType> A = pNode->FunctionValues();
+                    if (A.GetNumCols() == 1 || A.GetNumRows() == 1)       // it is a vector, no need to do it 
+                        continue;
+                    size_t m = A.GetNumRows();
+                    size_t n = A.GetNumCols();
+
+                    Matrix<ElemType> S(-1), U(-1), VT(-1), W(-1);
+                    std::chrono::time_point<std::chrono::system_clock> stTime = std::chrono::system_clock::now();
+                    Matrix<ElemType>::SVD(A, S, U, VT, W);
+                    std::chrono::time_point<std::chrono::system_clock> enTime = std::chrono::system_clock::now();
+                    // A \in R^{mXn} 
+                    // U \in R^{mXm} 
+                    // VT \in R^{nXn} 
+                    // S \in R^{min(m,n),1}  
+                    // S is in descending order 
+                    // 
+                    ElemType totalenergy = 0.0f;
+                    for (size_t i = 0; i < S.GetNumRows(); i++)
+                    {
+                        totalenergy += S(i, 0);
+                    }
+                    ElemType keepenergy = totalenergy*keepratio;
+                    ElemType runenergy = 0.0f;
+
+                    size_t r = 0;
+                    for (size_t indx = 0; indx < S.GetNumRows(); indx++)
+                    {
+                        runenergy += S(indx, 0);
+                        if (runenergy > keepenergy)
+                        {
+                            r = indx + 1;
+                            break;
+                        }
+                    }
+
+                    r = (r + 7) & (~7);             //  to keep the number of rows/cols of resultant matrix a multipier of 8 
+                    //  which can be helpful at runtime 
+
+                    std::chrono::duration<double>  elapsedtime = enTime - stTime;
+                    fprintf(stderr, "Performing SVD for a %5d-by-%-5d matrix (node name: %-20ls) ---  computation time %5.2f secs ;  keep %4.1f%% energy ===> keep %5d svd values (reduce to %4.1f%% parameters) \n",
+                        m, n, name.c_str(), elapsedtime.count(), keepratio*100, r, ((m+n)*r+0.0f)/m/n*100);
+
+
+                    Matrix<ElemType> redU = U.ColumnSlice(0, r);        // redU in R^ {mXr}
+                    Matrix<ElemType> redVT(-1); redVT.Resize(r, n);         // redVT in R^{rXn}
+                    redVT.AssignRowSliceValuesOf(VT, 0, r);
+
+                    Matrix<ElemType>    redS(r, (size_t)1);
+                    for (size_t i = 0; i < r; i++)
+                    {
+                        ElemType sqrtsigma = (ElemType)sqrt((double)S(i, 0));
+                        redS(i, 0) = sqrtsigma;
+                    }
+
+
+                    redU.RowElementMultiplyWith(redS.Transpose());
+                    redVT.ColumnElementMultiplyWith(redS);
+
+                    //========================================
+                    // Step 2. create two new Parameter nodes and one Times node
+                    //========================================
+                    wstring LeftChildName = name + L"-U";
+                    wstring rightChildName = name + L"-V";
+                    ComputationNodePtr pLeft = Parameter(m, r, LeftChildName);
+                    ComputationNodePtr pRight = Parameter(r, n, rightChildName);
+
+                    pLeft->FunctionValues() = redU;
+                    pRight->FunctionValues() = redVT;
+
+                    ComputationNodePtr pTimes = Times(pLeft, pRight, name + L"-SVD");
+
+                    //========================================
+                    // Step 3. remove old node 
+                    //========================================
+                    ReplaceLeafNode(name, pTimes);
+                }
+            }
+            RebuildNetwork(m_finalCriteria[0]);
+        }
+
     protected:
         // Copy constructor, should never be called.
 #pragma warning (push)
diff --git a/MachineLearning/cn/cn.cpp b/MachineLearning/cn/cn.cpp
index eeb748038..aa5dc58c7 100644
--- a/MachineLearning/cn/cn.cpp
+++ b/MachineLearning/cn/cn.cpp
@@ -39,6 +39,7 @@
 #include <set>
 #include "BestGpu.h"
 
+
 // MPI builds on windows require the following installed to "c:\program files\Microsoft MPI\"
 // HPC Pack 2012 R2 MS-MPI Redistributable Package
 // http://www.microsoft.com/en-us/download/details.aspx?id=41634
@@ -423,6 +424,96 @@ void DoCreateLabelMap(const ConfigParameters& config)
         fprintf(stderr, "%f seconds elapsed\n", (float)(std::chrono::duration_cast<std::chrono::milliseconds>(elapsed).count()) / 1000);
 }
 
+//////////////////////////////////////////////////////////////////////////
+//  for action SVD
+//		An action "SVD" performs the following process to transform an existing model: 
+//			1.	For a Learnable Parameter A whose name matches with the user specified regex, 
+//			    A is approximated by two matrice multiplication B*C ; 
+//			2.	In order to keep the low-rank structure in training, 
+//				the original A node will be replaced by A' whose opertions is Times
+//				with its left children being B and right chilren being 
+//
+//		To use this command,
+//			user need to specify: 
+//					1)	modelPath			-- path to the existing model 
+//					2)  outputmodelPath		-- where to write the transformed model 
+//					3)  KeepRatio			-- how many percentage of energy we want to keep
+//					4)  ParameterName		-- name (regex) of the parameter node we want to perform a SVD decomposition 
+//				
+//////////////////////////////////////////////////////////////////////////
+template<typename ElemType> 
+void  DoParameterSVD(const ConfigParameters& config)
+{
+    DEVICEID_TYPE deviceID = -1;        // use CPU for SVD 
+    wstring modelPath = config("modelPath");
+    wstring outputmodelPath = config("outputmodelPath");
+    map<wstring, float>     svdconfig; 
+
+    float keepratio = config("KeepRatio", "0.4");
+    wstring svdnodeRegex = config("NodeNameRegex", L"");
+    if (!svdnodeRegex.empty())
+    {
+        svdconfig[svdnodeRegex] = keepratio;
+    }
+    else
+    {
+        // alternatively, user can also use a config to specify KeepRatios for different groups of nodes 
+        wstring svdnodeConfigFile = config("SVDConfig", L"");
+        if (!ParseSVDConfigFile(svdnodeConfigFile, svdconfig))
+        {
+            SVDConfigFileUsage();
+            return; 
+        }
+    }
+
+
+    if (modelPath.empty())
+    {
+        fprintf(stderr, "ERROR: in DoParameterSVD, modelPath is empty!\n");
+        return;
+    }
+
+    
+    ComputationNetwork<ElemType> net(deviceID); 
+    net.LoadFromFile(modelPath);
+
+    net.PerformSVDecomposition(svdconfig);
+    if (!outputmodelPath.empty())
+        net.SaveToFile(outputmodelPath);
+
+}
+
+//////////////////////////////////////////////////////////////////////////
+//  helper function for DoParameterSVD 
+//////////////////////////////////////////////////////////////////////////
+bool ParseSVDConfigFile(wstring fn, map<wstring, float>& config)
+{
+    msra::files::textreader reader(fn);
+    for (; reader;)
+    {
+        wstring line = reader.wgetline(); 
+        vector<wstring> tokens=msra::strfun::split(line, L"\t ");
+        if (tokens.size() != 2)
+            return false;
+        config[tokens[0]] = (float)msra::strfun::todouble(tokens[1]);
+    }
+    return true;
+}
+
+// a brief on the SVD config file usage 
+void SVDConfigFileUsage()
+{
+    fprintf(stderr, "usage of SVDConfigFile\n"); 
+    fprintf(stderr, "A SVDConfigFile is referred in main config by \"SVDConfig\"\n"); 
+    fprintf(stderr, "Each line in this file specifies a group of Learnable Parameter nodes using regex and the KeepRatio associated with that group\n");
+    fprintf(stderr, "An example: \n"); 
+    fprintf(stderr, "W0         1.0\n"); 
+    fprintf(stderr, "W[1-5]     0.4\n"); 
+    
+
+}
+
+
 ///
 /// for action writeWordAndClassInfo
 ///
@@ -806,7 +897,9 @@ void DoCommand(const ConfigParameters& config)
             else if (action[j] == "writeWordAndClass")
 	            DoWriteWordAndClassInfo<ElemType>(commandParams);
             else if (action[j] == "plot")
-	            DoTopologyPlot<ElemType>(commandParams);
+                DoTopologyPlot<ElemType>(commandParams);
+            else if (action[j] == "SVD")
+                DoParameterSVD<ElemType>(commandParams);
             else
                 RuntimeError("unknown action: %s  in command set: %s", action[j].c_str(), command[i].c_str());
 

From 3c603c16c11d52778da267c7606d94798177dccb Mon Sep 17 00:00:00 2001
From: erw <erw@microsoft.com>
Date: Thu, 7 May 2015 10:56:30 -0700
Subject: [PATCH 09/49] Modify the prebuild.bat so that the build signature
 will include CUDA_PATH (can be helpful to check which CUDA version is used in
 build)

---
 MachineLearning/cn/cn.cpp       | 1 +
 MachineLearning/cn/prebuild.bat | 4 +++-
 2 files changed, 4 insertions(+), 1 deletion(-)

diff --git a/MachineLearning/cn/cn.cpp b/MachineLearning/cn/cn.cpp
index aa5dc58c7..e2ad40a22 100644
--- a/MachineLearning/cn/cn.cpp
+++ b/MachineLearning/cn/cn.cpp
@@ -979,6 +979,7 @@ void PrintBuiltInfo()
     fprintf(stderr, "\t\tLast modified date: %s\n", __TIMESTAMP__);
     fprintf(stderr, "\t\tBuilt by %s on %s\n", _BUILDER_, _BUILDMACHINE_);
     fprintf(stderr, "\t\tBuild Path: %s\n", _BUILDPATH_);
+    fprintf(stderr, "\t\tCUDA_PATH: %s\n", _CUDA_PATH_);
 #ifdef _GIT_EXIST
     fprintf(stderr, "\t\tBuild Branch: %s\n", _BUILDBRANCH_);
     fprintf(stderr, "\t\tBuild SHA1: %s\n", _BUILDSHA1_);
diff --git a/MachineLearning/cn/prebuild.bat b/MachineLearning/cn/prebuild.bat
index 0e72ecafd..3abac808b 100644
--- a/MachineLearning/cn/prebuild.bat
+++ b/MachineLearning/cn/prebuild.bat
@@ -10,7 +10,7 @@ FOR /F "usebackq" %%i IN (`hostname`) DO SET HOST=%%i
 
 :: not sure whether git in path ? 
 git --version 2 > nul 
-if not %ERRORLEVEL% == 9909 (
+if not %ERRORLEVEL% == 9009 (
     echo #define _GIT_EXIST >> buildinfo.h
     FOR /F "usebackq" %%i IN (`git rev-parse --abbrev-ref HEAD`) DO SET BRANCH=%%i
     FOR /F "usebackq" %%i IN (`git rev-parse HEAD`) DO SET COMMIT=%%i
@@ -26,5 +26,7 @@ set a=%~dp0
 set buildpath="%a:\=\\%"
 echo #define _BUILDPATH_    %buildpath%     >> buildinfo.h
 
+set cuda_path="%CUDA_PATH:\=\\%"
+echo #define _CUDA_PATH_    %cuda_path%     >> buildinfo.h
 
 echo #endif >> buildinfo.h

From 512a21fcff1fc02f205f212171497ca924e0f181 Mon Sep 17 00:00:00 2001
From: Dong Yu <dongyu@microsoft.com>
Date: Tue, 12 May 2015 18:36:33 -0700
Subject: [PATCH 10/49] add CNN, mixture density network, and gaussian mixture
 model example NDLs in the ndlexamples.ndl file under the examplesetups folder

---
 ExampleSetups/NDLExamples.ndl | 467 ++++++++++++++++++++++++++++++++++
 1 file changed, 467 insertions(+)
 create mode 100644 ExampleSetups/NDLExamples.ndl

diff --git a/ExampleSetups/NDLExamples.ndl b/ExampleSetups/NDLExamples.ndl
new file mode 100644
index 000000000..976de4a07
--- /dev/null
+++ b/ExampleSetups/NDLExamples.ndl
@@ -0,0 +1,467 @@
+load=ndlMacroDefine
+#run=ndlFull
+#run=ndlTestMDN
+#run=ndlTestGMM
+#run=ndlTestCosDist
+#run=ndlMacroUseCNNSubSample2
+run=ndlMacroUseCNN
+
+ndlTestCosDist=[
+    # constants defined
+    # Sample, Hidden, and Label dimensions
+    SDim=784
+    HDim=256
+    LDim=10
+
+    features=Input(SDim, tag=feature)
+    labels=Input(LDim, tag=label)
+
+    # compute mean/stddev for mean/stddev normalization
+    fmean = Mean(features);
+    finvstd=InvStdDev(features)
+    finput=PerDimMeanVarNormalization(features, fmean, finvstd)
+
+    # Layer operations
+    L1 = RBFF(finput, HDim, SDim)
+    L2 = RBFF(L1, HDim, HDim)
+    L3 = RBFF(L2, LDim, HDim)
+    L4 = SoftMax(L3);
+    CD = CosDistance(L4, labels);
+    CDAll=SumElements(CD)
+    NCD=Negate(CDALL, tag=Criteria)
+    Err=ErrorPrediction(labels, L4, tag=Eval)
+
+    # rootNodes defined here
+    OutputNodes=(L4)
+]
+
+ndlTestGMM=[
+    # constants defined
+    # Sample, Hidden, and Label dimensions
+    SDim=784
+    HDim=10
+    LDim=10
+
+    features=Input(SDim, tag=feature)
+    labels=Input(LDim, tag=label)
+
+    # Layer operations
+    L1=RBFF(features, HDim, SDim)
+    L2=RBFF(L1, HDim, HDim)
+    L3=BFF(L2, HDim, HDim)
+    
+    GMMComponent=4
+    SizeOfAllMeans=40
+    
+    UnnormedPrior=Parameter(GMMComponent, 1)
+    Means=Parameter(SizeOfAllMeans, 1)
+    LogStddev=Parameter(GMMComponent, 1)
+    
+    LL=GMMLL(UnnormedPrior, Means, LogStddev, L3)
+
+
+    # rootNodes defined here
+    OutputNodes=(NLL)
+    EvalNodes=(NLL)
+]
+
+ndlTestMDN=[
+    # constants defined
+    # Sample, Hidden, and Label dimensions
+    SDim=784
+    HDim=256
+    LDim=10
+
+    features=Input(SDim, tag=feature)
+    labels=Input(LDim, tag=label)
+
+    # Layer operations
+    L1=RBFF(features, HDim, SDim)
+    L2=RBFF(L1, HDim, HDim)
+    L3=RBFF(L2, HDim, HDim)
+    
+    GMMComponent=4
+    SizeOfAllMeans=40
+    
+    UnnormedPrior =  BFF(L3, GMMComponent, HDim)
+    Means=BFF(L3, SizeOfAllMeans, HDim)
+    LogStddev=BFF(L3, GMMComponent, HDim)
+    
+    LL=GMMLL(UnnormedPrior, Means, LogStddev, labels)
+    LLAll=SumElements(LL)
+    NLL=Negate(LLALL, tag=Criteria)
+
+    # rootNodes defined here
+    OutputNodes=(NLL)
+    EvalNodes=(NLL)
+]
+
+ndlFull=[
+    SDim=784
+    HDim=256
+    LDim=10
+    B0=Parameter(HDim)
+    W0=Parameter(HDim, SDim)
+    features=Input(SDim)
+    labels=Input(LDim)
+    mean0=Mean(features)
+    invstd0=InvStdDev(features)
+    normedFeat=PerDimMeanVarNormalization(features, mean0, invstd0)
+    Times1=Times(W0, normedFeat)
+    Plus1=Plus(Times1, B0)
+    RL1=RectifiedLinear(Plus1)
+    B1=Parameter(LDim, 1)
+    W1=Parameter(LDim, HDim)
+    Times2=Times(W1, RL1)
+    Plus2=Plus(Times2, B1)
+    #LogSM=LogSoftmax(Plus2)
+    #SM=Exp(LogSM)
+    #SM=Softmax(Plus2)
+    #CE=CrossEntropy(labels, SM)
+    CE=CrossEntropyWithSoftmax(labels, Plus2)
+    ErrPredict=ErrorPrediction(labels, Plus2)
+    FeatureNodes=(features)
+    LabelNodes=(labels)
+    CriteriaNodes=(CE)
+    EvalNodes=(ErrPredict)
+    OutputNodes=(Plus2)
+]
+
+ndlMacroDefine=[
+    # Macro definitions
+    #inline Rectified Linear Feed Forward
+    RFF_R(x1, w1, b1)=RectifiedLinear(Plus(Times(w1,x1),b1))
+    #Feed Forward
+    FF(X1, W1, B1)
+    [
+        T=Times(W1,X1);
+        P=Plus(T, B1);
+    ]
+    #Base feed Forward network, defines Bias and wieght parameters
+    BFF(in, rows, cols)
+    {
+        B=Parameter(rows, init=fixedvalue, value=0)
+        W=Parameter(rows, cols)
+        FF = FF(in, w, b)
+    }
+    #RectifiedLinear Base Feed Forward
+    RBFF(in,rowCount,colCount)
+    {
+        BFF = BFF(in, rowCount, colCount);
+        RL = RectifiedLinear(BFF);
+    }
+    #Rectified Linear Feed Forward
+    RFF(X2,W2,B2)=[
+        FF = FF(X2, W2, B2);  
+        RL = RectifiedLinear(FF);
+    ]
+    #RectifiedLinear Feed Forward with Dropout
+    RFFD(X3,W3,B3)
+    {
+        RFF=RFF(X3, W3, B3)
+        DO=Dropout(RFF)
+    }
+    #Sigmoid Base Feed Forward
+    SBFF(in,rowCount,colCount)
+    {
+        BFF = BFF(in, rowCount, colCount);
+        S = Sigmoid(BFF);
+    }
+    #Sigmoid Feed Forward
+    SFF(X2,W2,B2)=[
+        FF = FF(X2, W2, B2);  
+        S = Sigmoid(FF);
+    ]
+    #Sigmoid Feed Forward with Dropout
+    SFFD(X3,W3,B3)
+    {
+        SFF=SFF(X3, W3, B3)
+        DO=Dropout(SFF)
+    }
+    #SoftMax Feed Forward
+    SMFF(x,y,z, labels)
+    {
+        FF = FF(x,y,z);  
+        SM = CrossEntropyWithSoftmax(labels, FF)
+    }
+    #SoftMax Base Feed Forward
+    SMBFF(x,r,c, labels)
+    {
+        BFF = BFF(x,r,c);  
+        SM = CrossEntropyWithSoftmax(labels, BFF)
+    }
+    RFFD_R(x1, w1, b1)={Dropout(RectifiedLinear(Plus(Times(w1,x1),b1)))}
+    
+    WtObjFcn(o1,w1,o2,w2)
+     {
+		A1=Constant(w1)
+		A2=Constant(w2)
+		T1=Times(A1,o1)
+		T2=Times(A2,o2)
+		O=Plus(T1,T2) 
+     }
+
+]
+
+ndlMacroUse2=[
+    # constants defined
+    # Sample, Hidden, and Label dimensions
+    SDim=784
+    HDim=256
+    LDim=10
+
+    features=Input(SDim, tag=feature)
+    labels=Input(LDim, tag=label)
+
+    # compute mean/stddev for mean/stddev normalization
+    fmean = Mean(features);
+    finvstd=InvStdDev(features)
+    finput=PerDimMeanVarNormalization(features, fmean, finvstd)
+
+    # Layer operations
+    L1 = RBFF(finput, HDim, SDim)
+    L2 = RBFF(L1, HDim, HDim)
+    L3 = RBFF(L2, HDim, HDim)
+    CE = SMBFF(L3, LDim, HDim, labels, tag=Criteria)
+    Err=ErrorPrediction(labels, CE.BFF, tag=Eval)
+
+    # rootNodes defined here
+    OutputNodes=(CE.BFF)
+]
+ndlMacroUseCNNSubSample2ZeroPadding=[
+    # constants defined
+    # Sample, Hidden, and Label dimensions
+    SDim=784
+    LDim=10
+
+    features=Input(SDim, tag=feature)
+    labels=Input(LDim, tag=label)
+    
+    #convolution
+    inputWidth=28
+    inputHeight=28
+    inputChannels=1
+    kernelWidth=5
+    kernelHeight=5
+    outputChannels=24
+    horizontalSubsample=2
+    verticalSubsample=2
+    
+    # weight[outputChannels, kernelWidth * kernelHeight * inputChannels]
+    cvweight=Parameter(outputChannels, 25)
+    cv = Convolution(cvweight, features, inputWidth, inputHeight, inputChannels, kernelWidth, kernelHeight, outputChannels,horizontalSubsample, verticalSubsample, zeroPadding=true)
+    
+    #one bias per channel
+    cvbias=Parameter(outputChannels, 1)
+    
+    cvplusbias=Plus(cv, cvbias);
+    nlcv=Sigmoid(cvplusbias);
+    
+    #outputWidth = (m_inputWidth-1)/m_horizontalSubsample + 1;
+    outputWidth=14
+    #outputHeight = (m_inputHeight-1)/m_verticalSubsample + 1;
+    outputHeight=14
+    
+    #maxpooling
+    windowWidth=2
+    windowHeight=2
+    stepW=2
+    stepH=2
+    mp=MaxPooling(nlcv, outputWidth, outputHeight, outputChannels, windowWidth, windowHeight, stepW, stepH)
+    
+    #m_outputWidth = (m_inputWidth-m_windowWidth)/m_horizontalSubsample + 1;
+    mpoutputWidth=7
+    #m_outputHeight = (m_inputHeight-m_windowHeight)/m_verticalSubsample + 1;
+    mpoutputHeight=7
+    #m_outputSizePerSample = m_outputWidth * m_outputHeight * m_channels;
+    mpoutputSizePerSample=1176
+    # Layer operations
+    
+    HDim=128
+    L1 = SBFF(mp, HDim, mpoutputSizePerSample)
+    CE = SMBFF(L1, LDim, HDim, labels, tag=Criteria)
+    Err=ErrorPrediction(labels, CE.BFF, tag=Eval)
+
+    # rootNodes defined here
+    OutputNodes=(CE.BFF)
+]
+
+ndlMacroUseCNNSubSample2=[
+    # constants defined
+    # Sample, Hidden, and Label dimensions
+    SDim=784
+    LDim=10
+
+    features=ImageInput(28,28, 1, tag=feature)
+    labels=Input(LDim, tag=label)
+    
+    #convolution
+    inputWidth=28
+    inputHeight=28
+    inputChannels=1
+    kernelWidth=5
+    kernelHeight=5
+    outputChannels=24
+    horizontalSubsample=2
+    verticalSubsample=2
+    
+    # weight[outputChannels, kernelWidth * kernelHeight * inputChannels]
+    cvweight=Parameter(outputChannels, 25)
+    cv = Convolution(cvweight, features, kernelWidth, kernelHeight, outputChannels,horizontalSubsample, verticalSubsample, zeroPadding=false)
+    
+    #one bias per channel
+    cvbias=Parameter(outputChannels, 1)
+    
+    cvplusbias=Plus(cv, cvbias);
+    nlcv=Sigmoid(cvplusbias);
+    #nlcv=Sigmoid(cv);
+    
+    #outputWidth = (m_inputWidth-m_kernelWidth)/m_horizontalSubsample + 1;
+    outputWidth=12
+    #outputHeight = (m_inputHeight-m_kernelHeight)/m_verticalSubsample + 1;
+    outputHeight=12
+    
+    #maxpooling
+    windowWidth=2
+    windowHeight=2
+    stepW=2
+    stepH=2
+    mp=MaxPooling(nlcv, windowWidth, windowHeight, stepW, stepH)
+    
+    #m_outputWidth = (m_inputWidth-m_windowWidth)/m_horizontalSubsample + 1;
+    mpoutputWidth=6
+    #m_outputHeight = (m_inputHeight-m_windowHeight)/m_verticalSubsample + 1;
+    mpoutputHeight=6
+    #m_outputSizePerSample = m_outputWidth * m_outputHeight * m_channels;
+    mpoutputSizePerSample=864
+    # Layer operations
+    
+    HDim=128
+    L1 = SBFF(mp, HDim, mpoutputSizePerSample)
+    CE = SMBFF(L1, LDim, HDim, labels, tag=Criteria)
+    Err=ErrorPrediction(labels, CE.BFF, tag=Eval)
+
+    # rootNodes defined here
+    OutputNodes=(CE.BFF)
+]
+
+ndlMacroUseCNN=[
+    # constants defined
+    # Sample, Hidden, and Label dimensions
+    inputWidth=28
+    inputHeight=28
+    inputChannels=1
+    
+    SDim=784
+    LDim=10
+
+    features=ImageInput(inputWidth, inputHeight, inputChannels, 1, tag=feature)
+    labels=Input(LDim, tag=label)
+    
+    #convolution
+    kernelWidth=5
+    kernelHeight=5
+    outputChannels=24
+    horizontalSubsample=1
+    verticalSubsample=1
+    
+    # weight[outputChannels, kernelWidth * kernelHeight * inputChannels]
+    # cvweight=Parameter(outputChannels, 25)
+    cvweight=Parameter(0, 0)  #CNTK will derive the dimension automatically
+    cv = Convolution(cvweight, features, kernelWidth, kernelHeight, outputChannels,horizontalSubsample, verticalSubsample, zeroPadding=false)
+    
+    #one bias per channel
+    cvbias=Parameter(outputChannels, 1)
+    
+    cvplusbias=Plus(cv, cvbias);
+    nlcv=Sigmoid(cvplusbias);
+    
+    #maxpooling
+    windowWidth=2
+    windowHeight=2
+    stepW=2
+    stepH=2
+    mp=MaxPooling(nlcv, windowWidth, windowHeight, stepW, stepH)
+    
+    mpoutputSizePerSample=0
+    # Layer operations
+    
+    HDim=128
+    L1 = SBFF(mp, HDim, 0)
+    CE = SMBFF(L1, LDim, HDim, labels, tag=Criteria)
+    Err=ErrorPrediction(labels, CE.BFF, tag=Eval)
+
+    # rootNodes defined here
+    OutputNodes=(CE.BFF)
+]
+
+ndlMacroUseNoBase=[
+    # constants defined
+    # Sample, Hidden, and Label dimensions
+    SDim=784
+    HDim=256
+    LDim=10
+
+    # Weight, Bias, features and label inputs
+    B0=Parameter(HDim, init=fixedvalue, value=0)
+    W0=Parameter(HDim, SDim, init=uniform)
+    B1=Parameter(HDim, init=fixedvalue, value=0)
+    W1=Parameter(HDim, HDim, init=uniform)
+    B2=Parameter(HDim, init=fixedvalue, value=0)
+    W2=Parameter(HDim, HDim, init=uniform)
+    BTop=Parameter(LDim, init=fixedvalue, value=0)
+    WTop=Parameter(LDim, HDim, init=uniform)
+
+    features=Input(SDim, tag=feature)
+    labels=Input(LDim, tag=label)
+
+    # Layer operations
+    L1 = RFFD(features, HDim, SDim)
+    L2 = RFFD(L1, HDim, HDim)
+    L3 = RFFD(L2, HDim, HDim)
+    CE = SMFF(L3, LDim, SDim, labels, tag=Criteria)
+    Err=ErrorPrediction(labels, CE.BFF, tag=Eval)
+    # rootNodes defined here
+    OutputNodes=(CE.BFF)
+]
+
+ndlMacroUseMask=[
+    # constants defined
+    # Sample, Hidden, and Label dimensions
+    SDim=784
+    HDim=256
+    LDim=10
+
+    features=Input(SDim, tag=feature)
+    labels=Input(LDim, tag=label)
+
+    # compute mean/stddev for mean/stddev normalization
+    fmean = Mean(features);
+    finvstd=InvStdDev(features)
+    finput=PerDimMeanVarNormalization(features, fmean, finvstd)
+
+    # Layer operations
+    L1 = RBFF(finput, HDim, SDim)
+    L2 = RBFF(L1, HDim, HDim)
+    L3 = RBFF(L2, HDim, HDim)
+    
+    # mask layers
+    ML1=RBFF(finput, HDim, SDim)
+    ML2=RBFF(ML1, HDim, HDim)
+    
+    # mask
+    L4=ElementTimes(L3, ML2)
+    
+    CE = SMBFF(L4, LDim, HDim, labels, tag=Criteria)
+    Err=ErrorPrediction(labels, CE.BFF, tag=Eval)
+    
+    # output nodes
+    Prior=Mean(labels)
+    LP=Log(Prior)
+    O=Minus(CE.BFF, LP)
+
+    # rootNodes defined here
+    OutputNodes=(O)
+    CriteriaNodes=(CE)
+    EvaluationNodes(Err)
+]

From c467e1bb414c1e19ab6eb2e99a3780b1d4405bfc Mon Sep 17 00:00:00 2001
From: Dong Yu <dongyu@microsoft.com>
Date: Wed, 13 May 2015 10:47:35 +0800
Subject: [PATCH 11/49] add SVD command to CNTK book.

---
 ...ook-20150415.pdf => CNTKBook-20150513.pdf} | 29203 ++++++++--------
 .../lyx/CNTKBook_CNTK_Chapter.lyx             |   156 +
 2 files changed, 14840 insertions(+), 14519 deletions(-)
 rename papers/CNTK-TechReport/lyx/{CNTKBook-20150415.pdf => CNTKBook-20150513.pdf} (75%)

diff --git a/papers/CNTK-TechReport/lyx/CNTKBook-20150415.pdf b/papers/CNTK-TechReport/lyx/CNTKBook-20150513.pdf
similarity index 75%
rename from papers/CNTK-TechReport/lyx/CNTKBook-20150415.pdf
rename to papers/CNTK-TechReport/lyx/CNTKBook-20150513.pdf
index 86bd51a1e..1d8c9d00c 100644
--- a/papers/CNTK-TechReport/lyx/CNTKBook-20150415.pdf
+++ b/papers/CNTK-TechReport/lyx/CNTKBook-20150513.pdf
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 trailer
-<< /Size 4443
-/Root 4441 0 R
-/Info 4442 0 R
-/ID [<CB47115EF95B7081DE03E16276B367AD> <CB47115EF95B7081DE03E16276B367AD>] >>
+<< /Size 4474
+/Root 4472 0 R
+/Info 4473 0 R
+/ID [<077796DE00BBBDC9B4E1858B2190B91D> <077796DE00BBBDC9B4E1858B2190B91D>] >>
 startxref
-1418019
+1423335
 %%EOF
diff --git a/papers/CNTK-TechReport/lyx/CNTKBook_CNTK_Chapter.lyx b/papers/CNTK-TechReport/lyx/CNTKBook_CNTK_Chapter.lyx
index 6e7a40bc2..9c91fcba5 100644
--- a/papers/CNTK-TechReport/lyx/CNTKBook_CNTK_Chapter.lyx
+++ b/papers/CNTK-TechReport/lyx/CNTKBook_CNTK_Chapter.lyx
@@ -4418,6 +4418,162 @@ ndlMacros
  
 \end_layout
 
+\begin_layout Subsection
+SVD Command
+\begin_inset Index idx
+status open
+
+\begin_layout Plain Layout
+SVD Command
+\end_layout
+
+\end_inset
+
+
+\end_layout
+
+\begin_layout Standard
+This command conducts SVD decomposition for learnable parameters.
+ For example:
+\end_layout
+
+\begin_layout Standard
+\begin_inset listings
+inline false
+status open
+
+\begin_layout Plain Layout
+
+svd=[
+\end_layout
+
+\begin_layout Plain Layout
+
+  action=SVD 
+\end_layout
+
+\begin_layout Plain Layout
+
+  modelPath=train
+\backslash
+lstm.model.67
+\end_layout
+
+\begin_layout Plain Layout
+
+  outputmodelPath=train
+\backslash
+lstm.model.svd
+\end_layout
+
+\begin_layout Plain Layout
+
+  SVDConfig=NodeConfigs 
+\end_layout
+
+\begin_layout Plain Layout
+
+] 
+\end_layout
+
+\end_inset
+
+Here we list the associated parameter blocks.
+\end_layout
+
+\begin_layout Itemize
+\begin_inset Index idx
+status open
+
+\begin_layout Plain Layout
+modelPath
+\end_layout
+
+\end_inset
+
+modelPath – specifies where to load the initial model 
+\end_layout
+
+\begin_layout Itemize
+\begin_inset Index idx
+status open
+
+\begin_layout Plain Layout
+outputmodelPath
+\end_layout
+
+\end_inset
+
+outputmodelPath – specifies where to save the revised model 
+\end_layout
+
+\begin_layout Itemize
+\begin_inset Index idx
+status open
+
+\begin_layout Plain Layout
+SVDConfig
+\end_layout
+
+\end_inset
+
+SVDConfig – a config file which specifies how the SVD is performed for different
+ groups of nodes.
+ This config is in a two-column format:
+\end_layout
+
+\begin_deeper
+\begin_layout Standard
+\begin_inset listings
+inline false
+status open
+
+\begin_layout Plain Layout
+
+<NodeNameRegex> <float>
+\end_layout
+
+\end_inset
+
+
+\end_layout
+
+\begin_layout Standard
+The first column is a regular expression which will match the node name
+ in one group.
+ The second column is a float indicating what percentage of SVD-energy will
+ be kept after SVD, where SVD-energy is defined as the sum of singular values.
+ For example, the config
+\end_layout
+
+\begin_layout Standard
+\begin_inset listings
+inline false
+status open
+
+\begin_layout Plain Layout
+
+LSTMoutput[1-3].Wx[ifco] 0.4 
+\end_layout
+
+\begin_layout Plain Layout
+
+LSTMoutput[1-3].Wh[ifco] 0.6
+\end_layout
+
+\end_inset
+
+
+\end_layout
+
+\begin_layout Standard
+will cause a more aggressive SVD (0.4) decomposition for the non-recurrent
+ connections (from x to i,f,c,o gates) in LSTM and less aggressive SVD decomposi
+tion for recurrent connections (from h to i,f,c,o gates), where the parameter
+ names are defined in the NDL.
+\end_layout
+
+\end_deeper
 \begin_layout Subsection
 Dumpnode Command
 \begin_inset Index idx

From df2e4a64efd73962bdcc422ea3542b72360fdb84 Mon Sep 17 00:00:00 2001
From: Frank Seide <fseide@microsoft.com>
Date: Thu, 14 May 2015 16:35:38 -0700
Subject: [PATCH 12/49] (fixed a few warnings related to printf format
 specifiers)

---
 MachineLearning/cn/ComputationNetwork.h   | 4 ++--
 MachineLearning/cn/SimpleNetworkBuilder.h | 6 +++---
 2 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/MachineLearning/cn/ComputationNetwork.h b/MachineLearning/cn/ComputationNetwork.h
index 1ac287e58..fc2851789 100644
--- a/MachineLearning/cn/ComputationNetwork.h
+++ b/MachineLearning/cn/ComputationNetwork.h
@@ -2151,7 +2151,7 @@ public:
             {
                 float keepratio = group.second; 
                 fprintf(stderr, "--------------------------------------------------------------------------------------------\n");
-                fprintf(stderr, "ParameterSVD: start to process group %d with KeepRatio=%.2f\n", groupID++, keepratio);
+                fprintf(stderr, "ParameterSVD: start to process group %d with KeepRatio=%.2f\n", (int) groupID++, keepratio);
                 fprintf(stderr, "--------------------------------------------------------------------------------------------\n");
                 for (auto name : group.first)
                 {
@@ -2204,7 +2204,7 @@ public:
 
                     std::chrono::duration<double>  elapsedtime = enTime - stTime;
                     fprintf(stderr, "Performing SVD for a %5d-by-%-5d matrix (node name: %-20ls) ---  computation time %5.2f secs ;  keep %4.1f%% energy ===> keep %5d svd values (reduce to %4.1f%% parameters) \n",
-                        m, n, name.c_str(), elapsedtime.count(), keepratio*100, r, ((m+n)*r+0.0f)/m/n*100);
+                        (int)m, (int)n, name.c_str(), elapsedtime.count(), keepratio * 100, (int)r, ((m + n)*r + 0.0f) / m / n * 100);
 
 
                     Matrix<ElemType> redU = U.ColumnSlice(0, r);        // redU in R^ {mXr}
diff --git a/MachineLearning/cn/SimpleNetworkBuilder.h b/MachineLearning/cn/SimpleNetworkBuilder.h
index c96aa0110..da37a9524 100644
--- a/MachineLearning/cn/SimpleNetworkBuilder.h
+++ b/MachineLearning/cn/SimpleNetworkBuilder.h
@@ -454,17 +454,17 @@ namespace Microsoft { namespace MSR { namespace CNTK {
                 
                 if (layerType == "perceptron")
                 {
-                    fprintf(stderr, "DBN: Reading (%d x %d) perceptron\n", wts.GetNumRows(), wts.GetNumCols());
+                    fprintf(stderr, "DBN: Reading (%d x %d) perceptron\n", (int)wts.GetNumRows(), (int)wts.GetNumCols());
                     output = m_net->Plus(m_net->Times(w, input, nameOfTimes), b, nameOfPlus);
                 }
                 else if (layerType == "rbmisalinearbernoulli" )
                 {
-                    fprintf(stderr, "DBN: Reading (%d x %d) linear layer\n", wts.GetNumRows(), wts.GetNumCols());
+                    fprintf(stderr, "DBN: Reading (%d x %d) linear layer\n", (int)wts.GetNumRows(), (int)wts.GetNumCols());
                     output = m_net->Plus(m_net->Times(w, input, nameOfTimes), b, nameOfPlus);
                 }
                 else // assume rbmbernoullibernoulli
                 {
-                    fprintf(stderr, "DBN: Reading (%d x %d) non-linear layer\n", wts.GetNumRows(), wts.GetNumCols());
+                    fprintf(stderr, "DBN: Reading (%d x %d) non-linear layer\n", (int)wts.GetNumRows(), (int)wts.GetNumCols());
                     output = ApplyNonlinearFunction(m_net->Plus(m_net->Times(w, input, nameOfTimes), b, nameOfPlus), i, nameOfH);
                     if (m_addDropoutNodes)
                         input = m_net->Dropout(output, L"Drop" + nameOfH);

From 615412679423c3d1f208443ed3aab7332d5bfdf8 Mon Sep 17 00:00:00 2001
From: Frank Seide <fseide@microsoft.com>
Date: Thu, 14 May 2015 17:49:24 -0700
Subject: [PATCH 13/49] removed explicit Project Reference from CNTKMath to
 CNTHMathCUDA, to allow building even if CNTKMathCUDA failed to load (with
 #define CPUONLY in BestGpu.h)

---
 Math/Math/Math.vcxproj | 5 -----
 1 file changed, 5 deletions(-)

diff --git a/Math/Math/Math.vcxproj b/Math/Math/Math.vcxproj
index 742b4c5b8..955b5519b 100644
--- a/Math/Math/Math.vcxproj
+++ b/Math/Math/Math.vcxproj
@@ -195,11 +195,6 @@
   <ItemGroup>
     <None Include="GPUMatrix.h" />
   </ItemGroup>
-  <ItemGroup>
-    <ProjectReference Include="CNTKMathCUDA.vcxproj">
-      <Project>{b3dd765e-694e-4494-bad7-37bbf2942517}</Project>
-    </ProjectReference>
-  </ItemGroup>
   <Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
   <ImportGroup Label="ExtensionTargets" />
 </Project>
\ No newline at end of file

From 8a5163b705f538fd61ffa9d1904b63cc34c3e9f1 Mon Sep 17 00:00:00 2001
From: Dong Yu <dongyu@microsoft.com>
Date: Fri, 15 May 2015 02:23:02 -0700
Subject: [PATCH 14/49] Display the start index and the number of rows in the
 RowSlice validation step

Change the forward computation code in the GMMLogLikelihood node to make it more stable
update the NDLExamples.ndl to include node to control stddev in the GMMLogLikihood node.
---
 ExampleSetups/NDLExamples.ndl                 | 10 ++++-
 MachineLearning/cn/CompositeComputationNode.h | 40 ++++++++++++++-----
 MachineLearning/cn/ComputationNode.h          | 30 ++++++++++++++
 3 files changed, 67 insertions(+), 13 deletions(-)

diff --git a/ExampleSetups/NDLExamples.ndl b/ExampleSetups/NDLExamples.ndl
index 976de4a07..1558f9246 100644
--- a/ExampleSetups/NDLExamples.ndl
+++ b/ExampleSetups/NDLExamples.ndl
@@ -58,7 +58,8 @@ ndlTestGMM=[
     LogStddev=Parameter(GMMComponent, 1)
     
     LL=GMMLL(UnnormedPrior, Means, LogStddev, L3)
-
+    LLAll=SumElements(LL)
+    NLL=Negate(LLALL, tag=Criteria)
 
     # rootNodes defined here
     OutputNodes=(NLL)
@@ -85,7 +86,12 @@ ndlTestMDN=[
     
     UnnormedPrior =  BFF(L3, GMMComponent, HDim)
     Means=BFF(L3, SizeOfAllMeans, HDim)
-    LogStddev=BFF(L3, GMMComponent, HDim)
+    
+    #it's important to control the range of logstddev
+    LogStddev0=BFF(L3, GMMComponent, MDim)
+    LogStddev1=Tanh(LogStddev0)
+    scaleF=Const(2)    
+    LogStddev=Scale(scaleF, LogStddev1)    
     
     LL=GMMLL(UnnormedPrior, Means, LogStddev, labels)
     LLAll=SumElements(LL)
diff --git a/MachineLearning/cn/CompositeComputationNode.h b/MachineLearning/cn/CompositeComputationNode.h
index 33edb3385..7ebc83777 100644
--- a/MachineLearning/cn/CompositeComputationNode.h
+++ b/MachineLearning/cn/CompositeComputationNode.h
@@ -1892,7 +1892,7 @@ namespace Microsoft { namespace MSR { namespace CNTK {
 
         //input0=unnormedPrior, input1=mean, input2=logstddev, input3=feature
         //If we want to speed up we need to replace following code with a several specialized GPU functions
-        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, const Matrix<ElemType>& unnormedPrior, const Matrix<ElemType>& mean, const Matrix<ElemType>& logstddev,
+        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, const Matrix<ElemType>& unnormedPrior, const Matrix<ElemType>& mean,  Matrix<ElemType>& logstddev,
             const Matrix<ElemType>& feature, Matrix<ElemType>& prior, Matrix<ElemType>& stddev, Matrix<ElemType>& normedDeviationVectors,
             Matrix<ElemType>& normedDeviation, Matrix<ElemType>& posterior, Matrix<ElemType>& temp)
         {
@@ -1901,34 +1901,45 @@ namespace Microsoft { namespace MSR { namespace CNTK {
             size_t featureDim = feature.GetNumRows();
 
             //compute prior which is softmax of unnormedPrior
-            prior.AssignLogSoftmaxOf(unnormedPrior, true);
+            prior.AssignLogSoftmaxOf(unnormedPrior, true);  //log prior
+
             prior.InplaceExp();
 
             //compute stddev
             stddev.AssignExpOf(logstddev);
 
+#if DUMPOUTPUT
+            unnormedPrior.Print("unnormedPrior", 0, min(5, unnormedPrior.GetNumRows() - 1), 0, min(10, unnormedPrior.GetNumCols() - 1));
+            mean.Print("mean", 0, min(5, mean.GetNumRows() - 1), 0, min(10, mean.GetNumCols() - 1));
+            logstddev.Print("logstddev", 0, min(5, logstddev.GetNumRows() - 1), 0, min(10, logstddev.GetNumCols() - 1));
+
+            prior.Print("prior", 0, min(5, prior.GetNumRows() - 1), 0, min(10, prior.GetNumCols() - 1));
+            stddev.Print("stddev", 0, min(5, stddev.GetNumRows() - 1), 0, min(10, stddev.GetNumCols() - 1));
+#endif
+
             //compute normedDeviation <-- ||x-u_c||^2/(stddev^2)
             normedDeviationVectors.AssignRepeatOf(feature, numComponent, 1);
             normedDeviationVectors -= mean; //each column of the mean has multiple mean components
             normedDeviationVectors.Reshape(featureDim, numSamples* numComponent);  //now each column is feature-mean_i
 
             normedDeviation.AssignVectorNorm2Of(normedDeviationVectors, true);
+            normedDeviation ^= 2;
             temp.AssignRepeatOf(stddev, 1, numSamples / stddev.GetNumCols());  //stddev.GetNumCols() is either 1 or =numSamples
             temp.Reshape(1, temp.GetNumElements());  //one stddev value for each component for each sample
+            temp ^= 2;
             normedDeviation.ElementDivideBy(temp);  //normedDeviation and temp have same dim (1, numSamples* numComponent)
-            normedDeviation ^= 2;
 
             //compute  normedDeviationVectors <-- (x-u_c)/(stddev^2)
-            normedDeviationVectors.RowElementDivideBy(temp); //temp is stddev. divide once  
             normedDeviationVectors.RowElementDivideBy(temp);  //divide twice
             normedDeviationVectors.Reshape(featureDim*numComponent, numSamples);  //reshape back
 
             //compute per-component likelihood
             posterior.AssignProductOf(-0.5f, normedDeviation); //posterior  <-- -||x-u_c||^2/(stddev^2)/2 and in (1, numSamples* numComponent) dim
+            temp.InplaceLog();
+            temp *= ((ElemType)numComponent / 2.0f); //temp <-- stddev^c and in (1, numSamples* numComponent) dim
+            posterior -= temp;  // posterior  <-- exp[-||x-u_c||^2/(stddev^2)/2]/(stddev^c)
+            posterior -= (ElemType)(numComponent / 2.0f*log(TWO_PI)); //likelihood for each component and sample is now computed and stored in posterior
             posterior.InplaceExp(); //posterior  <-- exp(-||x-u_c||^2/(stddev^2)/2)
-            temp ^= (ElemType)numComponent; //temp <-- stddev^c and in (1, numSamples* numComponent) dim
-            posterior.RowElementDivideBy(temp);  // posterior  <-- exp[-||x-u_c||^2/(stddev^2)/2]/(stddev^c)
-            posterior /= (ElemType)pow(TWO_PI, numComponent / 2.0f); //likelihood for each component and sample is now computed and stored in posterior
 
             normedDeviation.Reshape(numComponent, numSamples);  //reshape back
             posterior.Reshape(numComponent, numSamples);  //reshape back
@@ -1937,18 +1948,25 @@ namespace Microsoft { namespace MSR { namespace CNTK {
             if (unnormedPrior.GetNumCols() == numSamples)  //each sample has different prior
                 posterior.ElementMultiplyWith(prior);
             else  //all samples share the same prior
-                posterior.ColumnElementMultiplyWith(prior);  
+                posterior.ColumnElementMultiplyWith(prior);
 
             //compute GMM log-likelihood
             Matrix<ElemType>::Multiply(ConstOnes(1, numComponent, posterior.GetDeviceId()), false, posterior, false, functionValues);  //functionValues <-- total likelihood
             posterior.RowElementDivideBy(functionValues); //posterior <-- per-comp likelihood / total likelihood
             functionValues.InplaceLog(); //log likelihood
 
+#if DUMPOUTPUT
+            temp.Print("temp", 0, min(5, temp.GetNumRows() - 1), 0, min(10, temp.GetNumCols() - 1));
+            normedDeviation.Print("normedDeviation", 0, min(5, normedDeviation.GetNumRows() - 1), 0, min(10, normedDeviation.GetNumCols() - 1));
+
+            posterior.Print("posterior", 0, min(5, posterior.GetNumRows() - 1), 0, min(10, posterior.GetNumCols() - 1));
+            functionValues.Print("functionValues", 0, min(5, functionValues.GetNumRows() - 1), 0, min(10, functionValues.GetNumCols() - 1));
+
+            functionValues.Print("GMMLogLikelihoodNode");
+#endif
+
 #if NANCHECK
             functionValues.HasNan("GMMLogLikelihood");
-#endif
-#if DUMPOUTPUT
-            functionValues.Print("GMMLogLikelihoodNode");
 #endif
         }
 
diff --git a/MachineLearning/cn/ComputationNode.h b/MachineLearning/cn/ComputationNode.h
index 0e0a3b0a7..0c6e5f9e7 100644
--- a/MachineLearning/cn/ComputationNode.h
+++ b/MachineLearning/cn/ComputationNode.h
@@ -2676,6 +2676,36 @@ protected:  \
         virtual const std::wstring OperationName() const {return TypeName();}
         static const std::wstring TypeName() {return L"RowSlice";} 
 
+        virtual void PrintSelfBeforeValidation(bool allowNulls = false) const
+        {
+            fprintf(stderr, "\nValidating --> %ls = %ls", NodeName().c_str(), OperationName().c_str());
+
+            if (!IsLeaf())
+            {
+                fprintf(stderr, "(");
+                for (size_t i = 0; i<ChildrenSize(); i++)
+                {
+                    ComputationNodePtr child = Inputs(i);
+                    if (i > 0)
+                        fprintf(stderr, ", ");
+
+                    if (child == nullptr)
+                    {
+                        if (allowNulls)
+                        {
+                            fprintf(stderr, "NULL");
+                            continue;
+                        }
+                        throw runtime_error("One of the children is missing.");
+                    }
+
+                    fprintf(stderr, "%ls[%lu, %lu]", child->NodeName().c_str(), child->FunctionValues().GetNumRows(), child->FunctionValues().GetNumCols());
+
+                }
+                fprintf(stderr, ", StartIndex=%lu, NumOfRows=%lu)", m_startIndex, m_numRows);
+            }
+        }
+
         virtual void ComputeInputPartial(const size_t inputIndex)
         {
             if (inputIndex != 0)

From c8b7a122424ed7d6be538731ec6ec3f64a63ea8d Mon Sep 17 00:00:00 2001
From: erw <erw@microsoft.com>
Date: Fri, 8 May 2015 14:59:03 -0700
Subject: [PATCH 15/49] Add cudart64_70.dll to delay loaded DLLs

---
 MachineLearning/CNTKEval/CNTKEval.vcxproj | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/MachineLearning/CNTKEval/CNTKEval.vcxproj b/MachineLearning/CNTKEval/CNTKEval.vcxproj
index 248242d64..b9ec7a4a2 100644
--- a/MachineLearning/CNTKEval/CNTKEval.vcxproj
+++ b/MachineLearning/CNTKEval/CNTKEval.vcxproj
@@ -99,7 +99,7 @@
       <AdditionalDependencies>Delayimp.lib;cntkMath.lib;kernel32.lib;user32.lib;gdi32.lib;winspool.lib;comdlg32.lib;advapi32.lib;shell32.lib;ole32.lib;oleaut32.lib;uuid.lib;odbc32.lib;odbccp32.lib;%(AdditionalDependencies)</AdditionalDependencies>
       <AdditionalLibraryDirectories>..\..\math\$(Platform)\$(Configuration);$(SolutionDir)$(Platform)\$(Configuration)\</AdditionalLibraryDirectories>
       <Profile>true</Profile>
-      <DelayLoadDLLs>CNTKMath.dll;nvml.dll</DelayLoadDLLs>
+      <DelayLoadDLLs>CNTKMath.dll;nvml.dll; cudart64_70.dll</DelayLoadDLLs>
     </Link>
   </ItemDefinitionGroup>
   <ItemGroup>

From c1e949ea044777e83708792390330f08132e91f4 Mon Sep 17 00:00:00 2001
From: erw <erw@microsoft.com>
Date: Mon, 11 May 2015 12:03:32 -0700
Subject: [PATCH 16/49] CNTKEval dll project (debug) is revised from /MTd to
 /MDd (Multi-thread DLL debug) such that one commond CRT is used.

---
 MachineLearning/CNTKEval/CNTKEval.vcxproj | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/MachineLearning/CNTKEval/CNTKEval.vcxproj b/MachineLearning/CNTKEval/CNTKEval.vcxproj
index b9ec7a4a2..2e179069d 100644
--- a/MachineLearning/CNTKEval/CNTKEval.vcxproj
+++ b/MachineLearning/CNTKEval/CNTKEval.vcxproj
@@ -88,7 +88,7 @@
       <AdditionalIncludeDirectories>..\..\common\include;..\..\math\math</AdditionalIncludeDirectories>
       <OpenMPSupport>false</OpenMPSupport>
       <AdditionalOptions>/d2Zi+ %(AdditionalOptions)</AdditionalOptions>
-      <RuntimeLibrary>MultiThreaded</RuntimeLibrary>
+      <RuntimeLibrary>MultiThreadedDLL</RuntimeLibrary>
       <TreatWarningAsError>true</TreatWarningAsError>
     </ClCompile>
     <Link>

From 58b291371dcdd2f452b36c5592a6d182852ced56 Mon Sep 17 00:00:00 2001
From: erw <erw@microsoft.com>
Date: Fri, 15 May 2015 11:21:54 -0700
Subject: [PATCH 17/49] Put IEvaluateModel::Init to public, as CNTKEval::Init
 is public

---
 Common/Include/Eval.h | 4 +---
 1 file changed, 1 insertion(+), 3 deletions(-)

diff --git a/Common/Include/Eval.h b/Common/Include/Eval.h
index 1269c6140..c61975afe 100644
--- a/Common/Include/Eval.h
+++ b/Common/Include/Eval.h
@@ -68,8 +68,6 @@ class Eval : public IEvaluateModel<ElemType>, protected Plugin
 private:
     IEvaluateModel<ElemType> *m_eval;  // evaluation class pointer
 
-    virtual void Init(const std::string& config);
-
     void GetEvalClass(const std::string& config);
 
     // Destroy - cleanup and remove this class
@@ -98,7 +96,7 @@ public:
     // inputs - map from node name to input vector
     // outputs - map from node name to output vector, outputs vectors need to be preallocated by caller, sizing will happen during evaluation
     virtual void Evaluate(std::map<std::wstring, std::vector<ElemType>*>& inputs, std::map<std::wstring, std::vector<ElemType>*>& outputs);
-
+    virtual void Init(const std::string& config);
     virtual void ResetState();
 };
 

From dd917f3cefe646efbf8075a7bfd4169dc794d6bb Mon Sep 17 00:00:00 2001
From: erw <erw@microsoft.com>
Date: Fri, 15 May 2015 11:24:30 -0700
Subject: [PATCH 18/49] Delay loading cu???64_70 instead of cu???64_65 as we
 are already at cuda70

---
 Math/Math/Math.vcxproj | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/Math/Math/Math.vcxproj b/Math/Math/Math.vcxproj
index 955b5519b..d6813ecfb 100644
--- a/Math/Math/Math.vcxproj
+++ b/Math/Math/Math.vcxproj
@@ -80,7 +80,7 @@
       <AdditionalDependencies>libacml_mp_dll.lib;%(AdditionalDependencies)</AdditionalDependencies>
       <AdditionalLibraryDirectories>
       </AdditionalLibraryDirectories>
-      <DelayLoadDLLs>cublas64_65.dll;cusparse64_65.dll;curand64_65.dll;cudart64_65.dll;libacml_dll.dll;libacml_mp_dll.dll;nvcuda.dll;%(DelayLoadDLLs)</DelayLoadDLLs>
+      <DelayLoadDLLs>cublas64_70.dll;cusparse64_70.dll;curand64_70.dll;cudart64_70.dll;libacml_dll.dll;libacml_mp_dll.dll;nvcuda.dll;%(DelayLoadDLLs)</DelayLoadDLLs>
       <Profile>true</Profile>
     </Link>
     <PostBuildEvent>
@@ -132,7 +132,7 @@
       </AdditionalLibraryDirectories>
       <AdditionalDependencies>libacml_mp_dll.lib;%(AdditionalDependencies)</AdditionalDependencies>
       <Profile>true</Profile>
-      <DelayLoadDLLs>libacml_mp_dll.dll;%(DelayLoadDLLs)</DelayLoadDLLs>
+      <DelayLoadDLLs>cublas64_70.dll;cusparse64_70.dll;curand64_70.dll;cudart64_70.dll;libacml_dll.dll;libacml_mp_dll.dll;nvcuda.dll;%(DelayLoadDLLs)</DelayLoadDLLs>
     </Link>
     <PostBuildEvent>
       <Command>xcopy /D /I /Y "$(ACML_PATH)\lib\*.dll" $(OutputPath)</Command>

From 0913d9f024fb6c65a7d374096897f9904ec8eb51 Mon Sep 17 00:00:00 2001
From: Frank Seide <fseide@microsoft.com>
Date: Fri, 15 May 2015 16:40:28 -0700
Subject: [PATCH 19/49] moved the tech report and tutorial into Documentation

---
 .../CNTK-TechReport/figures.vsdm                    | Bin
 .../figures/CN+TrainingCriterion.pdf                | Bin
 .../figures/CN+TrainingCriterion.png                | Bin
 .../CNTK-TechReport/figures/CN-1HiddenNN.pdf        | Bin
 .../CNTK-TechReport/figures/CN-1HiddenNN.png        | Bin
 .../CNTK-TechReport/figures/CN-2Inputs.pdf          | Bin
 .../CNTK-TechReport/figures/CN-2Inputs.png          | Bin
 .../figures/CN-EfficientGradient.pdf                | Bin
 .../figures/CN-EfficientGradient.png                | Bin
 .../CNTK-TechReport/figures/CN-NaiveGradient.pdf    | Bin
 .../CNTK-TechReport/figures/CN-NaiveGradient.png    | Bin
 .../CNTK-TechReport/figures/CN-ShareWeight.pdf      | Bin
 .../CNTK-TechReport/figures/CN-ShareWeight.png      | Bin
 .../CNTK-TechReport/figures/CN-WithDelayNode.pdf    | Bin
 .../CNTK-TechReport/figures/CN-WithDelayNode.png    | Bin
 .../CNTK-TechReport/figures/CNNComputation.pdf      | Bin
 .../CNTK-TechReport/figures/CNNComputation.png      | Bin
 .../CNTK-TechReport/figures/CNTKArch.pdf            | Bin
 .../CNTK-TechReport/figures/CNTKArch.png            | Bin
 .../CNTK-TechReport/figures/ConfusionData1.png      | Bin
 .../CNTK-TechReport/figures/ConfusionData100.png    | Bin
 .../CNTK-TechReport/figures/SequenceBatch.pdf       | Bin
 .../CNTK-TechReport/figures/SequenceBatch.png       | Bin
 .../figures/SimpleDemoDataReference.png             | Bin
 .../figures/SimpleDemoErrorRateReference.png        | Bin
 .../figures/SimpleDemoOutputReference.png           | Bin
 .../CNTK-TechReport/figures/SpeechErrorRate.png     | Bin
 .../CNTK-TechReport/figures/simpleRNN.png           | Bin
 .../lyx/#CNTKBook_CNTK_Programmer_Chapter.lyx#      |   0
 .../CNTK-TechReport/lyx/CNTKBook-20150513.pdf       |   0
 .../CNTK-TechReport/lyx/CNTKBook-master.lyx         |   0
 .../lyx/CNTKBook_ASRDecoder_Chapter.lyx             |   0
 .../CNTK-TechReport/lyx/CNTKBook_Abstract.lyx       |   0
 .../lyx/CNTKBook_CNTK_Adv_Chapter.lyx               |   0
 .../CNTK-TechReport/lyx/CNTKBook_CNTK_Chapter.lyx   |   0
 .../lyx/CNTKBook_CNTK_Programmer_Chapter.lyx        |   0
 .../CNTK-TechReport/lyx/CNTKBook_CN_Chapter.lyx     |   0
 .../lyx/CNTKBook_ExampleSetup_Chapter.lyx           |   0
 .../CNTK-TechReport/lyx/CNTKBook_Introduction.lyx   |   0
 .../CNTK-TechReport/lyx/references.bib              |   0
 .../CNTK-Tutorial-ICASSP2015.pdf                    | Bin
 41 files changed, 0 insertions(+), 0 deletions(-)
 rename {papers => Documentation}/CNTK-TechReport/figures.vsdm (100%)
 rename {papers => Documentation}/CNTK-TechReport/figures/CN+TrainingCriterion.pdf (100%)
 rename {papers => Documentation}/CNTK-TechReport/figures/CN+TrainingCriterion.png (100%)
 rename {papers => Documentation}/CNTK-TechReport/figures/CN-1HiddenNN.pdf (100%)
 rename {papers => Documentation}/CNTK-TechReport/figures/CN-1HiddenNN.png (100%)
 rename {papers => Documentation}/CNTK-TechReport/figures/CN-2Inputs.pdf (100%)
 rename {papers => Documentation}/CNTK-TechReport/figures/CN-2Inputs.png (100%)
 rename {papers => Documentation}/CNTK-TechReport/figures/CN-EfficientGradient.pdf (100%)
 rename {papers => Documentation}/CNTK-TechReport/figures/CN-EfficientGradient.png (100%)
 rename {papers => Documentation}/CNTK-TechReport/figures/CN-NaiveGradient.pdf (100%)
 rename {papers => Documentation}/CNTK-TechReport/figures/CN-NaiveGradient.png (100%)
 rename {papers => Documentation}/CNTK-TechReport/figures/CN-ShareWeight.pdf (100%)
 rename {papers => Documentation}/CNTK-TechReport/figures/CN-ShareWeight.png (100%)
 rename {papers => Documentation}/CNTK-TechReport/figures/CN-WithDelayNode.pdf (100%)
 rename {papers => Documentation}/CNTK-TechReport/figures/CN-WithDelayNode.png (100%)
 rename {papers => Documentation}/CNTK-TechReport/figures/CNNComputation.pdf (100%)
 rename {papers => Documentation}/CNTK-TechReport/figures/CNNComputation.png (100%)
 rename {papers => Documentation}/CNTK-TechReport/figures/CNTKArch.pdf (100%)
 rename {papers => Documentation}/CNTK-TechReport/figures/CNTKArch.png (100%)
 rename {papers => Documentation}/CNTK-TechReport/figures/ConfusionData1.png (100%)
 rename {papers => Documentation}/CNTK-TechReport/figures/ConfusionData100.png (100%)
 rename {papers => Documentation}/CNTK-TechReport/figures/SequenceBatch.pdf (100%)
 rename {papers => Documentation}/CNTK-TechReport/figures/SequenceBatch.png (100%)
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 rename {papers => Documentation}/CNTK-TechReport/lyx/#CNTKBook_CNTK_Programmer_Chapter.lyx# (100%)
 rename {papers => Documentation}/CNTK-TechReport/lyx/CNTKBook-20150513.pdf (100%)
 rename {papers => Documentation}/CNTK-TechReport/lyx/CNTKBook-master.lyx (100%)
 rename {papers => Documentation}/CNTK-TechReport/lyx/CNTKBook_ASRDecoder_Chapter.lyx (100%)
 rename {papers => Documentation}/CNTK-TechReport/lyx/CNTKBook_Abstract.lyx (100%)
 rename {papers => Documentation}/CNTK-TechReport/lyx/CNTKBook_CNTK_Adv_Chapter.lyx (100%)
 rename {papers => Documentation}/CNTK-TechReport/lyx/CNTKBook_CNTK_Chapter.lyx (100%)
 rename {papers => Documentation}/CNTK-TechReport/lyx/CNTKBook_CNTK_Programmer_Chapter.lyx (100%)
 rename {papers => Documentation}/CNTK-TechReport/lyx/CNTKBook_CN_Chapter.lyx (100%)
 rename {papers => Documentation}/CNTK-TechReport/lyx/CNTKBook_ExampleSetup_Chapter.lyx (100%)
 rename {papers => Documentation}/CNTK-TechReport/lyx/CNTKBook_Introduction.lyx (100%)
 rename {papers => Documentation}/CNTK-TechReport/lyx/references.bib (100%)
 rename {papers => Documentation}/CNTK-Tutorial-ICASSP2015.pdf (100%)

diff --git a/papers/CNTK-TechReport/figures.vsdm b/Documentation/CNTK-TechReport/figures.vsdm
similarity index 100%
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rename to Documentation/CNTK-TechReport/figures.vsdm
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diff --git a/papers/CNTK-TechReport/lyx/#CNTKBook_CNTK_Programmer_Chapter.lyx# b/Documentation/CNTK-TechReport/lyx/#CNTKBook_CNTK_Programmer_Chapter.lyx#
similarity index 100%
rename from papers/CNTK-TechReport/lyx/#CNTKBook_CNTK_Programmer_Chapter.lyx#
rename to Documentation/CNTK-TechReport/lyx/#CNTKBook_CNTK_Programmer_Chapter.lyx#
diff --git a/papers/CNTK-TechReport/lyx/CNTKBook-20150513.pdf b/Documentation/CNTK-TechReport/lyx/CNTKBook-20150513.pdf
similarity index 100%
rename from papers/CNTK-TechReport/lyx/CNTKBook-20150513.pdf
rename to Documentation/CNTK-TechReport/lyx/CNTKBook-20150513.pdf
diff --git a/papers/CNTK-TechReport/lyx/CNTKBook-master.lyx b/Documentation/CNTK-TechReport/lyx/CNTKBook-master.lyx
similarity index 100%
rename from papers/CNTK-TechReport/lyx/CNTKBook-master.lyx
rename to Documentation/CNTK-TechReport/lyx/CNTKBook-master.lyx
diff --git a/papers/CNTK-TechReport/lyx/CNTKBook_ASRDecoder_Chapter.lyx b/Documentation/CNTK-TechReport/lyx/CNTKBook_ASRDecoder_Chapter.lyx
similarity index 100%
rename from papers/CNTK-TechReport/lyx/CNTKBook_ASRDecoder_Chapter.lyx
rename to Documentation/CNTK-TechReport/lyx/CNTKBook_ASRDecoder_Chapter.lyx
diff --git a/papers/CNTK-TechReport/lyx/CNTKBook_Abstract.lyx b/Documentation/CNTK-TechReport/lyx/CNTKBook_Abstract.lyx
similarity index 100%
rename from papers/CNTK-TechReport/lyx/CNTKBook_Abstract.lyx
rename to Documentation/CNTK-TechReport/lyx/CNTKBook_Abstract.lyx
diff --git a/papers/CNTK-TechReport/lyx/CNTKBook_CNTK_Adv_Chapter.lyx b/Documentation/CNTK-TechReport/lyx/CNTKBook_CNTK_Adv_Chapter.lyx
similarity index 100%
rename from papers/CNTK-TechReport/lyx/CNTKBook_CNTK_Adv_Chapter.lyx
rename to Documentation/CNTK-TechReport/lyx/CNTKBook_CNTK_Adv_Chapter.lyx
diff --git a/papers/CNTK-TechReport/lyx/CNTKBook_CNTK_Chapter.lyx b/Documentation/CNTK-TechReport/lyx/CNTKBook_CNTK_Chapter.lyx
similarity index 100%
rename from papers/CNTK-TechReport/lyx/CNTKBook_CNTK_Chapter.lyx
rename to Documentation/CNTK-TechReport/lyx/CNTKBook_CNTK_Chapter.lyx
diff --git a/papers/CNTK-TechReport/lyx/CNTKBook_CNTK_Programmer_Chapter.lyx b/Documentation/CNTK-TechReport/lyx/CNTKBook_CNTK_Programmer_Chapter.lyx
similarity index 100%
rename from papers/CNTK-TechReport/lyx/CNTKBook_CNTK_Programmer_Chapter.lyx
rename to Documentation/CNTK-TechReport/lyx/CNTKBook_CNTK_Programmer_Chapter.lyx
diff --git a/papers/CNTK-TechReport/lyx/CNTKBook_CN_Chapter.lyx b/Documentation/CNTK-TechReport/lyx/CNTKBook_CN_Chapter.lyx
similarity index 100%
rename from papers/CNTK-TechReport/lyx/CNTKBook_CN_Chapter.lyx
rename to Documentation/CNTK-TechReport/lyx/CNTKBook_CN_Chapter.lyx
diff --git a/papers/CNTK-TechReport/lyx/CNTKBook_ExampleSetup_Chapter.lyx b/Documentation/CNTK-TechReport/lyx/CNTKBook_ExampleSetup_Chapter.lyx
similarity index 100%
rename from papers/CNTK-TechReport/lyx/CNTKBook_ExampleSetup_Chapter.lyx
rename to Documentation/CNTK-TechReport/lyx/CNTKBook_ExampleSetup_Chapter.lyx
diff --git a/papers/CNTK-TechReport/lyx/CNTKBook_Introduction.lyx b/Documentation/CNTK-TechReport/lyx/CNTKBook_Introduction.lyx
similarity index 100%
rename from papers/CNTK-TechReport/lyx/CNTKBook_Introduction.lyx
rename to Documentation/CNTK-TechReport/lyx/CNTKBook_Introduction.lyx
diff --git a/papers/CNTK-TechReport/lyx/references.bib b/Documentation/CNTK-TechReport/lyx/references.bib
similarity index 100%
rename from papers/CNTK-TechReport/lyx/references.bib
rename to Documentation/CNTK-TechReport/lyx/references.bib
diff --git a/papers/CNTK-Tutorial-ICASSP2015.pdf b/Documentation/CNTK-Tutorial-ICASSP2015.pdf
similarity index 100%
rename from papers/CNTK-Tutorial-ICASSP2015.pdf
rename to Documentation/CNTK-Tutorial-ICASSP2015.pdf

From 0462453a1bc07c4e2bbe7b926d6a769d7a3c9676 Mon Sep 17 00:00:00 2001
From: Yinggong ZHAO <yinggong.zhao@gmail.com>
Date: Sat, 16 May 2015 22:07:38 +0800
Subject: [PATCH 20/49] 	modified:   SequenceReader.h

---
 DataReader/LMSequenceReader/SequenceReader.h | 48 +++++++++++++++++++-
 1 file changed, 47 insertions(+), 1 deletion(-)

diff --git a/DataReader/LMSequenceReader/SequenceReader.h b/DataReader/LMSequenceReader/SequenceReader.h
index 244174a98..83dd08d55 100644
--- a/DataReader/LMSequenceReader/SequenceReader.h
+++ b/DataReader/LMSequenceReader/SequenceReader.h
@@ -14,7 +14,7 @@
 #include <map>
 #include <vector>
 #include "minibatchsourcehelpers.h"
-
+#include <random>
 
 namespace Microsoft { namespace MSR { namespace CNTK {
 
@@ -33,6 +33,52 @@ enum LabelKind
     labelOther = 3, // some other type of label
 };
 
+template <typename Count>
+class noiseSampler {
+    std::vector<double> m_prob, m_log_prob;
+    std::uniform_int_distribution<Count> unif_int;
+    bool uniform_sampling;
+    double uniform_prob;
+    double uniform_log_prob;
+    std::piecewise_constant_distribution<double> d;
+    std::mt19937 rng;
+public:
+    noiseSampler(){ }
+    noiseSampler(const std::vector<double> &counts, bool xuniform_sampling = false)
+        :uniform_sampling(xuniform_sampling), rng(time(0))
+    {
+        int k = counts.size();
+        uniform_prob = 1.0 / k;
+        uniform_log_prob = std::log(uniform_prob);
+        std::vector<double> vn(counts.size() + 1);
+        for (int i = 0; i < vn.size(); i++)
+            vn[i] = i;
+        d = std::piecewise_constant_distribution<double>(vn.begin(), vn.end(), counts.begin());
+        unif_int = std::uniform_int_distribution<Count>(0, counts.size() - 1);
+        m_prob = d.densities();
+        m_log_prob.resize(m_prob.size());
+        for (int i = 0; i < k; i++)
+            m_log_prob[i] = std::log(m_prob[i]);
+    }
+    int size() const{ return m_prob.size(); }
+    double prob(int i) const { if (uniform_sampling) return uniform_prob; else return m_prob[i]; }
+    double logprob(int i) const { if (uniform_sampling) return uniform_log_prob; else return m_log_prob[i]; }
+
+    template <typename Engine>
+    int sample(Engine &eng) const
+    {
+        int m = unif_int(eng);
+        if (uniform_sampling)
+            return m;
+        return d(eng);
+    }
+    
+    int sample()
+    {
+        return sample(this->rng);
+    }
+};
+
 template<class ElemType>
 class SequenceReader : public IDataReader<ElemType>
 {

From dad030381eab76a02f12a995c7acc11f5f78be31 Mon Sep 17 00:00:00 2001
From: unknown <v-yinggz@suzgpu-01.fareast.corp.microsoft.com>
Date: Mon, 18 May 2015 00:46:27 -0700
Subject: [PATCH 21/49] 	modified:   SequenceReader.cpp 	modified:  
 SequenceReader.h

---
 .../LMSequenceReader/SequenceReader.cpp       | 145 +++++++++++++-----
 DataReader/LMSequenceReader/SequenceReader.h  |  28 +++-
 ExampleSetups/LM/LSTMLM/global.config         |   6 +-
 3 files changed, 132 insertions(+), 47 deletions(-)

diff --git a/DataReader/LMSequenceReader/SequenceReader.cpp b/DataReader/LMSequenceReader/SequenceReader.cpp
index 256b6584a..7fdda1cd5 100644
--- a/DataReader/LMSequenceReader/SequenceReader.cpp
+++ b/DataReader/LMSequenceReader/SequenceReader.cpp
@@ -646,6 +646,11 @@ void SequenceReader<ElemType>::ReadClassInfo(const wstring & vocfile, bool /*fla
     }
     fin.close();
     class_size++;
+ 
+    std::vector<double> counts(idx4cnt.size());
+    for (auto p : idx4cnt)
+        counts[p.first] = (double)p.second;
+    m = noiseSampler<long>(counts);
 }
 
 // InitCache - Initialize the caching reader if cache files exist, otherwise the writer
@@ -983,29 +988,68 @@ void SequenceReader<ElemType>::GetLabelOutput(std::map<std::wstring, Matrix<Elem
     Matrix<ElemType>* labels = matrices[m_labelsName[labelInfoOut]];
     if (labels == nullptr) return;
     
-    labels->Resize(4, actualmbsize);
+    if (readerMode == ReaderMode::NCE)
+        labels->Resize(2 * (this->noise_sample_size + 1), actualmbsize);
+    else if (readerMode == ReaderMode::Class)
+        labels->Resize(4, actualmbsize);
+    else if (readerMode == ReaderMode::Softmax)
+        labels->Resize(1, actualmbsize);
         
     for (size_t jSample = m_mbStartSample; j < actualmbsize; ++j, ++jSample)
     {
         // pick the right sample with randomization if desired
-        size_t jRand = jSample;
-         
-        int    wrd = m_labelIdData[jRand];
-        int    clsidx = idx4class[wrd]; 
-        
+        size_t jRand = jSample;         
+        int    wrd = m_labelIdData[jRand];        
         labels->SetValue(0, j, (ElemType)wrd); 
 
-        if (class_size > 0){
-            labels->SetValue(1, j, (ElemType)clsidx);
-            
-            /// save the [begining ending_indx) of the class 
-            labels->SetValue(2, j, (*m_classInfoLocal)(0, clsidx)); /// begining index of the class
-            labels->SetValue(3, j, (*m_classInfoLocal)(1, clsidx)); /// end index of the class
+        if (readerMode == ReaderMode::NCE)
+        {
+            labels->SetValue(1, j, (ElemType)m.logprob(wrd));
+            for (size_t noiseid = 0; noiseid < this->noise_sample_size; noiseid++)
+            {
+                int wid = m.sample();
+                labels->SetValue(2 * (noiseid + 1), j, (ElemType)wid);
+                labels->SetValue(2 * (noiseid + 1) + 1, j, -(ElemType)m.logprob(wid));
+            }
+        }
+        else if (readerMode == ReaderMode::Class)
+        {
+            int clsidx = idx4class[wrd];
+            if (class_size > 0){
+                labels->SetValue(1, j, (ElemType)clsidx);
+                /// save the [begining ending_indx) of the class 
+                labels->SetValue(2, j, (*m_classInfoLocal)(0, clsidx)); /// begining index of the class
+                labels->SetValue(3, j, (*m_classInfoLocal)(1, clsidx)); /// end index of the class
+            }
         }
     }
-
 }
+template<class ElemType>
+void SequenceReader<ElemType>::GetInputProb(std::map<std::wstring, Matrix<ElemType>*>& matrices)
+{
+    Matrix<ElemType>* idx2prob = matrices[STRIDX2PROB];
+    if (idx2prob == nullptr) return;
 
+    if (m_idx2probRead) return;
+
+    // populate local CPU matrix
+    m_id2Prob->SwitchToMatrixType(MatrixType::DENSE, matrixFormatDense, false);
+    m_id2Prob->Resize(nwords, 1, false);
+
+    //move to CPU since element-wise operation is expensive and can go wrong in GPU
+    int curDevId = m_id2Prob->GetDeviceId();
+    m_id2Prob->TransferFromDeviceToDevice(curDevId, CPUDEVICE, true, false, false);
+    for (size_t j = 0; j < nwords; j++)
+        (*m_id2Prob)((int)j, 0) = (float)m.prob((int)j);
+    m_id2Prob->TransferFromDeviceToDevice(CPUDEVICE, curDevId, true, false, false);
+
+    int oldDeviceId = idx2prob->GetDeviceId();
+    // caution, SetValue changes idx2cls from GPU to CPU, may change this behavior later
+    idx2prob->SetValue(*m_id2Prob);
+    idx2prob->TransferFromDeviceToDevice(idx2prob->GetDeviceId(), oldDeviceId, true);
+
+    m_idx2probRead = true;
+}
 template<class ElemType>
 void SequenceReader<ElemType>::GetInputToClass(std::map<std::wstring, Matrix<ElemType>*>& matrices)
 {
@@ -1342,6 +1386,18 @@ void BatchSequenceReader<ElemType>::Init(const ConfigParameters& readerConfig)
 
     ConfigParameters featureConfig = readerConfig(m_featuresName,"");
     ConfigParameters labelConfig[2] = {readerConfig(m_labelsName[0],""),readerConfig(m_labelsName[1],"")};
+    string mode = featureConfig("mode","class");//class, softmax, nce
+
+    if (mode == "nce")
+    {
+        readerMode = ReaderMode::NCE;
+    
+        this->noise_sample_size = featureConfig("noise_number", "0");
+    }
+    else if (mode == "softmax")
+        readerMode = ReaderMode::Softmax;
+    else if (mode == "class")
+        readerMode = ReaderMode::Class;
 
     class_size = 0;
     m_featureDim = featureConfig("dim");
@@ -1804,8 +1860,11 @@ bool BatchSequenceReader<ElemType>::GetMinibatch(std::map<std::wstring, Matrix<E
         features.TransferFromDeviceToDevice(CPUDEVICE, featureDeviceId, false,false, false);
                 
         // TODO: move these two methods to startMiniBatchLoop()
-        GetInputToClass(matrices);
-        GetClassInfo();
+        if (readerMode == ReaderMode::Class)
+        {
+            GetInputToClass(matrices);
+            GetClassInfo();
+        }
         GetLabelOutput(matrices, 0, actualmbsize);
 
         // go to the next sequence
@@ -1919,43 +1978,51 @@ bool BatchSequenceReader<ElemType>::DataEnd(EndDataType endDataType)
 /// notice that indices are defined as follows [begining ending_indx) of the class 
 /// i.e., the ending_index is 1 plus of the true ending index
 template<class ElemType>
-void BatchSequenceReader<ElemType>::GetLabelOutput(std::map<std::wstring, 
-    Matrix<ElemType>*>& matrices, 
+void BatchSequenceReader<ElemType>::GetLabelOutput(std::map<std::wstring,
+    Matrix<ElemType>*>& matrices,
     size_t m_mbStartSample, size_t actualmbsize)
 {
     size_t j = 0;
-    Matrix<ElemType>* labels = matrices[m_labelsName[labelInfoOut]]; 
+    Matrix<ElemType>* labels = matrices[m_labelsName[labelInfoOut]];
     if (labels == nullptr) return;
-    
-    if(labels->GetMatrixType() == MatrixType::DENSE) 
-    {
+
+    if (readerMode == ReaderMode::NCE)
+        labels->Resize(2 * (this->noise_sample_size + 1), actualmbsize);
+    else if (readerMode == ReaderMode::Class)
         labels->Resize(4, actualmbsize, false);
-    }
-    else 
-    {
-        RuntimeError("GetLabelOutput::should use dense matrix for labels which only save index of words"); 
-    }
+    else
+        labels->Resize(1, actualmbsize, false);
+
 
     //move to CPU since element-wise operation is expensive and can go wrong in GPU
     int curDevId = labels->GetDeviceId();
     labels->TransferFromDeviceToDevice(curDevId, CPUDEVICE, true, false, false);
 
 
-    if(labels->GetCurrentMatrixLocation() == CPU) {
-        for (size_t jSample = m_mbStartSample; j < actualmbsize; ++j, ++jSample)
+    if (labels->GetCurrentMatrixLocation() == CPU)
+    for (size_t jSample = m_mbStartSample; j < actualmbsize; ++j, ++jSample)
+    {
+        // pick the right sample with randomization if desired
+        size_t jRand = jSample;
+        int    wrd = m_labelIdData[jRand];
+        labels->SetValue(0, j, (ElemType)wrd);
+        SetSentenceEnd(wrd, j, actualmbsize);
+
+        if (readerMode == ReaderMode::NCE)
         {
-            // pick the right sample with randomization if desired
-            size_t jRand = jSample;
-
-            int    wrd = m_labelIdData[jRand];
-            int    clsidx = idx4class[wrd]; 
-
-            labels->SetValue(0, j, (ElemType)wrd); 
-
-            SetSentenceEnd(wrd, j, actualmbsize);
-
-            if (class_size > 0)
+            labels->SetValue(1, j, (ElemType)m.logprob(wrd));
+            for (size_t noiseid = 0; noiseid < this->noise_sample_size; noiseid++)
             {
+                int wid = m.sample();
+                labels->SetValue(2 * (noiseid + 1), j, (ElemType)wid);
+                labels->SetValue(2 * (noiseid + 1) + 1, j, -(ElemType)m.logprob(wid));
+            }
+        }
+        else if (readerMode == ReaderMode::Class)
+        {
+            int clsidx = idx4class[wrd];
+            if (class_size > 0){
+
                 labels->SetValue(1, j, (ElemType)clsidx);
 
                 /// save the [begining ending_indx) of the class 
diff --git a/DataReader/LMSequenceReader/SequenceReader.h b/DataReader/LMSequenceReader/SequenceReader.h
index 83dd08d55..292af20ab 100644
--- a/DataReader/LMSequenceReader/SequenceReader.h
+++ b/DataReader/LMSequenceReader/SequenceReader.h
@@ -22,7 +22,8 @@ namespace Microsoft { namespace MSR { namespace CNTK {
 
 #define STRIDX2CLS L"idx2cls"
 #define CLASSINFO  L"classinfo"
-    
+
+#define STRIDX2PROB L"idx2prob"
 #define MAX_STRING  2048
 
 enum LabelKind
@@ -32,6 +33,14 @@ enum LabelKind
     labelNextWord = 2,  // sentence mapping (predicts next word)
     labelOther = 3, // some other type of label
 };
+            
+enum ReaderMode
+{
+    Softmax = 0,  // no labels to worry about
+    Class = 1, // category labels, creates mapping tables
+    NCE = 2,  // sentence mapping (predicts next word)
+    None = 3, // some other type of label
+};
 
 template <typename Count>
 class noiseSampler {
@@ -45,16 +54,16 @@ class noiseSampler {
 public:
     noiseSampler(){ }
     noiseSampler(const std::vector<double> &counts, bool xuniform_sampling = false)
-        :uniform_sampling(xuniform_sampling), rng(time(0))
+        :uniform_sampling(xuniform_sampling), rng((int)time(0))
     {
-        int k = counts.size();
+        size_t k = counts.size();
         uniform_prob = 1.0 / k;
         uniform_log_prob = std::log(uniform_prob);
         std::vector<double> vn(counts.size() + 1);
         for (int i = 0; i < vn.size(); i++)
             vn[i] = i;
         d = std::piecewise_constant_distribution<double>(vn.begin(), vn.end(), counts.begin());
-        unif_int = std::uniform_int_distribution<Count>(0, counts.size() - 1);
+        unif_int = std::uniform_int_distribution<Count>(0,(long) counts.size() - 1);
         m_prob = d.densities();
         m_log_prob.resize(m_prob.size());
         for (int i = 0; i < k; i++)
@@ -70,7 +79,7 @@ public:
         int m = unif_int(eng);
         if (uniform_sampling)
             return m;
-        return d(eng);
+        return (int)d(eng);
     }
     
     int sample()
@@ -86,6 +95,7 @@ protected:
     bool   m_idx2clsRead; 
     bool   m_clsinfoRead;
 
+    bool   m_idx2probRead;
     std::wstring m_file; 
 public:
 	using LabelType = typename IDataReader<ElemType>::LabelType;
@@ -98,10 +108,15 @@ public:
     Matrix<ElemType>* m_id2classLocal; // CPU version
     Matrix<ElemType>* m_classInfoLocal; // CPU version
 
+    Matrix<ElemType>* m_id2Prob; // CPU version
     int class_size;
     map<int, vector<int>> class_words;
     vector<int>class_cn;
 
+    int noise_sample_size;
+    noiseSampler<long> m;
+
+    ReaderMode readerMode;
     int eos_idx, unk_idx;
 public:
 //    typedef std::string LabelType;
@@ -204,12 +219,15 @@ public:
     void GetLabelOutput(std::map<std::wstring, Matrix<ElemType>*>& matrices, 
                        size_t m_mbStartSample, size_t actualmbsize);
     void GetInputToClass(std::map<std::wstring, Matrix<ElemType>*>& matrices);
+
+    void GetInputProb(std::map<std::wstring, Matrix<ElemType>*>& matrices);
     void GetClassInfo();
 
     virtual void Destroy();
     SequenceReader() {
         m_featuresBuffer=NULL; m_labelsBuffer=NULL; m_clsinfoRead = false; m_idx2clsRead = false;             
         m_cachingReader=NULL; m_cachingWriter=NULL; m_labelsIdBuffer = NULL;
+        readerMode = ReaderMode::Class;
 		/*
         delete m_featuresBufferRow;
         delete m_featuresBufferRowIdx;
diff --git a/ExampleSetups/LM/LSTMLM/global.config b/ExampleSetups/LM/LSTMLM/global.config
index 700d9f846..c5073e768 100644
--- a/ExampleSetups/LM/LSTMLM/global.config
+++ b/ExampleSetups/LM/LSTMLM/global.config
@@ -1,3 +1,3 @@
-ExpDir=\\speechstore5\transient\kaishengy\exp\lm\fnnlm
-ConfigDir=\\speechstore5\userdata\kaishengy\exp\lm\setup
-DataDir=\\speechstore5\transient\kaishengy\data\LM\PennTreeBank
+ExpDir=D:\zhaoyg\2015-5-6\cntk\ExampleSetups\LM\LSTMLM\
+ConfigDir=D:\zhaoyg\2015-5-6\cntk\ExampleSetups\LM\LSTMLM\
+DataDir=D:\zhaoyg\2015-5-6\cntk\ExampleSetups\LM\LSTMLM\

From 0bc4a2838a709be11ba9281c98320cf9874e36b9 Mon Sep 17 00:00:00 2001
From: Dong Yu <dongyu@microsoft.com>
Date: Mon, 18 May 2015 00:55:44 -0700
Subject: [PATCH 22/49] update NDLExamples.ndl

---
 ExampleSetups/NDLExamples.ndl | 10 +++++++---
 1 file changed, 7 insertions(+), 3 deletions(-)

diff --git a/ExampleSetups/NDLExamples.ndl b/ExampleSetups/NDLExamples.ndl
index 1558f9246..d4d2091fc 100644
--- a/ExampleSetups/NDLExamples.ndl
+++ b/ExampleSetups/NDLExamples.ndl
@@ -84,14 +84,18 @@ ndlTestMDN=[
     GMMComponent=4
     SizeOfAllMeans=40
     
-    UnnormedPrior =  BFF(L3, GMMComponent, HDim)
+    UnnormedPrior0 =  BFF(L3, GMMComponent, HDim)
+    UnnormedPrior1=Tanh(UnnormedPrior0)
+    scaleFPrior=Const(2)   
+    UnnormedPrior=Scale(scaleFPrior, UnnormedPrior1)
+    
     Means=BFF(L3, SizeOfAllMeans, HDim)
     
     #it's important to control the range of logstddev
     LogStddev0=BFF(L3, GMMComponent, MDim)
     LogStddev1=Tanh(LogStddev0)
-    scaleF=Const(2)    
-    LogStddev=Scale(scaleF, LogStddev1)    
+    scaleFStddev=Const(2)    
+    LogStddev=Scale(scaleFStddev, LogStddev1)    
     
     LL=GMMLL(UnnormedPrior, Means, LogStddev, labels)
     LLAll=SumElements(LL)

From 86e79fb7c62f0e1dac93f017d5ceab57f123e889 Mon Sep 17 00:00:00 2001
From: Dong Yu <dongyu@microsoft.com>
Date: Mon, 18 May 2015 02:00:50 -0700
Subject: [PATCH 23/49] fix the "not used" warning in
 GPUMatrix<ElemType>::RCRFBackwardCompute

---
 Math/Math/GPUMatrix.cu | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/Math/Math/GPUMatrix.cu b/Math/Math/GPUMatrix.cu
index a19759314..2bca8cadd 100644
--- a/Math/Math/GPUMatrix.cu
+++ b/Math/Math/GPUMatrix.cu
@@ -3757,7 +3757,7 @@ namespace Microsoft { namespace MSR { namespace CNTK {
     template<class ElemType>
     void GPUMatrix<ElemType>::RCRFBackwardCompute(
         const GPUMatrix<ElemType>& alpha, GPUMatrix<ElemType>& beta,
-        const GPUMatrix<ElemType>& lbls,
+        const GPUMatrix<ElemType>& /*lbls*/,
         const GPUMatrix<ElemType>& pos_scores, const GPUMatrix<ElemType>& pair_scores, const int shift)
     {
         if (alpha.IsEmpty() || pos_scores.IsEmpty() || pair_scores.IsEmpty())

From 3dbed2fc893bd9f56e8361bafdfecf0194be6d00 Mon Sep 17 00:00:00 2001
From: Yinggong ZHAO <yinggong.zhao@gmail.com>
Date: Mon, 18 May 2015 05:18:00 -0700
Subject: [PATCH 24/49] use default seed for sampler

---
 DataReader/LMSequenceReader/SequenceReader.h |   2 +-
 MachineLearning/cn/ComputationNetwork.h      |  13 +-
 MachineLearning/cn/SimpleEvaluator.h         |   3 +-
 MachineLearning/cn/SimpleNetworkBuilder.cpp  | 115 ++++
 MachineLearning/cn/SimpleNetworkBuilder.h    |  28 +-
 MachineLearning/cn/TrainingCriterionNode.h   | 213 ++++++++
 MachineLearning/cn/cn.cpp                    |   4 +
 Math/Math/CPUMatrix.cpp                      | 131 ++++-
 Math/Math/CPUMatrix.h                        |   7 +
 Math/Math/GPUMatrix.cu                       | 112 +++-
 Math/Math/GPUMatrix.h                        |   6 +
 Math/Math/GPUMatrixCUDAKernels.cu            | 544 +++++++++++++++++++
 Math/Math/Matrix.cpp                         |  64 +++
 Math/Math/Matrix.h                           |   5 +
 Math/Math/NoGPU.cpp                          |  17 +
 15 files changed, 1254 insertions(+), 10 deletions(-)

diff --git a/DataReader/LMSequenceReader/SequenceReader.h b/DataReader/LMSequenceReader/SequenceReader.h
index 292af20ab..1d8518bf2 100644
--- a/DataReader/LMSequenceReader/SequenceReader.h
+++ b/DataReader/LMSequenceReader/SequenceReader.h
@@ -54,7 +54,7 @@ class noiseSampler {
 public:
     noiseSampler(){ }
     noiseSampler(const std::vector<double> &counts, bool xuniform_sampling = false)
-        :uniform_sampling(xuniform_sampling), rng((int)time(0))
+        :uniform_sampling(xuniform_sampling), rng(1234)
     {
         size_t k = counts.size();
         uniform_prob = 1.0 / k;
diff --git a/MachineLearning/cn/ComputationNetwork.h b/MachineLearning/cn/ComputationNetwork.h
index fc2851789..e99983612 100644
--- a/MachineLearning/cn/ComputationNetwork.h
+++ b/MachineLearning/cn/ComputationNetwork.h
@@ -985,7 +985,9 @@ public:
             else if (nodeType == CrossEntropyWithSoftmaxNode<ElemType>::TypeName())
                 newNode = new CrossEntropyWithSoftmaxNode<ElemType>(fstream, modelVersion, m_deviceId, nodeName);
             else if (nodeType == ClassBasedCrossEntropyWithSoftmaxNode<ElemType>::TypeName())
-                newNode = new ClassBasedCrossEntropyWithSoftmaxNode<ElemType>(fstream, modelVersion, m_deviceId, nodeName);
+                newNode = new ClassBasedCrossEntropyWithSoftmaxNode<ElemType>(fstream, modelVersion, m_deviceId, nodeName); 
+            else if (nodeType == NoiseContrastiveEstimationNode<ElemType>::TypeName())
+                newNode = new NoiseContrastiveEstimationNode<ElemType>(fstream, modelVersion, m_deviceId, nodeName);
             else if (nodeType == CRFNode<ElemType>::TypeName())
                 newNode = new CRFNode<ElemType>(fstream, modelVersion, m_deviceId, nodeName);
             else if (nodeType == CrossEntropyNode<ElemType>::TypeName())
@@ -1282,6 +1284,15 @@ public:
             return newNode;
         }
 
+        ComputationNodePtr NoiseContrastiveEstimation(const ComputationNodePtr label, const ComputationNodePtr prediction,
+            const ComputationNodePtr input_weight, const ComputationNodePtr input_bias, const std::wstring nodeName = L"", NCEEvalMode mode = NCEEvalMode::None)
+        {
+            ComputationNodePtr newNode(new NoiseContrastiveEstimationNode<ElemType>(m_deviceId, nodeName, mode));
+            newNode->AttachInputs(label, prediction, input_weight, input_bias);
+            AddNodeToNet(newNode);
+            return newNode;
+        }
+
         ComputationNodePtr ClassCrossEntropyWithSoftmax(const ComputationNodePtr label, const ComputationNodePtr prediction,
             const ComputationNodePtr input_weight, const ComputationNodePtr cls_log_post_prob, const std::wstring nodeName = L"")
         {
diff --git a/MachineLearning/cn/SimpleEvaluator.h b/MachineLearning/cn/SimpleEvaluator.h
index 0b6834b2f..f31801087 100644
--- a/MachineLearning/cn/SimpleEvaluator.h
+++ b/MachineLearning/cn/SimpleEvaluator.h
@@ -315,7 +315,8 @@ namespace Microsoft { namespace MSR { namespace CNTK {
                     //display Perplexity as well for crossEntropy values
                     if (evalNodes[i]->OperationName() == CrossEntropyWithSoftmaxNode<ElemType>::TypeName() ||
                         evalNodes[i]->OperationName() == CrossEntropyNode<ElemType>::TypeName() ||
-                        evalNodes[i]->OperationName() == ClassBasedCrossEntropyWithSoftmaxNode<ElemType>::TypeName())
+                        evalNodes[i]->OperationName() == ClassBasedCrossEntropyWithSoftmaxNode<ElemType>::TypeName() ||
+                        evalNodes[i]->OperationName() == NoiseContrastiveEstimationNode<ElemType>::TypeName())
                         fprintf(stderr, "Perplexity = %.8g    ", std::exp(eresult));
                 }
             }
diff --git a/MachineLearning/cn/SimpleNetworkBuilder.cpp b/MachineLearning/cn/SimpleNetworkBuilder.cpp
index bf7344776..85a68b3b2 100644
--- a/MachineLearning/cn/SimpleNetworkBuilder.cpp
+++ b/MachineLearning/cn/SimpleNetworkBuilder.cpp
@@ -1176,6 +1176,121 @@ namespace Microsoft { namespace MSR { namespace CNTK {
 
             return *m_net;
     }
+    template<class ElemType>
+    ComputationNetwork<ElemType>& SimpleNetworkBuilder<ElemType>::BuildNCELSTMNetworkFromDescription(size_t mbSize)
+    {
+        if (m_net->GetTotalNumberOfNodes() < 1) //not built yet
+        {
+            unsigned long randomSeed = 1;
+
+            size_t numHiddenLayers = m_layerSizes.size() - 2;
+            size_t numRecurrentLayers = m_recurrentLayers.size();
+
+            ComputationNodePtr input = nullptr, w = nullptr, b = nullptr, u = nullptr, e = nullptr, delay = nullptr, output = nullptr, label = nullptr, prior = nullptr;
+            ComputationNodePtr Wxo = nullptr, Who = nullptr, Wco = nullptr, bo = nullptr, Wxi = nullptr, Whi = nullptr, Wci = nullptr, bi = nullptr;
+            ComputationNodePtr clslogpostprob = nullptr;
+            ComputationNodePtr bias = nullptr;
+            ComputationNodePtr outputFromEachLayer[MAX_DEPTH] = { nullptr };
+
+            input = m_net->CreateSparseInputNode(L"features", m_layerSizes[0], mbSize);
+            m_net->FeatureNodes().push_back(input);
+
+            if (m_applyMeanVarNorm)
+            {
+                w = m_net->Mean(input);
+                b = m_net->InvStdDev(input);
+                output = m_net->PerDimMeanVarNormalization(input, w, b);
+
+                input = output;
+            }
+
+            if (m_lookupTableOrder > 0)
+            {
+                e = m_net->CreateLearnableParameter(msra::strfun::wstrprintf(L"E%d", 0), m_layerSizes[1], m_layerSizes[0] / m_lookupTableOrder);
+                m_net->InitLearnableParameters(e, m_uniformInit, randomSeed++, m_initValueScale);
+                output = m_net->LookupTable(e, input, L"LookupTable");
+
+                if (m_addDropoutNodes)
+                    input = m_net->Dropout(output);
+                else
+                    input = output;
+
+                outputFromEachLayer[1] = input;
+            }
+
+            /// direct connect from input node to output node
+
+            int recur_idx = 0;
+            int offset = m_lookupTableOrder > 0 ? 1 : 0;
+            if (numHiddenLayers > 0)
+            {
+                output = (ComputationNodePtr)BuildLSTMComponent(randomSeed, mbSize, 0, m_layerSizes[offset] * (offset ? m_lookupTableOrder : 1), m_layerSizes[offset + 1], input);
+                input = output;
+                outputFromEachLayer[offset + 1] = input;
+
+                for (int i = 1 + offset; i<numHiddenLayers; i++)
+                {
+                    if (m_recurrentLayers.size() > 0 && m_recurrentLayers[recur_idx] == i)
+                    {
+                        output = (ComputationNodePtr)BuildLSTMComponent(randomSeed, mbSize, i, m_layerSizes[i], m_layerSizes[i + 1], input);
+
+                        recur_idx++;
+                    }
+                    else
+                    {
+                        u = m_net->CreateLearnableParameter(msra::strfun::wstrprintf(L"U%d", i), m_layerSizes[i + 1], m_layerSizes[i]);
+                        m_net->InitLearnableParameters(u, m_uniformInit, randomSeed++, m_initValueScale);
+                        b = m_net->CreateLearnableParameter(msra::strfun::wstrprintf(L"B%d", i), m_layerSizes[i + 1], 1);
+                        output = ApplyNonlinearFunction(m_net->Plus(m_net->Times(u, input), b), i);
+                    }
+
+                    if (m_addDropoutNodes)
+                        input = m_net->Dropout(output);
+                    else
+                        input = output;
+
+                    outputFromEachLayer[i + 1] = input;
+                }
+            }
+
+            for (size_t i = offset; i < m_layerSizes.size(); i++)
+            {
+                /// add direct connect from each layers' output to the layer before the output layer
+                output = BuildDirectConnect(randomSeed, mbSize, i, (i > 1) ? m_layerSizes[i] : ((offset == 0) ? m_layerSizes[i] : m_layerSizes[i] * m_lookupTableOrder), m_layerSizes[numHiddenLayers], outputFromEachLayer[i], input);
+                if (output != nullptr)
+                    input = output;
+            }
+
+            /// need to have [input_dim x output_dim] matrix
+            /// e.g., [200 x 10000], where 10000 is the vocabulary size
+            /// this is for speed-up issue as per word matrix can be simply obtained using column slice
+            w = m_net->CreateLearnableParameter(msra::strfun::wstrprintf(L"W%d", numHiddenLayers), m_layerSizes[numHiddenLayers], m_layerSizes[numHiddenLayers + 1]);
+            m_net->InitLearnableParameters(w, m_uniformInit, randomSeed++, m_initValueScale);
+
+            double val = w->FunctionValues()(0, 0);
+
+            /// the label is a dense matrix. each element is the word index
+            label = m_net->CreateInputNode(L"labels", 2 * (this->nce_noises + 1), mbSize);
+
+            bias = m_net->CreateLearnableParameter(L"BiasVector", m_layerSizes[m_layerSizes.size() - 1], 1);
+            bias->FunctionValues().SetValue((ElemType)-std::log(m_layerSizes[m_layerSizes.size() - 1]));
+            //m_net->InitLearnableParameters(bias, m_uniformInit, randomSeed++, std::log(m_layerSizes[m_layerSizes.size() - 1])* m_initValueScale);
+            //clslogpostprob = m_net->Times(clsweight, input, L"ClassPostProb");
+
+            output = AddTrainAndEvalCriterionNodes(input, label, w, L"TrainNodeNCEBasedCrossEntropy", L"EvalNodeNCEBasedCrossEntrpy", bias);
+
+            m_net->OutputNodes().push_back(output);
+
+            if (m_needPrior)
+            {
+                prior = m_net->Mean(label);
+            }
+        }
+
+        m_net->ResetEvalTimeStamp();
+
+        return *m_net;
+    }
 
     template class SimpleNetworkBuilder<float>;
     template class SimpleNetworkBuilder<double>;
diff --git a/MachineLearning/cn/SimpleNetworkBuilder.h b/MachineLearning/cn/SimpleNetworkBuilder.h
index da37a9524..587fef540 100644
--- a/MachineLearning/cn/SimpleNetworkBuilder.h
+++ b/MachineLearning/cn/SimpleNetworkBuilder.h
@@ -26,14 +26,16 @@ namespace Microsoft { namespace MSR { namespace CNTK {
     typedef enum tpRNNType { SIMPLENET=0, /// no recurrent connections
             SIMPLERNN = 1, LSTM=2, DEEPRNN=4, CLASSLM = 8, 
             LBLM=16,
-            NPLM=32, CLASSLSTM=64, TENSORIOLSTM=128} RNNTYPE; 
+            NPLM = 32, CLASSLSTM = 64, NCELSTM = 128, TENSORIOLSTM = 256} RNNTYPE;
+
 
     enum class TrainingCriterion : int
     {
         CrossEntropyWithSoftmax,
         CrossEntropy,
         SquareError,
-        ClassCrossEntropyWithSoftmax
+        ClassCrossEntropyWithSoftmax,
+        NCECrossEntropyWithSoftmax
     };
 
     enum class EvalCriterion : int
@@ -42,7 +44,9 @@ namespace Microsoft { namespace MSR { namespace CNTK {
         CrossEntropy,
         SquareError,
         ErrorPrediction,
-        ClassCrossEntropyWithSoftmax
+        ClassCrossEntropyWithSoftmax,
+
+        NCECrossEntropyWithSoftmax
     };
 
     extern TrainingCriterion ParseTrainingCriterionString(wstring s);
@@ -134,6 +138,8 @@ namespace Microsoft { namespace MSR { namespace CNTK {
                 m_rnnType= NPLM;
             if (std::find(strType.begin(), strType.end(), L"CLASSLSTM") != strType.end())
                 m_rnnType= CLASSLSTM;
+            if (std::find(strType.begin(), strType.end(), L"NCELSTM") != strType.end())
+                m_rnnType = NCELSTM;
             if (std::find(strType.begin(), strType.end(), L"TENSORIOLSTM") != strType.end())
                 m_rnnType= TENSORIOLSTM;
         }
@@ -174,6 +180,7 @@ namespace Microsoft { namespace MSR { namespace CNTK {
             m_cls2index = config("cls2index", "");
             m_vocabSize = (int)config("vocabSize", "-1");
             m_nbrCls = (int)config("nbrClass", "-1");
+            nce_noises = (int)config("noise_number", "-1");//nce noise
  
             Init(layers, trainingCriterion, evalCriterion, outputLayerSize,
                 nonlinearFunctions, addDropoutNodes,
@@ -222,6 +229,8 @@ namespace Microsoft { namespace MSR { namespace CNTK {
                 return BuildLSTMNetworkFromDescription(mbSize);
             if (m_rnnType == CLASSLSTM)
                 return BuildCLASSLSTMNetworkFromDescription(mbSize);
+            if (m_rnnType == NCELSTM)
+                return BuildNCELSTMNetworkFromDescription(mbSize);
             if (m_rnnType == CLASSLM)
                 return BuildClassEntropyNetwork(mbSize);
             if (m_rnnType == LBLM)
@@ -348,6 +357,7 @@ namespace Microsoft { namespace MSR { namespace CNTK {
 
         ComputationNetwork<ElemType>& BuildCLASSLSTMNetworkFromDescription(size_t mbSize = 1);
         
+        ComputationNetwork<ElemType>& BuildNCELSTMNetworkFromDescription(size_t mbSize = 1);
         ComputationNetwork<ElemType>& BuildLSTMInputOutputTensorNetworkFromDescription(size_t mbSize = 1);        
         
         ComputationNetwork<ElemType>& BuildNetworkFromDbnFile(const std::wstring& dbnModelFileName)
@@ -475,6 +485,7 @@ namespace Microsoft { namespace MSR { namespace CNTK {
 
             if (!CheckDbnTag(fstream,"ENET"))
                 throw std::runtime_error("Error reading DBN file - did not find expected tag ENET\n");
+            //size_t outputLayerSize =  m_layerSizes[m_layerSizes.size()-1];
 
             label = m_net->Input(m_outputLayerSize, mbSize, L"labels");
 
@@ -596,6 +607,10 @@ namespace Microsoft { namespace MSR { namespace CNTK {
                 break;
             case TrainingCriterion::ClassCrossEntropyWithSoftmax:
                 output = m_net->ClassCrossEntropyWithSoftmax(label, input, matrix, clspostprob, (trainNodeName == L"")?L"ClassCrossEntropyWithSoftmax":trainNodeName);
+                break;
+            case TrainingCriterion::NCECrossEntropyWithSoftmax:
+                output = m_net->NoiseContrastiveEstimation(label, input, matrix, clspostprob, (trainNodeName == L"") ? L"NoiseContrastiveEstimationNode" : trainNodeName);
+                
                 break;
          default:
                 throw std::logic_error("Unsupported training criterion.");
@@ -604,7 +619,8 @@ namespace Microsoft { namespace MSR { namespace CNTK {
 
             if (!((m_evalCriterion == EvalCriterion::CrossEntropyWithSoftmax && m_trainCriterion == TrainingCriterion::CrossEntropyWithSoftmax) ||
                 (m_evalCriterion == EvalCriterion::SquareError && m_trainCriterion == TrainingCriterion::SquareError) ||
-                (m_evalCriterion == EvalCriterion::ClassCrossEntropyWithSoftmax && m_trainCriterion == TrainingCriterion::ClassCrossEntropyWithSoftmax)))
+                (m_evalCriterion == EvalCriterion::ClassCrossEntropyWithSoftmax && m_trainCriterion == TrainingCriterion::ClassCrossEntropyWithSoftmax) ||
+                (m_evalCriterion == EvalCriterion::NCECrossEntropyWithSoftmax && m_trainCriterion == TrainingCriterion::NCECrossEntropyWithSoftmax)))
             {
                 switch (m_evalCriterion)
                 {
@@ -613,6 +629,9 @@ namespace Microsoft { namespace MSR { namespace CNTK {
                     break;
                 case EvalCriterion::ClassCrossEntropyWithSoftmax:
                     output = m_net->ClassCrossEntropyWithSoftmax(label, input, matrix, clspostprob, (evalNodeName == L"") ? L"ClassCrossEntropyWithSoftmax" : evalNodeName);
+                    break;  
+                case EvalCriterion::NCECrossEntropyWithSoftmax:
+                    output = m_net->NoiseContrastiveEstimation(label, input, matrix, clspostprob, (evalNodeName == L"") ? L"NoiseContrastiveEstimationNode" : evalNodeName);
                     break;
                 case EvalCriterion::SquareError:
                     output = m_net->SquareError(label, tinput, (evalNodeName == L"")?L"SquareError":evalNodeName);
@@ -730,6 +749,7 @@ namespace Microsoft { namespace MSR { namespace CNTK {
         string m_word2class;
         int m_nbrCls;  /// number of classes
         int m_vocabSize; /// vocabulary size
+        int nce_noises;
 
     };
 
diff --git a/MachineLearning/cn/TrainingCriterionNode.h b/MachineLearning/cn/TrainingCriterionNode.h
index b43e2e27e..89a65152a 100644
--- a/MachineLearning/cn/TrainingCriterionNode.h
+++ b/MachineLearning/cn/TrainingCriterionNode.h
@@ -868,6 +868,219 @@ namespace Microsoft { namespace MSR { namespace CNTK {
 
     template class MatrixL2RegNode<float>; 
     template class MatrixL2RegNode<double>;
+    enum NCEEvalMode
+    {
+        Softmax = 0,
+        Unnormalized = 1,
+        None = 2
+    };
+    template<class ElemType>
+    class NoiseContrastiveEstimationNode : public ComputationNode < ElemType >
+    {
+        UsingComputationNodeMembers;
+    public:
+        NoiseContrastiveEstimationNode(const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX, const std::wstring name = L"", NCEEvalMode xm_evalMode = NCEEvalMode::None)
+            : ComputationNode<ElemType>(deviceId), m_logSoftmax(deviceId),
+            m_softMax(deviceId), m_grdToSoftMaxInput(deviceId), m_ncePrediction(deviceId)
+        {
+                m_nodeName = (name == L"" ? CreateUniqNodeName() : name);
+                m_deviceId = deviceId;
+                MoveMatricesToDevice(deviceId);
+                InitRecurrentNode();
+                m_evalMode = xm_evalMode;
+            }
+        NCEEvalMode &EvalMode(){ return m_evalMode; }
+
+        NoiseContrastiveEstimationNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX, const std::wstring name = L"")
+            : ComputationNode<ElemType>(deviceId), m_logSoftmax(deviceId),
+            m_softMax(deviceId), m_grdToSoftMaxInput(deviceId), m_ncePrediction(deviceId)
+        {
+                m_nodeName = (name == L"" ? CreateUniqNodeName() : name);
+                LoadFromFile(fstream, modelVersion, deviceId);
+            }
+
+        virtual const std::wstring OperationName() const { return TypeName(); }
+        static const std::wstring TypeName() { return L"NCEBasedCrossEntropyWithSoftmax"; }
+
+        /**
+        compute gradients to input observations, the weights to the observations, and the class log posterior probabilities
+        */
+        virtual void ComputeInputPartial(const size_t inputIndex)
+        {
+            m_needRecomputeGradientToSoftmaxInput = false;
+            //gradient computation@yinggongzhao
+            //inputIndex should be 2 this time
+            if (m_evalMode != NCEEvalMode::None)
+                throw std::logic_error("ComputeInputPartial should only be called in training mode");
+            if (inputIndex == 0)
+                throw std::invalid_argument("ComputeInput partial should not be called for label");
+            //                                                                              samples+probs                   hidden                  embedding
+            Inputs(inputIndex)->GradientValues().AssignNCEDerivative(m_ncePrediction, Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues(), Inputs(2)->FunctionValues(), inputIndex);
+        }
+
+        virtual void ComputeInputPartial(const size_t /*inputIndex*/, const size_t /*timeIdxInSeq*/)
+        {
+            throw std::logic_error("NCECrossEntropyWithSoftmax node should never be in a loop.");
+        }
+
+        static void WINAPI ComputeInputPartialRight(const Matrix<ElemType>& inputFunctionValues, Matrix<ElemType>& inputGradientValues, const Matrix<ElemType>& gradientValues)
+        {
+            Matrix<ElemType>::MultiplyAndAdd(inputFunctionValues, false, gradientValues, true, inputGradientValues);
+        }
+
+        static void WINAPI ComputeInputPartialLeft(const Matrix<ElemType>& obs, Matrix<ElemType>& inputGradientValues, const Matrix<ElemType>& gradientValues)
+        {
+            Matrix<ElemType>::MultiplyAndAdd(obs, false, gradientValues, false, inputGradientValues);
+        }
+
+        static void WINAPI ComputeCEPartialToSoftmaxInputs(Matrix<ElemType>& inputGradientValues, Matrix<ElemType>& gradientValues, size_t y_t)
+        {
+            Matrix<ElemType>::MinusOneAt(inputGradientValues, y_t);
+            Matrix<ElemType>::Scale(gradientValues, inputGradientValues);
+        }
+
+        virtual void EvaluateThisNode()   //-sum(left_i * log(softmax_i(right)))
+        {
+            if (m_evalMode == NCEEvalMode::Softmax || Inputs(0)->FunctionValues().GetNumRows() == 1)
+            {
+                // evaluation uses softmax
+                m_logSoftmax.AssignProductOf(Inputs(1)->FunctionValues(), true, Inputs(2)->FunctionValues(), false);
+#pragma omp parallel for
+                for (int i = 0; i < Inputs(0)->FunctionValues().GetNumCols(); i++)
+                for (int j = 0; j < Inputs(3)->FunctionValues().GetNumRows(); j++)
+                    m_logSoftmax(i, j) += Inputs(3)->FunctionValues()(j, 0);
+                m_logSoftmax.InplaceLogSoftmax(false);
+                FunctionValues().Resize(1, 1);
+                FunctionValues().SetValue(0);
+                for (int i = 0; i < Inputs(0)->FunctionValues().GetNumCols(); i++)
+                    FunctionValues()(0, 0) -= m_logSoftmax(i, (size_t)Inputs(0)->FunctionValues()(0, i));
+                ElemType val = FunctionValues()(0, 0);
+                val *= 1;
+            }
+            else if (m_evalMode == NCEEvalMode::Unnormalized)
+            {
+                FunctionValues().AssignNceUnnormalizedEval(Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues(), Inputs(2)->FunctionValues());
+            }
+            else
+            {
+                // training criterion uses NCE
+                //likelihood                                         samples+probs                        hidden                       embedding            bias
+                FunctionValues().AssignNoiseContrastiveEstimation(Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues(), Inputs(2)->FunctionValues(), Inputs(3)->FunctionValues(), m_ncePrediction);
+            }
+            m_needRecomputeGradientToSoftmaxInput = true;
+        }
+
+        virtual void EvaluateThisNode(const size_t /*timeIdxInSeq*/)
+        {
+            throw std::logic_error("NCECrossEntropyWithSoftmax node should never be in a loop.");
+        }
+
+        /**
+        Inputs: [0] label in dense matrix in [4 x T]
+        the first row is the word index, the second row is the class index, the third row is the first word index of the class
+        the last row is the first word index of the next class
+        [1] hidden layer activity to the node in [hdsize x T]. for a simple rnn, this is the hidden layer activty
+        [2] weight matrix in [hdsize x vocab_size], for speed-up, as per word matrix can be simply obtained as column slice
+        [3] clsprob in dense matrix in [nbr_cls x T]. this is the output from logsoftmax node for the log-posterior probabilty of class given observations
+        */
+        virtual void Validate()
+        {
+            PrintSelfBeforeValidation();
+
+            if (m_children.size() != 4)
+                throw std::logic_error("NoiseContrastiveEstimationNode criterion requires four inputs.");
+
+            if (Inputs(0)->OperationName() != InputValue<ElemType>::TypeName())
+                throw std::logic_error("NoiseContrastiveEstimationNode criterion requires the first input to be the label.");
+
+            if (!(Inputs(1)->FunctionValues().GetNumRows() == Inputs(2)->FunctionValues().GetNumRows())) // input and matrix can be timed
+            {
+                throw std::logic_error("The Matrix<ElemType>  dimension for observation and weight in the NoiseContrastiveEstimationNode operation does not match.");
+            }
+            if (!(Inputs(0)->FunctionValues().GetNumCols() == Inputs(1)->FunctionValues().GetNumCols())) // label and input same obs numbers
+            {
+                throw std::logic_error("The Matrix<ElemType>  dimension for label and observation in the NoiseContrastiveEstimationNode operation does not match.");
+            }
+            //if (!(Inputs(0)->FunctionValues().GetNumRows() == 3)) // label needs to be 4 rows
+            //{
+            //  throw std::logic_error("The label in the NoiseContrastiveEstimationNode operation needs to be 4 rows.");
+            // }
+
+            //cerr << Inputs(3)->FunctionValues().GetNumCols() << "\t" << Inputs(0)->FunctionValues().GetNumCols() << endl;
+            //if (!(Inputs(3)->FunctionValues().GetNumCols() == Inputs(0)->FunctionValues().GetNumCols())) // number of observations
+            //{
+            //   throw std::logic_error("The number of observations in class log post probability and label in the NoiseContrastiveEstimationNode operation don't match.");
+            // }
+            FunctionValues().Resize(1, 1);
+            CopyImageSizeFromInputs();
+        }
+
+        virtual void CopyImageSizeFromInputs()
+        {
+            CopyImageSizeFromInput(0, false);
+            m_outputChannels = 1;
+            m_outputWidth = 1;
+            m_outputHeight = 1;
+        }
+
+        virtual void AttachInputs(const ComputationNodePtr label, const ComputationNodePtr input,
+            const ComputationNodePtr inputweight, const ComputationNodePtr biasWeight)
+        {
+            m_children.resize(4);
+            m_children[0] = label;
+            m_children[1] = input;
+            m_children[2] = inputweight;
+            m_children[3] = biasWeight;
+        }
+
+        virtual void MoveMatricesToDevice(const DEVICEID_TYPE deviceId)
+        {
+            ComputationNode<ElemType>::MoveMatricesToDevice(deviceId);
+            if (deviceId != AUTOPLACEMATRIX)
+            {
+                if (m_logSoftmax.GetDeviceId() != deviceId)
+                    m_logSoftmax.TransferFromDeviceToDevice(m_logSoftmax.GetDeviceId(), deviceId, true);
+                if (m_softMax.GetDeviceId() != deviceId)
+                    m_softMax.TransferFromDeviceToDevice(m_softMax.GetDeviceId(), deviceId, true);
+                if (m_grdToSoftMaxInput.GetDeviceId() != deviceId)
+                    m_grdToSoftMaxInput.TransferFromDeviceToDevice(m_grdToSoftMaxInput.GetDeviceId(), deviceId, true);
+            }
+        }
+
+        // copy constructor
+        NoiseContrastiveEstimationNode(const NoiseContrastiveEstimationNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags)
+            : ComputationNode<ElemType>(node->m_deviceId), m_logSoftmax(node->m_deviceId), m_softMax(node->m_deviceId), m_grdToSoftMaxInput(node->m_deviceId)
+        {
+                node->CopyTo(this, newName, flags);
+            }
+
+        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            const std::wstring& name = (newName == L"") ? NodeName() : newName;
+
+            ComputationNodePtr node = new NoiseContrastiveEstimationNode<ElemType>(this, name, flags);
+            return node;
+        }
+
+    protected:
+        Matrix<ElemType> m_logSoftmax;
+        Matrix<ElemType> m_softMax;
+        Matrix<ElemType> m_ncePrediction;
+
+        /// gradient of cross entropy with respect to the input of softmax
+        /// a 1 row by \sum_t m_nbrWordsInEachTime[t] vector
+        /// one slice of size m_nbrWordsInEachTime[t] saves the input to softmax for word y_t
+        Matrix<ElemType> m_grdToSoftMaxInput;
+        bool m_needRecomputeGradientToSoftmaxInput;
+
+        size_t m_nbrNoise;
+        //size_t           m_nbrCls;//number class
+        size_t           m_totalNbrWords;
+    private:
+        NCEEvalMode m_evalMode;
+    };
+    template class NoiseContrastiveEstimationNode<float>;
+    template class NoiseContrastiveEstimationNode<double>;
 
     //calculates: -sum(left_i * log(softmax_i(right))) for class given history and for word given history
     // need to provide class probabilty from external node
diff --git a/MachineLearning/cn/cn.cpp b/MachineLearning/cn/cn.cpp
index e2ad40a22..ce5f05b25 100644
--- a/MachineLearning/cn/cn.cpp
+++ b/MachineLearning/cn/cn.cpp
@@ -330,6 +330,8 @@ namespace Microsoft {
                     return TrainingCriterion::CrossEntropyWithSoftmax;
                 else if (s == L"squareerror")
                     return TrainingCriterion::SquareError;
+                else if (s == L"noisecontrastiveestimationnode")
+                    return TrainingCriterion::NCECrossEntropyWithSoftmax;
                 else if (s != L"classcrossentropywithsoftmax")    // (twisted logic to keep compiler happy w.r.t. not returning from LogicError)
                     LogicError("trainingCriterion: Invalid trainingCriterion value. Valid values are (CrossEntropyWithSoftmax | SquareError | ClassCrossEntropyWithSoftmax)");
                 return TrainingCriterion::ClassCrossEntropyWithSoftmax;
@@ -344,6 +346,8 @@ namespace Microsoft {
                     return EvalCriterion::CrossEntropyWithSoftmax;
                 else if (s == L"classcrossentropywithsoftmax")
                     return EvalCriterion::ClassCrossEntropyWithSoftmax;
+                else if (s == L"noisecontrastiveestimationnode")
+                    return EvalCriterion::NCECrossEntropyWithSoftmax;
                 else if (s != L"squareerror")
                     LogicError("evalCriterion: Invalid trainingCriterion value. Valid values are (ErrorPrediction | CrossEntropyWithSoftmax | SquareError)");
                 return EvalCriterion::SquareError;
diff --git a/Math/Math/CPUMatrix.cpp b/Math/Math/CPUMatrix.cpp
index f39b5f182..61f87f781 100644
--- a/Math/Math/CPUMatrix.cpp
+++ b/Math/Math/CPUMatrix.cpp
@@ -19,7 +19,7 @@
 #include <chrono>
 #include <exception>
 #include <thread>
-
+#include<iostream>
 #ifdef     _WIN32
 #include <Windows.h>
 #else
@@ -3763,6 +3763,135 @@ namespace Microsoft { namespace MSR { namespace CNTK {
         return CPUMatrix<ElemType>::MultiplyAndWeightedAdd(1.0, a, transposeA, b, transposeB, 1.0, c);
     }
 
+    template<class ElemType>
+    void CPUMatrix<ElemType>::AssignNCEUnnormalizedEval(const CPUMatrix<ElemType>& a,
+        const CPUMatrix<ElemType>& b, CPUMatrix<ElemType>& c)
+        //this: samples+probs
+        // a:   hidden
+        // b:   embedding
+        // tmp:  softmax
+        //  c: loglikelihood
+    {
+        ElemType log_likelihood = 0.0;
+        size_t sample_size = this->GetNumRows() / 2;
+        size_t batch_size = this->GetNumCols();
+        size_t num_noise_samples = sample_size - 1;
+        ElemType log_num_noise_samples = (ElemType)std::log(num_noise_samples);
+#pragma omp parallel for reduction(+:log_likelihood)
+        for (int instance_id = 0; instance_id < batch_size; instance_id++)
+        for (int sample_id = 0; sample_id < sample_size; sample_id++)
+        {
+            int sample =(int) (*this)(2 * sample_id, instance_id);
+            ElemType prob = -(*this)(2 * sample_id + 1, instance_id);
+            if (sample_id == 0)
+                prob = -prob;
+            double score = 0;// a[sample];
+            for (int dim = 0; dim < b.GetNumCols(); dim++)
+                score += a(sample, dim)* b(dim, instance_id);
+            double score_noise = log_num_noise_samples + prob;
+            double z = logadd(score, score_noise);
+            double logprob = score - z;
+            double logprob_noise = score_noise - z;
+            log_likelihood += sample_id == 0 ? (ElemType)logprob : (ElemType)logprob_noise;
+        }
+        c(0, 0) = log_likelihood;
+    }
+
+    //samples+prob                         gradient           hidden               embedding          embedding/hidden
+    //a.m_CPUMatrix->AssignNCEDerivative(*tmp.m_CPUMatrix, *a.m_CPUMatrix, *b.m_CPUMatrix, inputIndex, *c.m_CPUMatrix);
+    template<class ElemType>
+    CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignNCEDerivative(const CPUMatrix<ElemType>& tmp, const CPUMatrix<ElemType>& a, const CPUMatrix<ElemType>& b, size_t inputIndex, CPUMatrix<ElemType>& c)
+    {
+        size_t sample_size = this->GetNumRows() / 2;
+        size_t batch_size = this->GetNumCols();
+        if (inputIndex == 1)
+        {
+#pragma omp parallel for
+            for (int instance_id = 0; instance_id < batch_size; instance_id++)
+            for (int sample_id = 0; sample_id < sample_size; sample_id++)
+            {
+                int sample =(int) (*this)(2 * sample_id, instance_id);
+                for (int dim = 0; dim < b.GetNumRows(); dim++)
+                    c(dim, instance_id) -= b(dim, sample)* tmp(sample_id, instance_id);
+            }
+        }
+        else if (inputIndex == 2)
+        {
+            int i_blocks = omp_get_num_threads() * 16;
+            // Assume only one block in k direction.
+            // We don't need to explicitly block in the j direction.
+#pragma omp parallel for
+            for (int ib = 0; ib < i_blocks; ib++)
+            for (int instance_id = 0; instance_id < batch_size; instance_id++)
+            for (int sample_id = 0; sample_id < sample_size; sample_id++)
+            {
+                int sample =(int) (*this)(2 * sample_id, instance_id);
+                if (sample % i_blocks == ib)
+                for (int dim = 0; dim < b.GetNumRows(); dim++)
+                    c(dim, sample) -= a(dim, instance_id)* tmp(sample_id, instance_id);
+            }
+        }
+        else
+        {
+            assert(inputIndex == 3);
+            // Assume only one block in k direction.
+            // We don't need to explicitly block in the j direction.
+            for (int instance_id = 0; instance_id < batch_size; instance_id++)
+            for (int sample_id = 0; sample_id < sample_size; sample_id++)
+            {
+                int sample =(int) (*this)(2 * sample_id, instance_id);
+                c(sample, 0) -= tmp(sample_id, instance_id);
+            }
+        }
+        return *this;
+    }
+
+    template<class ElemType>
+    void CPUMatrix<ElemType>::AssignNoiseContrastiveEstimation(const CPUMatrix<ElemType>& a,
+        const CPUMatrix<ElemType>& b, const CPUMatrix<ElemType>& bias, size_t sampleCount, CPUMatrix<ElemType>& tmp, CPUMatrix<ElemType>& c)
+        //this: samples+probs
+        // a:   hidden
+        // b:   embedding
+        // tmp:  softmax
+        //  c: loglikelihood
+    {
+        /*z
+        for (int i = 0; i < (*this).GetNumRows(); i++)
+        {
+            for (int j = 0; j < (*this).GetNumCols(); j++)
+                std::cerr << (*this)(i, j) << " ";
+            std::cerr << endl;
+        }
+        */
+        sampleCount *= 1;
+        double log_likelihood = 0.0;
+        size_t sample_size = this->GetNumRows() / 2;
+        size_t batch_size = this->GetNumCols();
+        size_t num_noise_samples = sample_size - 1;
+        double log_num_noise_samples = std::log(num_noise_samples);
+#pragma omp parallel for reduction(+:log_likelihood)
+        for (int instance_id = 0; instance_id < batch_size; instance_id++)
+        for (int sample_id = 0; sample_id < sample_size; sample_id++)
+        {
+            int sample =(int) (*this)(2 * sample_id, instance_id);
+            double score = bias(sample, 0);
+            for (int dim = 0; dim < b.GetNumRows(); dim++)
+                score += a(dim, instance_id)* b(dim, sample);
+            double sample_prob = -(*this)(2 * sample_id + 1, instance_id);
+            if (sample_id == 0)
+                sample_prob = -sample_prob;
+            double score_noise = log_num_noise_samples + sample_prob;
+            double z = logadd(score, score_noise);
+            double logprob = score - z;
+            double logprob_noise = score_noise - z;
+            tmp(sample_id, instance_id) = (ElemType)-std::exp(logprob);
+            if (sample_id == 0)
+                tmp(sample_id, instance_id) += 1;
+            log_likelihood += sample_id == 0 ? logprob : logprob_noise; 
+        }
+
+        c(0, 0) = (ElemType)-log_likelihood;
+    }
 
     /// <summary>Matrix-matrix multiply with col-major matrices (a and b may be transposed): c =  op(a) * op(b)</summary>
     /// <param name="a">Input matrix</param>
diff --git a/Math/Math/CPUMatrix.h b/Math/Math/CPUMatrix.h
index e70c6ea3f..f6199aef0 100644
--- a/Math/Math/CPUMatrix.h
+++ b/Math/Math/CPUMatrix.h
@@ -215,6 +215,13 @@ namespace Microsoft { namespace MSR { namespace CNTK {
         void VectorNorm2(CPUMatrix<ElemType>& c, const bool isColWise) const;
         CPUMatrix<ElemType>& AssignVectorNorm2Of(CPUMatrix<ElemType>& a, const bool isColWise);
 
+        void AssignNoiseContrastiveEstimation(const CPUMatrix<ElemType>& a, const CPUMatrix<ElemType>& b, const CPUMatrix<ElemType>& bias,
+            size_t sampleCount, CPUMatrix<ElemType>& tmp, CPUMatrix<ElemType>& c);
+
+        void AssignNCEUnnormalizedEval(const CPUMatrix<ElemType>& a, const CPUMatrix<ElemType>& b, CPUMatrix<ElemType>& c);
+
+        CPUMatrix<ElemType>& AssignNCEDerivative(const CPUMatrix<ElemType>& tmp, const CPUMatrix<ElemType>& a, const CPUMatrix<ElemType>& b, size_t inputIndex, CPUMatrix<ElemType>& c);
+
         void VectorNormInf(CPUMatrix<ElemType>& c, const bool isColWise) const;
         CPUMatrix<ElemType>& AssignVectorNormInfOf(CPUMatrix<ElemType>& a, const bool isColWise);
 
diff --git a/Math/Math/GPUMatrix.cu b/Math/Math/GPUMatrix.cu
index a19759314..49aa96154 100644
--- a/Math/Math/GPUMatrix.cu
+++ b/Math/Math/GPUMatrix.cu
@@ -38,6 +38,8 @@ bool do_sync = true;
 
 #define DEFAULT_THREAD_PER_DIM		16
 
+#define UNCONST(t,c,uc)  GPUMatrix<t> &uc = const_cast<GPUMatrix<t>&>(c);
+
 #ifdef _WIN32
 // thread local storage to access the current stream, initalize to default stream
 __declspec (thread)
@@ -1744,13 +1746,119 @@ namespace Microsoft { namespace MSR { namespace CNTK {
         cudaEvent_t done = nullptr;
         if (do_sync)    CUDA_CALL(cudaEventCreate(&done));        
 
-        _assignSigmoidDerivative<ElemType><<<blocksPerGrid,threadsPerBlock,0,t_stream>>>(a.m_pArray, m_pArray, N);
+        //_assignSigmoidDerivative<ElemType><<<blocksPerGrid,threadsPerBlock,0,t_stream>>>(a.m_pArray, m_pArray, N);
         if (do_sync)    CUDA_CALL(cudaEventRecord(done));        
         if (do_sync)    CUDA_CALL(cudaEventSynchronize(done)); 
         if (do_sync)    CUDA_CALL(cudaEventDestroy(done));
         return *this;
     }
 
+    template<class ElemType>
+    void GPUMatrix<ElemType>::AssignNoiseContrastiveEstimation(const GPUMatrix<ElemType>& a,
+        const GPUMatrix<ElemType>& b, size_t sampleCount, GPUMatrix<ElemType>& tmp, GPUMatrix<ElemType>& c)
+    {
+        UNCONST(ElemType, a, my_a);
+        UNCONST(ElemType, b, my_b);
+
+        cudaEvent_t done;
+        if (do_sync) CUDA_CALL(cudaEventCreate(&done));
+
+        int p = 512;
+        int width = a.GetNumCols();
+        while (p / 2 > width) p = p / 2;
+        
+        _computeNceOutput<ElemType> << <m_nz, p >> >(
+            this->GetArray(),
+            m_numRows,
+            sampleCount,
+            my_a.GetArray(),//a
+            a.GetNumCols(),
+            my_b.GetArray(),//b
+            tmp.GetArray());//tmp
+
+        p = 512;
+        while (p / 2 > m_nz) p = p / 2;
+
+        // summing up objective must be done in one block
+        _assignNoiseContrastiveEstimation<ElemType> << <1, p >> >(
+            this->GetArray(),
+            m_numRows,
+            sampleCount, my_a.GetArray(),
+            a.GetNumCols(),
+            my_b.GetArray(),
+            tmp.GetArray(),
+            c.GetArray());
+
+        _computeNceError<ElemType> << <1, p >> >(
+            this->GetArray(),
+            m_numRows,
+            tmp.GetNumCols(),
+            tmp.GetArray());
+          
+        if (do_sync) CUDA_CALL(cudaEventRecord(done));
+        if (do_sync) CUDA_CALL(cudaEventSynchronize(done));
+        if (do_sync) CUDA_CALL(cudaEventDestroy(done));
+    }
+
+    template<class ElemType>
+    void GPUMatrix<ElemType>::AssignNCEDerivative(GPUMatrix<ElemType>& tmp, const GPUMatrix<ElemType>& a,
+        const GPUMatrix<ElemType>& b, size_t inputIndex, GPUMatrix<ElemType>& c)
+    {
+        UNCONST(ElemType, a, my_a);
+        UNCONST(ElemType, b, my_b);
+        cudaEvent_t done;
+        if (do_sync) CUDA_CALL(cudaEventCreate(&done));
+        int p = 512;
+        int width = a.GetNumCols();
+        while (p / 2 > width) p = p / 2;
+        
+        _assignNceDerivative<ElemType> << <m_nz, p >> >(
+            GetArray(),
+            m_numRows,
+            tmp.GetNumCols(),
+            my_a.GetArray(),
+            a.GetNumCols(),
+            my_b.GetArray(),
+            tmp.GetArray(),
+            c.GetArray(),
+            inputIndex);
+           
+        if (do_sync) CUDA_CALL(cudaEventRecord(done));
+        if (do_sync) CUDA_CALL(cudaEventSynchronize(done));
+        if (do_sync) CUDA_CALL(cudaEventDestroy(done));
+    }
+
+
+
+    template<class ElemType>
+    void GPUMatrix<ElemType>::AssignNCEUnnormalizedEval(const GPUMatrix<ElemType>& a, const GPUMatrix<ElemType>& b, GPUMatrix<ElemType>& c)
+    {
+        assert(a.GetComputeDeviceId() == b.GetComputeDeviceId());
+        assert(GetNumRows() == a.GetNumRows());
+        assert(GetNumCols() == b.GetNumRows());
+        assert(a.GetNumCols() == b.GetNumRows());
+        /*
+        EnsureAuxMemory();
+        int p = 512;
+        int width = a.GetNumCols();
+        while (p / 2 > width) p = p / 2;
+
+        // this kernel need be launched in nnz blocks
+        _sparseInnerProductDenseTimesDense<ElemType> << <m_nz, p >> >(
+        m_dVal,
+        m_buf,
+        m_dCol,
+        m_nz,
+        GetNumRows(),
+        a.GetArray(),
+        b.GetArray(),
+        b.GetNumRows(),
+        m_res);
+
+        //sum up the results
+        _reductionSum32<ElemType> << <1, 32 >> >(m_res, c.GetArray(), m_nz);*/
+    }
+
 
     template<class ElemType>
     GPUMatrix<ElemType>& GPUMatrix<ElemType>::InplaceTanh()
@@ -3757,7 +3865,7 @@ namespace Microsoft { namespace MSR { namespace CNTK {
     template<class ElemType>
     void GPUMatrix<ElemType>::RCRFBackwardCompute(
         const GPUMatrix<ElemType>& alpha, GPUMatrix<ElemType>& beta,
-        const GPUMatrix<ElemType>& lbls,
+        const GPUMatrix<ElemType>& /*lbls*/,
         const GPUMatrix<ElemType>& pos_scores, const GPUMatrix<ElemType>& pair_scores, const int shift)
     {
         if (alpha.IsEmpty() || pos_scores.IsEmpty() || pair_scores.IsEmpty())
diff --git a/Math/Math/GPUMatrix.h b/Math/Math/GPUMatrix.h
index ad999f8a0..185b1123e 100644
--- a/Math/Math/GPUMatrix.h
+++ b/Math/Math/GPUMatrix.h
@@ -284,6 +284,12 @@ namespace Microsoft { namespace MSR { namespace CNTK {
 
         GPUMatrix<ElemType>& AssignInnerProductOfMatrices(const GPUMatrix<ElemType>& a, const GPUMatrix<ElemType>& b); 
 
+
+        void AssignNoiseContrastiveEstimation(const GPUMatrix<ElemType>& a, const GPUMatrix<ElemType>& b, size_t sampleCount, GPUMatrix<ElemType>& tmp, GPUMatrix<ElemType>& c);
+        void AssignNCEDerivative(GPUMatrix<ElemType>& tmp, const GPUMatrix<ElemType>& a, const GPUMatrix<ElemType>& b, size_t inputIndex, GPUMatrix<ElemType>& c);    
+        void AssignNCEUnnormalizedEval(const GPUMatrix<ElemType>& a, const GPUMatrix<ElemType>& b, GPUMatrix<ElemType>& c);
+
+
         void Print(const char* matrixName, size_t rowStart, size_t rowEnd, size_t colStart, size_t colEnd) const;
         void Print(const char* matrixName = NULL) const; //print whole matrix. can be expensive
 
diff --git a/Math/Math/GPUMatrixCUDAKernels.cu b/Math/Math/GPUMatrixCUDAKernels.cu
index b3a4604f5..4b28b1e53 100644
--- a/Math/Math/GPUMatrixCUDAKernels.cu
+++ b/Math/Math/GPUMatrixCUDAKernels.cu
@@ -2729,6 +2729,550 @@ __global__ void _computeGradientOfInput(
     atomicAdd(&grd[IDX2C(h,j,numrows)], sum);
 }
 
+
+template<class ElemType>
+__global__ void computeNCEForwardProp(
+    const ElemType* val,
+    const int* col,
+    int numRows,
+    int sampleCount,
+    const ElemType* a,
+    int numCols_a,
+    const ElemType* b,
+    ElemType* res)
+{
+    // val and col are in CSR format
+    // val is an array contains log_Pn(w). To differentiate positive and negative samples, 
+    // we store log_Pn(w) as it is for positive samples, and -log_Pn(w) for negative samples
+    // col is an array contains index of the word samples
+    // a is a matrix in column major format contains output from hidden layer
+    // b is the weight matrix for output layer
+    // res is the buffer to store computed output (sparse)
+
+    // follow the convention, this kernel must be run on 512 threads per block
+    __shared__ ElemType partials[512];
+    partials[threadIdx.x] = 0;
+
+    // determine the elements to be handled by this block
+    int total = numRows * sampleCount;
+    int loadPerBlock = (total + gridDim.x - 1) / gridDim.x;
+
+    int start = loadPerBlock * blockIdx.x;
+    int end = min(total, loadPerBlock * (blockIdx.x + 1));
+
+    for (int i = start; i < end; i++)
+    {
+        int colIndex = col[i];
+        int rowIndex = i / sampleCount;
+
+        int loadPerThread = (numCols_a + blockDim.x - 1) / blockDim.x;
+        int tstart = loadPerThread * threadIdx.x;
+        int tend = min(numCols_a, loadPerThread * (threadIdx.x + 1));
+
+        for (int j = tstart; j < tend; j++)
+            partials[threadIdx.x] = a[IDX2C(rowIndex, j, numRows)] * b[IDX2C(j, colIndex, numCols_a)];
+
+        __syncthreads();
+
+        // sum up
+        int nTotalThreads = blockDim.x;
+
+        while (nTotalThreads >1)
+        {
+            int halfPoint = (nTotalThreads >> 1);
+
+            if (threadIdx.x < halfPoint)
+                partials[threadIdx.x] += partials[threadIdx.x + halfPoint];
+
+            __syncthreads();
+
+            nTotalThreads = (nTotalThreads >> 1);
+        }
+
+        if (threadIdx.x == 0)
+            res[i] = partials[0];
+    }
+}
+
+
+template<class ElemType>
+__global__ void _computeNceOutput(
+    const ElemType* col,
+    int numRows,
+    int sampleCount,
+    const ElemType* a,
+    int numCols_a,
+    const ElemType* b,
+    ElemType* res)
+{
+    // val and col are in CSR format
+    // val is an array contains log_Pn(w). To differentiate positive and negative samples, 
+    // we store log_Pn(w) as it is for positive samples, and -log_Pn(w) for negative samples
+    // col is an array contains index of the word samples
+    // a is a matrix in column major format contains output from hidden layer
+    // b is the weight matrix for output layer
+    // res is the buffer to store computed output (sparse)
+
+    // follow the convention, this kernel must be run on 512 threads per block
+    __shared__ ElemType partials[512];
+    partials[threadIdx.x] = 0;
+
+    //threadIdx.x range from[0 ~ 512)
+    //blockIdx.x range from[0 ~ nnz)
+    //blockDim.x equal to 512
+    //gridDim.x equal to nnz
+
+    // determine the elements to be handled by this block
+    int total = numRows * sampleCount;
+    int loadPerBlock = (total + gridDim.x - 1) / gridDim.x;
+
+    int start = loadPerBlock * blockIdx.x;
+    int end = min(total, loadPerBlock * (blockIdx.x + 1));
+
+    for (int i = start; i < end; i++)
+    {
+        int colIndex = (int)col[2 * i];
+        int rowIndex = i / sampleCount;
+
+        int loadPerThread = (numCols_a + blockDim.x - 1) / blockDim.x;
+        int tstart = loadPerThread * threadIdx.x;
+        int tend = min(numCols_a, loadPerThread * (threadIdx.x + 1));
+
+        for (int j = tstart; j < tend; j++)
+            partials[threadIdx.x] = a[IDX2C(rowIndex, j, numRows)] * b[IDX2C(j, colIndex, numCols_a)];
+
+        __syncthreads();
+
+        // sum up
+        int nTotalThreads = blockDim.x;
+
+        while (nTotalThreads >1)
+        {
+            int halfPoint = (nTotalThreads >> 1);
+
+            if (threadIdx.x < halfPoint)
+                partials[threadIdx.x] += partials[threadIdx.x + halfPoint];
+
+            __syncthreads();
+
+            nTotalThreads = (nTotalThreads >> 1);
+        }
+
+        if (threadIdx.x == 0)
+            res[i] = partials[0];
+    }
+}
+
+template<class ElemType>
+__global__ void _computeNceOutput(
+    const ElemType* val,
+    const int* col,
+    int numRows,
+    int sampleCount,
+    const ElemType* a,
+    int numCols_a,
+    const ElemType* b,
+    ElemType* res)
+{
+    // val and col are in CSR format
+    // val is an array contains log_Pn(w). To differentiate positive and negative samples, 
+    // we store log_Pn(w) as it is for positive samples, and -log_Pn(w) for negative samples
+    // col is an array contains index of the word samples
+    // a is a matrix in column major format contains output from hidden layer
+    // b is the weight matrix for output layer
+    // res is the buffer to store computed output (sparse)
+
+    // follow the convention, this kernel must be run on 512 threads per block
+    __shared__ ElemType partials[512];
+    partials[threadIdx.x] = 0;
+
+    //threadIdx.x range from[0 ~ 512)
+    //blockIdx.x range from[0 ~ nnz)
+    //blockDim.x equal to 512
+    //gridDim.x equal to nnz
+
+    // determine the elements to be handled by this block
+    int total = numRows * sampleCount;
+    int loadPerBlock = (total + gridDim.x - 1) / gridDim.x;
+
+    int start = loadPerBlock * blockIdx.x;
+    int end = min(total, loadPerBlock * (blockIdx.x + 1));
+
+    for (int i = start; i < end; i++)
+    {
+        int colIndex = col[i];
+        int rowIndex = i / sampleCount;
+
+        int loadPerThread = (numCols_a + blockDim.x - 1) / blockDim.x;
+        int tstart = loadPerThread * threadIdx.x;
+        int tend = min(numCols_a, loadPerThread * (threadIdx.x + 1));
+
+        for (int j = tstart; j < tend; j++)
+            partials[threadIdx.x] = a[IDX2C(rowIndex, j, numRows)] * b[IDX2C(j, colIndex, numCols_a)];
+
+        __syncthreads();
+
+        // sum up
+        int nTotalThreads = blockDim.x;
+
+        while (nTotalThreads >1)
+        {
+            int halfPoint = (nTotalThreads >> 1);
+
+            if (threadIdx.x < halfPoint)
+                partials[threadIdx.x] += partials[threadIdx.x + halfPoint];
+
+            __syncthreads();
+
+            nTotalThreads = (nTotalThreads >> 1);
+        }
+
+        if (threadIdx.x == 0)
+            res[i] = partials[0];
+    }
+}
+
+
+template<class ElemType>
+__global__ void _assignNoiseContrastiveEstimation(
+    const ElemType* val,
+    int numRows,
+    int sampleCount,
+    const ElemType* a,
+    int width, // number of columns in a
+    const ElemType* b,
+    const ElemType* tmp,
+    ElemType* c) // run on 512 threads per block
+{
+    // val and col are in CSR format
+    // val is an array contains log_Pn(w). To differentiate positive and negative samples, 
+    // we store log_Pn(w) as it is for positive samples, and -log_Pn(w) for negative samples
+    // col is an array contains index of the word samples
+    // a is a matrix in column major format contains output from hidden layer
+    // b is the weight matrix for output layer
+    // tmp is the buffer that stores NCE output calculated from _computeNceOutput
+    // c is the matrix to store objective
+
+    __shared__ ElemType partials[512];
+    partials[threadIdx.x] = 0;
+
+    int total = numRows * sampleCount;
+    int loadPerThread = (total + 511) / 512;
+
+    // find out the items this thread is responsible for
+    int start = loadPerThread * threadIdx.x;
+    int end = min(total, loadPerThread * (threadIdx.x + 1));
+
+    for (int i = start; i < end; i++)
+    {
+        //int colIndex = col[i];
+        //int rowIndex = i / sampleCount;
+
+        // add to objective
+        ElemType log_pnw = val[2 * i + 1];
+        if (log_pnw < 0) // positive sample: log(pw / (pw + k * pnw))
+        {
+            ElemType den = tmp[i];
+            logadd(den, log((ElemType)(sampleCount - 1)) + log_pnw);
+            partials[threadIdx.x] += (tmp[i] - den);
+        }
+        else // negative sample: log(k * pnw / (pw + k * pnw))
+        {
+            ElemType nom = log((ElemType)(sampleCount - 1)) - log_pnw;
+            ElemType den = nom;
+            logadd(den, tmp[i]);
+            partials[threadIdx.x] += (nom - den);
+        }
+    }
+
+    __syncthreads();
+
+    // now sum up the objective function
+    int nTotalThreads = blockDim.x;
+
+    while (nTotalThreads >1)
+    {
+        int halfPoint = (nTotalThreads >> 1);
+
+        if (threadIdx.x < halfPoint)
+            partials[threadIdx.x] += partials[threadIdx.x + halfPoint];
+
+        __syncthreads();
+
+        nTotalThreads = (nTotalThreads >> 1);
+    }
+
+    if (threadIdx.x == 0)
+        c[0] = -partials[0];
+}
+
+template<class ElemType>
+__global__ void _assignNoiseContrastiveEstimation(
+    const ElemType* val,
+    const int* col,
+    int numRows,
+    int sampleCount,
+    const ElemType* a,
+    int width, // number of columns in a
+    const ElemType* b,
+    const ElemType* tmp,
+    ElemType* c) // run on 512 threads per block
+{
+    // val and col are in CSR format
+    // val is an array contains log_Pn(w). To differentiate positive and negative samples, 
+    // we store log_Pn(w) as it is for positive samples, and -log_Pn(w) for negative samples
+    // col is an array contains index of the word samples
+    // a is a matrix in column major format contains output from hidden layer
+    // b is the weight matrix for output layer
+    // tmp is the buffer that stores NCE output calculated from _computeNceOutput
+    // c is the matrix to store objective
+
+    __shared__ ElemType partials[512];
+    partials[threadIdx.x] = 0;
+
+    int total = numRows * sampleCount;
+    int loadPerThread = (total + 511) / 512;
+
+    // find out the items this thread is responsible for
+    int start = loadPerThread * threadIdx.x;
+    int end = min(total, loadPerThread * (threadIdx.x + 1));
+
+    for (int i = start; i < end; i++)
+    {
+        //int colIndex = col[i];
+        //int rowIndex = i / sampleCount;
+
+        // add to objective
+        ElemType log_pnw = val[i];
+        if (log_pnw < 0) // positive sample: log(pw / (pw + k * pnw))
+        {
+            ElemType den = tmp[i];
+            logadd(den, log((ElemType)(sampleCount - 1)) + log_pnw);
+            partials[threadIdx.x] += (tmp[i] - den);
+        }
+        else // negative sample: log(k * pnw / (pw + k * pnw))
+        {
+            ElemType nom = log((ElemType)(sampleCount - 1)) - log_pnw;
+            ElemType den = nom;
+            logadd(den, tmp[i]);
+            partials[threadIdx.x] += (nom - den);
+        }
+    }
+
+    __syncthreads();
+
+    // now sum up the objective function
+    int nTotalThreads = blockDim.x;
+
+    while (nTotalThreads >1)
+    {
+        int halfPoint = (nTotalThreads >> 1);
+
+        if (threadIdx.x < halfPoint)
+            partials[threadIdx.x] += partials[threadIdx.x + halfPoint];
+
+        __syncthreads();
+
+        nTotalThreads = (nTotalThreads >> 1);
+    }
+
+    if (threadIdx.x == 0)
+        c[0] = -partials[0];
+}
+
+template<class ElemType>
+__global__ void _computeNceError(
+    const ElemType* val,
+
+    int numRows,
+    int sampleCount,
+    ElemType* tmp) // run on one block 
+{
+    int total = numRows * sampleCount;
+    int loadPerThread = (total + blockDim.x - 1) / blockDim.x;
+
+    // find out the items this thread is responsible for
+    int start = loadPerThread * threadIdx.x;
+    int end = min(total, loadPerThread * (threadIdx.x + 1));
+
+    for (int i = start; i < end; i++)
+    {
+        ElemType ac = tmp[i]; // precalculated NCE output
+        ElemType log_pnw = val[2 * i + 1];
+
+        ElemType er = 0;
+        if (log_pnw < 0) // positive sample: k * pnw / (pw + k * pnw)
+        {
+            ElemType nom = log((ElemType)(sampleCount - 1)) + log_pnw;
+            logadd(ac, nom);
+            er = -1 * exp(nom - ac);
+
+        }
+        else // negative sample: pw / (pw + k * pnw);
+        {
+            logadd(ac, log((ElemType)(sampleCount - 1)) - log_pnw);
+            er = exp(tmp[i] - ac);
+        }
+
+        tmp[i] = er;
+    }
+}
+
+template<class ElemType>
+__global__ void _computeNceError(
+    const ElemType* val,
+    const int* col,
+    int numRows,
+    int sampleCount,
+    ElemType* tmp) // run on one block 
+{
+    int total = numRows * sampleCount;
+    int loadPerThread = (total + blockDim.x - 1) / blockDim.x;
+
+    // find out the items this thread is responsible for
+    int start = loadPerThread * threadIdx.x;
+    int end = min(total, loadPerThread * (threadIdx.x + 1));
+
+    for (int i = start; i < end; i++)
+    {
+        ElemType ac = tmp[i]; // precalculated NCE output
+        ElemType log_pnw = val[i];
+
+        ElemType er = 0;
+        if (log_pnw < 0) // positive sample: k * pnw / (pw + k * pnw)
+        {
+            ElemType nom = log((ElemType)(sampleCount - 1)) + log_pnw;
+            logadd(ac, nom);
+            er = -1 * exp(nom - ac);
+
+        }
+        else // negative sample: pw / (pw + k * pnw);
+        {
+            logadd(ac, log((ElemType)(sampleCount - 1)) - log_pnw);
+            er = exp(tmp[i] - ac);
+        }
+
+        tmp[i] = er;
+    }
+}
+
+template<class ElemType>
+__global__ void _assignNceDerivativeInJbor(
+    const ElemType* val,
+    const int* col,
+    const int* colndx,
+    int numRows,
+    int sampleCount,
+    const ElemType* a,
+    int width, // number of columns in a
+    const ElemType* b,
+    const ElemType* tmp,
+    unsigned char* c,
+    size_t jborBlockSize)
+{
+    // val and col are CSR format sparse matrix for label
+    // val is an array contains log_Pn(w). To differentiate positive and negative samples
+    // we store log_Pn(w) as it is for positive samples, and -log_Pn(w) for negative samples
+    // col is an array contains index of the word samples
+    // a is a matrix in column major format contains output from hidden layer
+    // b is the weight matrix for output layer
+    // tmp is a matrix of precalculated error
+    // c is the output array to store intermediate results
+
+
+    /*
+    int total = numRows * sampleCount;
+    int loadPerBlock = (total + gridDim.x - 1) / gridDim.x;
+
+    // find out the items this block is responsible for
+    int start = loadPerBlock * blockIdx.x;
+    int end = min(total, loadPerBlock * (blockIdx.x + 1));
+
+    for (int i = start; i < end; i++)
+    {
+    int colIndex = col[i];
+    int rowIndex = i / sampleCount;
+
+    ElemType er = tmp[i]; // precalculated error for this output node
+    ElemType log_pnw = val[i];
+
+    // calculate gradients
+    int loadPerThread = (width + blockDim.x - 1) / blockDim.x;
+    int tstart = loadPerThread * threadIdx.x;
+    int tend = min(width, loadPerThread*(threadIdx.x + 1));
+    for (int j = tstart; j < tend; j++)
+    {
+    ElemType val = er * a[IDX2C(rowIndex, j, numRows)];
+
+    unsigned char* pj = c + (j*jborBlockSize + colndx[i]) * sizeof(JborRecord<ElemType>);
+    atomicExch((int*)pj, colIndex);
+    atomicAdd((ElemType*)(pj + sizeof(int)), val);
+    }
+    }*/
+}
+
+template<class ElemType>
+__global__ void _assignNceDerivative(
+    const ElemType* val,
+    int numRows,
+    int sampleCount,
+    const ElemType* a,
+    int width, // number of columns in a
+    const ElemType* b,
+    const ElemType* tmp,
+    ElemType* c,
+    size_t inputIndex)
+{
+    // val and col are CSR format sparse matrix for label
+    // val is an array contains log_Pn(w). To differentiate positive and negative samples
+    // we store log_Pn(w) as it is for positive samples, and -log_Pn(w) for negative samples
+    // col is an array contains index of the word samples
+    // a is a matrix in column major format contains output from hidden layer
+    // b is the weight matrix for output layer
+    // tmp is a matrix of precalculated error
+    // c is the output matrix to store calculated gradients
+
+    int total = numRows * sampleCount;
+    int loadPerBlock = (total + gridDim.x - 1) / gridDim.x;
+
+    // find out the items this block is responsible for
+    int start = loadPerBlock * blockIdx.x;
+    int end = min(total, loadPerBlock * (blockIdx.x + 1));
+
+    for (int i = start; i < end; i++)
+    {
+        int colIndex = (int)val[2 * i];
+        int rowIndex = i / sampleCount;
+
+        ElemType er = tmp[i]; // precalculated error for this output node
+        ElemType log_pnw = val[2 * i + 1];
+
+        // calculate gradients
+        int loadPerThread = (width + blockDim.x - 1) / blockDim.x;
+        int tstart = loadPerThread * threadIdx.x;
+        int tend = min(width, loadPerThread*(threadIdx.x + 1));
+
+        if (inputIndex == 1) // hidden layer output
+        {
+            for (int j = tstart; j < tend; j++)
+            {
+                ElemType val = er * b[IDX2C(j, colIndex, width)];
+                atomicAdd(c + IDX2C(rowIndex, j, numRows), val);
+                //c[IDX2C(rowIndex, j, numRows)] += val;
+            }
+        }
+        else // weight
+        {
+            for (int j = tstart; j < tend; j++)
+            {
+                ElemType val = er * a[IDX2C(rowIndex, j, numRows)];
+                atomicAdd(c + IDX2C(j, colIndex, width), val);
+                //c[IDX2C(j, colIndex, width)] += val;
+            }
+        }
+    }
+}
+
 // compute gradients of weights in cross entropy node
 template<class ElemType>
 __global__ void _computeGradientOfWeight(
diff --git a/Math/Math/Matrix.cpp b/Math/Math/Matrix.cpp
index 45d339275..6738867a3 100644
--- a/Math/Math/Matrix.cpp
+++ b/Math/Math/Matrix.cpp
@@ -3524,6 +3524,70 @@ namespace Microsoft { namespace MSR { namespace CNTK {
 
         return *this;
     }
+    template<class ElemType>
+    Matrix<ElemType>& Matrix<ElemType>::AssignNceUnnormalizedEval(const Matrix<ElemType>& a, const Matrix<ElemType>& b, const Matrix<ElemType>& c)
+    {
+        if (a.GetMatrixType() != MatrixType::SPARSE)
+            NOT_IMPLEMENTED;
+
+        this->Resize(1, 1);
+        if (this->GetDeviceId() < 0)
+            a.m_CPUMatrix->AssignNCEUnnormalizedEval(*b.m_CPUMatrix, *c.m_CPUMatrix, *this->m_CPUMatrix);
+        else
+            a.m_GPUMatrix->AssignNCEUnnormalizedEval(*b.m_GPUMatrix, *c.m_GPUMatrix, *this->m_GPUMatrix);
+        return *this;
+    }
+
+    template<class ElemType>
+    Matrix<ElemType>& Matrix<ElemType>::AssignNoiseContrastiveEstimation(const Matrix<ElemType>& a, const Matrix<ElemType>& b, const Matrix<ElemType>& c, const Matrix<ElemType>& bias, Matrix<ElemType>& tmp)
+    {
+        if (a.IsEmpty() || b.IsEmpty() || c.IsEmpty())
+            throw std::logic_error("AssignNoiseContrastiveEstimation: one of the input matrices is empty.");
+
+        if (a.GetDeviceId() != b.GetDeviceId() || b.GetDeviceId() != c.GetDeviceId() || c.GetDeviceId() != this->GetDeviceId())
+            NOT_IMPLEMENTED;
+
+        //if (a.GetMatrixType() == MatrixType::DENSE)
+        //    NOT_IMPLEMENTED;
+
+        this->Resize(1, 1);
+
+        if (this->GetDeviceId() < 0)
+        {
+            size_t sampleCount = a.m_CPUMatrix->GetNumElements() / a.m_CPUMatrix->GetNumRows();
+            tmp.Resize(a.GetNumRows() / 2, sampleCount);
+            a.m_CPUMatrix->AssignNoiseContrastiveEstimation(*b.m_CPUMatrix, *c.m_CPUMatrix, *bias.m_CPUMatrix, sampleCount, *tmp.m_CPUMatrix, *this->m_CPUMatrix);
+        }
+        else
+        {
+            size_t sampleCount = a.m_GPUSparseMatrix->GetNumNZElements() / a.m_GPUSparseMatrix->GetNumRows();
+            tmp.Resize(a.GetNumRows() / 2, sampleCount);
+            a.m_GPUMatrix->AssignNoiseContrastiveEstimation(*b.m_GPUMatrix, *c.m_GPUMatrix, sampleCount, *tmp.m_GPUMatrix, *this->m_GPUMatrix);
+        }
+        return *this;
+    }
+
+    template<class ElemType>
+    Matrix<ElemType>& Matrix<ElemType>::AssignNCEDerivative(const Matrix<ElemType>& tmp, const Matrix<ElemType>& a, const Matrix<ElemType>& b, const Matrix<ElemType>& c, size_t inputIndex)
+    {
+        if (a.IsEmpty() || b.IsEmpty() || c.IsEmpty())
+            throw std::logic_error("AssignNoiseContrastiveEstimation: one of the input matrices is empty.");
+
+        if (a.GetDeviceId() != b.GetDeviceId() || b.GetDeviceId() != c.GetDeviceId() || c.GetDeviceId() != this->GetDeviceId())
+            NOT_IMPLEMENTED;
+
+        assert(tmp.GetNumRows() == a.GetNumRows() / 2);
+        if (this->GetDeviceId() < 0)
+        {
+            //samples                           gradient           hidden               embedding            embedding/hidden
+            a.m_CPUMatrix->AssignNCEDerivative(*tmp.m_CPUMatrix, *b.m_CPUMatrix, *c.m_CPUMatrix, inputIndex, *m_CPUMatrix);
+        }
+        else
+        {
+            a.m_GPUMatrix->AssignNCEDerivative(*tmp.m_GPUMatrix, *b.m_GPUMatrix, *c.m_GPUMatrix, inputIndex, *m_GPUMatrix);
+        }
+        return *this;
+    }
 
     template<class ElemType>
     Matrix<ElemType>&   Matrix<ElemType>::AddAveragePoolingGradient(const Matrix<ElemType>& outputGradientBatch, 
diff --git a/Math/Math/Matrix.h b/Math/Math/Matrix.h
index e21ad8053..36b1c4ae4 100644
--- a/Math/Math/Matrix.h
+++ b/Math/Math/Matrix.h
@@ -144,6 +144,11 @@ namespace Microsoft { namespace MSR { namespace CNTK {
         void SetGaussianRandomValue(const ElemType mean, const ElemType sigma, unsigned long seed=USE_TIME_BASED_SEED);
         void SetUniformRandomMask(const ElemType maskRate, const ElemType scaleValue, unsigned long seed=USE_TIME_BASED_SEED); 
         void AddGaussianRandomValue(const ElemType mean, const ElemType sigma, unsigned long seed=USE_TIME_BASED_SEED);
+        Matrix<ElemType>& AssignNoiseContrastiveEstimation(const Matrix<ElemType>& a, const Matrix<ElemType>& b, const Matrix<ElemType>& c, const Matrix<ElemType>& bias, Matrix<ElemType>& tmp);
+
+        Matrix<ElemType>& AssignNCEDerivative(const Matrix<ElemType>& tmp, const Matrix<ElemType>& a, const Matrix<ElemType>& b, const Matrix<ElemType>& c, size_t inputIndex);
+
+        Matrix<ElemType>& AssignNceUnnormalizedEval(const Matrix<ElemType>& a, const Matrix<ElemType>& b, const Matrix<ElemType>& c);
 
         Matrix<ElemType> Transpose();
         Matrix<ElemType>& AssignTransposeOf (const Matrix<ElemType>& a);
diff --git a/Math/Math/NoGPU.cpp b/Math/Math/NoGPU.cpp
index 85bc01dcc..88cbca9be 100644
--- a/Math/Math/NoGPU.cpp
+++ b/Math/Math/NoGPU.cpp
@@ -1037,7 +1037,24 @@ namespace Microsoft {
             {
                 return ElemType(0);
             }
+            template<class ElemType>
+            void GPUMatrix<ElemType>::AssignNoiseContrastiveEstimation(const GPUMatrix<ElemType>& a,
+                const GPUMatrix<ElemType>& b, size_t sampleCount, GPUMatrix<ElemType>& tmp, GPUMatrix<ElemType>& c)
+            {
+            }
 
+            template<class ElemType>
+            void GPUMatrix<ElemType>::AssignNCEDerivative(GPUMatrix<ElemType>& tmp, const GPUMatrix<ElemType>& a,
+                const GPUMatrix<ElemType>& b, size_t inputIndex, GPUMatrix<ElemType>& c)
+            {
+
+            }
+
+
+            template<class ElemType>
+            void GPUMatrix<ElemType>::AssignNCEUnnormalizedEval(const GPUMatrix<ElemType>& a, const GPUMatrix<ElemType>& b, GPUMatrix<ElemType>& c)
+            {              
+            }
 #pragma endregion Static BLAS Functions
 
             template class GPUMatrix<float>;

From c6865da977cdd070fb301b82d5a0f638c01468e1 Mon Sep 17 00:00:00 2001
From: Yinggong ZHAO <yinggong.zhao@gmail.com>
Date: Mon, 18 May 2015 05:39:44 -0700
Subject: [PATCH 25/49] config file for NCE-LSTM

---
 ExampleSetups/LM/LSTMLM/lstmlm.gpu.nce.config | 432 ++++++++++++++++++
 1 file changed, 432 insertions(+)
 create mode 100644 ExampleSetups/LM/LSTMLM/lstmlm.gpu.nce.config

diff --git a/ExampleSetups/LM/LSTMLM/lstmlm.gpu.nce.config b/ExampleSetups/LM/LSTMLM/lstmlm.gpu.nce.config
new file mode 100644
index 000000000..21ac5fa62
--- /dev/null
+++ b/ExampleSetups/LM/LSTMLM/lstmlm.gpu.nce.config
@@ -0,0 +1,432 @@
+# configuration file for class based RNN training
+
+ExpFolder=$ExpDir$
+ConfigFolder=$ConfigDir$
+DataFolder=$DataDir$
+
+stderr=$ExpFolder$
+numCPUThreads=4
+# command=dumpNodeInfo
+#command=train
+#command=test
+command=writeWordAndClassInfo:train:test
+command=train:test
+type=double
+
+DEVICEID=-1
+
+NOISE=100
+RATE=0.06
+VOCABSIZE=10000
+CLASSSIZE=50
+makeMode=true
+TRAINFILE=ptb.train.cntk.txt
+VALIDFILE=ptb.valid.cntk.txt
+TESTFILE=ptb.test.cntk.txt
+
+#number of threads
+nthreads=4
+
+writeWordAndClassInfo=[
+    action=writeWordAndClass
+    inputFile=$DataFolder$\$TRAINFILE$
+	outputVocabFile=$DataFolder$\vocab.txt
+    outputWord2Cls=$ExpFolder$\word2cls.txt
+    outputCls2Index=$ExpFolder$\cls2idx.txt
+    vocabSize=$VOCABSIZE$
+	cutoff=0
+    printValues=true
+]
+
+dumpNodeInfo=[
+    action=dumpnode
+    modelPath=$ExpFolder$\modelRnnCNTK
+    #nodeName=W0
+    printValues=true
+]
+
+devtest=[action=devtest]
+
+train=[
+    action=train
+    minibatchSize=10
+    traceLevel=1
+    deviceId=$DEVICEID$
+    epochSize=4430000
+    # which is 886 * 5000
+    recurrentLayer=1
+    defaultHiddenActivity=0.1
+    useValidation=true
+    rnnType=NCELSTM 
+	#CLASSLSTM
+
+    # uncomment below and comment SimpleNetworkBuilder section to use NDL to train RNN LM
+    # NDLNetworkBuilder=[
+    #    networkDescription=$ConfigFolder$\rnnlm.ndl
+    # ]
+
+    SimpleNetworkBuilder=[
+        trainingCriterion=NoiseContrastiveEstimationNode
+        evalCriterion=NoiseContrastiveEstimationNode
+        nodeType=Sigmoid
+        initValueScale=6.0
+        layerSizes=$VOCABSIZE$:200:$VOCABSIZE$
+        addPrior=false
+        addDropoutNodes=false
+        applyMeanVarNorm=false
+        uniformInit=true;
+
+        # these are for the class information for class-based language modeling
+        vocabSize=$VOCABSIZE$
+        #nbrClass=$CLASSSIZE$
+		noise_number=$NOISE$
+    ]
+
+    # configuration file, base parameters
+    SGD=[
+	    makeMode=true
+        learningRatesPerSample=$RATE$
+        momentumPerMB=0
+        gradientClippingWithTruncation=true
+        clippingThresholdPerSample=15.0
+        maxEpochs=40
+        unroll=false
+        numMBsToShowResult=2000
+        # gradUpdateType=AdaGrad
+        gradUpdateType=None
+      
+        modelPath=$ExpFolder$\modelRnnCNTK
+        loadBestModel=true
+
+        # settings for Auto Adjust Learning Rate
+        AutoAdjust=[
+            # auto learning rate adjustment
+            autoAdjustLR=adjustafterepoch
+            reduceLearnRateIfImproveLessThan=0.001
+            continueReduce=false
+            increaseLearnRateIfImproveMoreThan=1000000000
+            learnRateDecreaseFactor=0.5
+            learnRateIncreaseFactor=1.382
+            numMiniBatch4LRSearch=100
+            numPrevLearnRates=5
+            numBestSearchEpoch=1
+        ]
+
+        dropoutRate=0.0
+    ]
+
+    reader=[
+      readerType=LMSequenceReader
+      randomize=None
+      nbruttsineachrecurrentiter=10
+
+      # word class info
+      wordclass=$DataFolder$\vocab.txt
+      noise_number=$NOISE$
+	  mode=nce
+      # if writerType is set, we will cache to a binary file
+      # if the binary file exists, we will use it instead of parsing this file
+      # writerType=BinaryReader
+
+      #### write definition
+      wfile=$ExpFolder$\sequenceSentence.bin
+      #wsize - inital size of the file in MB
+      # if calculated size would be bigger, that is used instead
+      wsize=256
+
+      #wrecords - number of records we should allocate space for in the file
+      # files cannot be expanded, so this should be large enough. If known modify this element in config before creating file
+      wrecords=1000
+      #windowSize - number of records we should include in BinaryWriter window
+      windowSize=$VOCABSIZE$
+
+      file=$DataFolder$\$TRAINFILE$
+
+      #additional features sections
+      #for now store as expanded category data (including label in)
+      features=[
+        # sentence has no features, so need to set dimension to zero
+        dim=0
+        ### write definition
+        sectionType=data
+      ]
+      # sequence break table, list indexes into sequence records, so we know when a sequence starts/stops
+      sequence=[
+        dim=1
+        wrecords=2
+        ### write definition
+        sectionType=data
+      ]
+      #labels sections
+      labelIn=[
+        dim=1
+        # vocabulary size
+        labelDim=$VOCABSIZE$
+        labelMappingFile=$ExpFolder$\sentenceLabels.txt
+        labelType=Category
+        beginSequence="</s>"
+        endSequence="</s>"
+
+        #### Write definition ####
+        # sizeof(unsigned) which is the label index type
+        elementSize=4
+        sectionType=labels
+        mapping=[
+          #redefine number of records for this section, since we don't need to save it for each data record
+          wrecords=11
+          #variable size so use an average string size
+          elementSize=10
+          sectionType=labelMapping
+        ]
+        category=[
+          dim=11
+          #elementSize=sizeof(ElemType) is default
+          sectionType=categoryLabels
+        ]
+      ]
+      #labels sections
+      labels=[
+        dim=1
+        labelType=NextWord
+        beginSequence="O"
+        endSequence="O"
+
+        # vocabulary size
+        labelDim=$VOCABSIZE$
+
+        labelMappingFile=$ExpFolder$\sentenceLabels.out.txt
+        #### Write definition ####
+        # sizeof(unsigned) which is the label index type
+        elementSize=4
+        sectionType=labels
+        mapping=[
+          #redefine number of records for this section, since we don't need to save it for each data record
+          wrecords=3
+          #variable size so use an average string size
+          elementSize=10
+          sectionType=labelMapping
+        ]
+        category=[
+          dim=3
+          #elementSize=sizeof(ElemType) is default
+          sectionType=categoryLabels
+        ]
+      ]
+    ]
+
+    cvReader=[
+      # reader to use
+      readerType=LMSequenceReader
+      randomize=None
+      mode=softmax
+      # word class info
+      wordclass=$DataFolder$\vocab.txt
+
+      # if writerType is set, we will cache to a binary file
+      # if the binary file exists, we will use it instead of parsing this file
+      # writerType=BinaryReader
+
+      #### write definition
+      wfile=$ExpFolder$\sequenceSentence.valid.bin
+      #wsize - inital size of the file in MB
+      # if calculated size would be bigger, that is used instead
+      wsize=256
+
+      #wrecords - number of records we should allocate space for in the file
+      # files cannot be expanded, so this should be large enough. If known modify this element in config before creating file
+      wrecords=1000
+      #windowSize - number of records we should include in BinaryWriter window
+      windowSize=$VOCABSIZE$
+
+      file=$DataFolder$\$VALIDFILE$
+
+      #additional features sections
+      #for now store as expanded category data (including label in)
+      features=[
+        # sentence has no features, so need to set dimension to zero
+        dim=0
+        ### write definition
+        sectionType=data
+      ]
+      # sequence break table, list indexes into sequence records, so we know when a sequence starts/stops
+      sequence=[
+        dim=1
+        wrecords=2
+        ### write definition
+        sectionType=data
+      ]
+      #labels sections
+      # it should be the same as that in the training set
+      labelIn=[
+        dim=1
+
+        # vocabulary size
+        labelDim=$VOCABSIZE$
+        labelMappingFile=$ExpFolder$\sentenceLabels.out.txt
+        labelType=Category
+        beginSequence="</s>"
+        endSequence="</s>"
+
+        #### Write definition ####
+        # sizeof(unsigned) which is the label index type
+        elementSize=4
+        sectionType=labels
+        mapping=[
+          #redefine number of records for this section, since we don't need to save it for each data record
+          wrecords=11
+          #variable size so use an average string size
+          elementSize=10
+          sectionType=labelMapping
+        ]
+        category=[
+          dim=11
+          #elementSize=sizeof(ElemType) is default
+          sectionType=categoryLabels
+        ]
+      ]
+      #labels sections
+      labels=[
+        dim=1
+        labelType=NextWord
+        beginSequence="O"
+        endSequence="O"
+
+        labelDim=$VOCABSIZE$
+        labelMappingFile=$ExpFolder$\sentenceLabels.out.txt
+        #### Write definition ####
+        # sizeof(unsigned) which is the label index type
+        elementSize=4
+        sectionType=labels
+        mapping=[
+          #redefine number of records for this section, since we don't need to save it for each data record
+          wrecords=3
+          #variable size so use an average string size
+          elementSize=10
+          sectionType=labelMapping
+        ]
+        category=[
+          dim=3
+          #elementSize=sizeof(ElemType) is default
+          sectionType=categoryLabels
+        ]
+      ]
+    ]
+]
+
+
+test=[
+    action=eval
+
+    # correspond to the number of words/characteres to train in a minibatch
+    minibatchSize=1
+    # need to be small since models are updated for each minibatch
+    traceLevel=1
+    deviceId=$DEVICEID$
+    epochSize=4430000
+    # which is 886 * 5000
+    recurrentLayer=1
+    defaultHiddenActivity=0.1
+    useValidation=true
+    rnnType=NCELSTM
+
+    modelPath=$ExpFolder$\modelRnnCNTK
+
+    reader=[
+      # reader to use
+      readerType=LMSequenceReader
+      randomize=None
+      mode=softmax
+      # word class info
+      wordclass=$DataFolder$\vocab.txt
+
+      # if writerType is set, we will cache to a binary file
+      # if the binary file exists, we will use it instead of parsing this file
+      # writerType=BinaryReader
+
+      #### write definition
+      wfile=$ExpFolder$\sequenceSentence.bin
+      #wsize - inital size of the file in MB
+      # if calculated size would be bigger, that is used instead
+      wsize=256
+
+      # wrecords - number of records we should allocate space for in the file
+      # files cannot be expanded, so this should be large enough. If known modify this element in config before creating file
+      wrecords=1000
+      # windowSize - number of records we should include in BinaryWriter window
+      windowSize=$VOCABSIZE$
+
+      file=$DataFolder$\$TESTFILE$
+
+      #additional features sections
+      #for now store as expanded category data (including label in)
+      features=[
+        # sentence has no features, so need to set dimension to zero
+        dim=0
+        ### write definition
+        sectionType=data
+      ]
+      # sequence break table, list indexes into sequence records, so we know when a sequence starts/stops
+      sequence=[
+        dim=1
+        wrecords=2
+        ### write definition
+        sectionType=data
+      ]
+      #labels sections
+      labelIn=[
+        dim=1
+
+        # vocabulary size
+        labelDim=$VOCABSIZE$
+        labelMappingFile=$ExpFolder$\sentenceLabels.txt
+        labelType=Category
+        beginSequence="</s>"
+        endSequence="</s>"
+
+        #### Write definition ####
+        # sizeof(unsigned) which is the label index type
+        elementSize=4
+        sectionType=labels
+        mapping=[
+          #redefine number of records for this section, since we don't need to save it for each data record
+          wrecords=11
+          #variable size so use an average string size
+          elementSize=10
+          sectionType=labelMapping
+        ]
+        category=[
+          dim=11
+          #elementSize=sizeof(ElemType) is default
+          sectionType=categoryLabels
+        ]
+      ]
+      #labels sections
+      labels=[
+        dim=1
+        labelType=NextWord
+        beginSequence="O"
+        endSequence="O"
+
+        # vocabulary size
+        labelDim=$VOCABSIZE$
+
+        labelMappingFile=$ExpFolder$\sentenceLabels.out.txt
+        #### Write definition ####
+        # sizeof(unsigned) which is the label index type
+        elementSize=4
+        sectionType=labels
+        mapping=[
+          #redefine number of records for this section, since we don't need to save it for each data record
+          wrecords=3
+          #variable size so use an average string size
+          elementSize=10
+          sectionType=labelMapping
+        ]
+        category=[
+          dim=3
+          #elementSize=sizeof(ElemType) is default
+          sectionType=categoryLabels
+        ]
+      ]
+    ]
+]
\ No newline at end of file

From 392d64da08172dddc4969d99e5f2767dd8d578ed Mon Sep 17 00:00:00 2001
From: Frank Seide <fseide@microsoft.com>
Date: Mon, 18 May 2015 18:51:20 -0700
Subject: [PATCH 26/49] various cleanups: renamed cn.exe to CNTK.exe on Windows
 and "cntk" (no more .exe!) on Linux; renamed 'cn' folder to 'CNTK'; moved
 CNTK.sln out from CNTKSolution folder, which now no longer needs to exist;
 removed Win32 build target from Visual Studio Solution and all Projects;
 added are documentation and Linux makefiles to the Visual Studio Solution for
 easy access; removed unused PTasks files

---
 CNTK.sln                                      | 267 +++++++++++++++
 CNTKSolution/CNTKSolution.sln                 | 154 ---------
 Common/BestGpu.cpp                            |  10 +-
 Common/{Include => trash}/nvml.h              |   0
 DataReader/BinaryReader/BinaryReader.vcxproj  |  83 +----
 DataReader/DSSMReader/DSSMReader.vcxproj      |  79 +----
 DataReader/HTKMLFReader/HTKMLFReader.vcxproj  |  80 +----
 .../LMSequenceReader/LMSequenceReader.vcxproj | 304 +++++++++---------
 .../LUSequenceReader/LUSequenceReader.vcxproj |   2 +
 .../LibSVMBinaryReader.vcxproj                |  85 +----
 .../UCIFastReader/UCIFastReader.vcxproj       |  82 +----
 Documentation/Documentation.vcxproj           | 117 +++++++
 Documentation/Documentation.vcxproj.filters   | 159 +++++++++
 .../{ => Documents}/Configuration Files.docx  | Bin
 .../External Buffer Behavior.docx             | Bin
 .../Model Editing Language.docx               | Bin
 .../Network Description Language.docx         | Bin
 .../CNTK-Tutorial-ICASSP2015.pdf              | Bin
 Linux/Linux.vcxproj                           |  76 +++++
 Linux/Linux.vcxproj.filters                   |  10 +
 MachineLearning/{cn/cn.cpp => CNTK/CNTK.cpp}  |   0
 .../{cn/cn.vcxproj => CNTK/CNTK.vcxproj}      | 106 ++----
 .../CNTK.vcxproj.filters}                     |  16 +-
 .../CNTK.vcxproj.vspscc}                      |   0
 .../{cn => CNTK}/CompositeComputationNode.h   |   0
 .../{cn => CNTK}/ComputationNetwork.cpp       |   0
 .../{cn => CNTK}/ComputationNetwork.h         |   0
 .../{cn => CNTK}/ComputationNetworkHelper.h   |   0
 .../{cn => CNTK}/ComputationNode.cpp          |   0
 .../{cn => CNTK}/ComputationNode.h            |   0
 .../{cn => CNTK}/DefaultMacros.txt            |   0
 .../{cn => CNTK}/EvaluationCriterionNode.h    |   0
 .../{cn => CNTK}/FullNetworkBuilder.h         |   0
 .../{cn => CNTK}/IComputationNetBuilder.h     |   0
 .../{cn => CNTK}/IExecutionEngine.h           |   0
 .../{cn => CNTK}/ModelEditLanguage.cpp        |   0
 .../{cn => CNTK}/ModelEditLanguage.h          |   0
 .../{cn => CNTK}/NDLNetworkBuilder.h          |   0
 MachineLearning/{cn => CNTK}/NDLUtil.h        |   0
 MachineLearning/{cn => CNTK}/NdlScript.txt    |   0
 .../NetworkDescriptionLanguage.cpp            |   0
 .../{cn => CNTK}/NetworkDescriptionLanguage.h |   0
 MachineLearning/{cn => CNTK}/PTask.cpp        |   0
 MachineLearning/{cn => CNTK}/PTask.h          |   0
 .../{cn => CNTK}/PTaskComputationNetwork.h    |   0
 .../{cn => CNTK}/PTaskExecutionEngine.h       |   0
 .../{cn => CNTK}/PTaskGraphBuilder.cpp        |   0
 .../{cn => CNTK}/PTaskGraphBuilder.h          |   0
 .../{cn => CNTK}/RecurrentNetworkBuilder.h    |   0
 MachineLearning/{cn => CNTK}/SGD.h            |   0
 .../{cn => CNTK}/SimpleEvaluator.h            |   0
 .../{cn => CNTK}/SimpleNetworkBuilder.cpp     |   0
 .../{cn => CNTK}/SimpleNetworkBuilder.h       |   0
 .../{cn => CNTK}/SimpleOutputWriter.h         |   0
 .../SimpleRecurrentNetEvaluator.h             |   0
 .../{cn => CNTK}/SynchronousExecutionEngine.h |   0
 .../{cn => CNTK}/TrainingCriterionNode.h      |   0
 MachineLearning/{cn => CNTK}/fileutil.cpp     |   0
 MachineLearning/{cn => CNTK}/modelEditor.txt  |   0
 .../{cn => CNTK}/modelEditorFromScratch.txt   |   0
 MachineLearning/{cn => CNTK}/prebuild.bat     |   0
 MachineLearning/{cn => CNTK}/stdafx.cpp       |   0
 MachineLearning/{cn => CNTK}/stdafx.h         |   0
 MachineLearning/{cn => CNTK}/targetver.h      |   0
 MachineLearning/{cn => CNTK}/tests.cpp        |   0
 MachineLearning/CNTKEval/CNTKEval.vcxproj     |  37 ++-
 .../CNTKEval/CNTKEval.vcxproj.filters         |   2 +-
 .../CNTKEvalTest/CNTKEvalTest.vcxproj         |  67 +---
 MachineLearning/PTaskHost/PTaskHost.cpp       |  59 ----
 MachineLearning/PTaskHost/PTaskHost.h         |  31 --
 MachineLearning/PTaskHost/PTaskHost.vcxproj   | 174 ----------
 MachineLearning/PTaskHost/dllmain.cpp         |  19 --
 MachineLearning/PTaskHost/stdafx.cpp          |   8 -
 MachineLearning/PTaskHost/stdafx.h            |  16 -
 MachineLearning/PTaskHost/targetver.h         |   8 -
 Makefile.cpu                                  |  14 +-
 Makefile.gpu                                  |  12 +-
 Makefile_kaldi.cpu                            |  14 +-
 Makefile_kaldi.gpu                            |  12 +-
 Math/CNTKMathTest/CNTKMathTest.vcxproj        |  73 +----
 Math/Math.sln                                 |  75 -----
 Math/Math.vssscc                              |  10 -
 Math/Math/CNTKMathCUDA.vcxproj                |   4 +-
 Math/Math/Math.vcxproj                        |   8 +-
 .../MathPerformanceTests.vcxproj              |  68 +---
 README                                        |   2 +
 86 files changed, 894 insertions(+), 1449 deletions(-)
 create mode 100644 CNTK.sln
 delete mode 100644 CNTKSolution/CNTKSolution.sln
 rename Common/{Include => trash}/nvml.h (100%)
 create mode 100644 Documentation/Documentation.vcxproj
 create mode 100644 Documentation/Documentation.vcxproj.filters
 rename Documentation/{ => Documents}/Configuration Files.docx (100%)
 rename Documentation/{ => Documents}/External Buffer Behavior.docx (100%)
 rename Documentation/{ => Documents}/Model Editing Language.docx (100%)
 rename Documentation/{ => Documents}/Network Description Language.docx (100%)
 rename Documentation/{ => Tutorial}/CNTK-Tutorial-ICASSP2015.pdf (100%)
 create mode 100644 Linux/Linux.vcxproj
 create mode 100644 Linux/Linux.vcxproj.filters
 rename MachineLearning/{cn/cn.cpp => CNTK/CNTK.cpp} (100%)
 rename MachineLearning/{cn/cn.vcxproj => CNTK/CNTK.vcxproj} (61%)
 rename MachineLearning/{cn/cn.vcxproj.filters => CNTK/CNTK.vcxproj.filters} (92%)
 rename MachineLearning/{cn/cn.vcxproj.vspscc => CNTK/CNTK.vcxproj.vspscc} (100%)
 rename MachineLearning/{cn => CNTK}/CompositeComputationNode.h (100%)
 rename MachineLearning/{cn => CNTK}/ComputationNetwork.cpp (100%)
 rename MachineLearning/{cn => CNTK}/ComputationNetwork.h (100%)
 rename MachineLearning/{cn => CNTK}/ComputationNetworkHelper.h (100%)
 rename MachineLearning/{cn => CNTK}/ComputationNode.cpp (100%)
 rename MachineLearning/{cn => CNTK}/ComputationNode.h (100%)
 rename MachineLearning/{cn => CNTK}/DefaultMacros.txt (100%)
 rename MachineLearning/{cn => CNTK}/EvaluationCriterionNode.h (100%)
 rename MachineLearning/{cn => CNTK}/FullNetworkBuilder.h (100%)
 rename MachineLearning/{cn => CNTK}/IComputationNetBuilder.h (100%)
 rename MachineLearning/{cn => CNTK}/IExecutionEngine.h (100%)
 rename MachineLearning/{cn => CNTK}/ModelEditLanguage.cpp (100%)
 rename MachineLearning/{cn => CNTK}/ModelEditLanguage.h (100%)
 rename MachineLearning/{cn => CNTK}/NDLNetworkBuilder.h (100%)
 rename MachineLearning/{cn => CNTK}/NDLUtil.h (100%)
 rename MachineLearning/{cn => CNTK}/NdlScript.txt (100%)
 rename MachineLearning/{cn => CNTK}/NetworkDescriptionLanguage.cpp (100%)
 rename MachineLearning/{cn => CNTK}/NetworkDescriptionLanguage.h (100%)
 rename MachineLearning/{cn => CNTK}/PTask.cpp (100%)
 rename MachineLearning/{cn => CNTK}/PTask.h (100%)
 rename MachineLearning/{cn => CNTK}/PTaskComputationNetwork.h (100%)
 rename MachineLearning/{cn => CNTK}/PTaskExecutionEngine.h (100%)
 rename MachineLearning/{cn => CNTK}/PTaskGraphBuilder.cpp (100%)
 rename MachineLearning/{cn => CNTK}/PTaskGraphBuilder.h (100%)
 rename MachineLearning/{cn => CNTK}/RecurrentNetworkBuilder.h (100%)
 rename MachineLearning/{cn => CNTK}/SGD.h (100%)
 rename MachineLearning/{cn => CNTK}/SimpleEvaluator.h (100%)
 rename MachineLearning/{cn => CNTK}/SimpleNetworkBuilder.cpp (100%)
 rename MachineLearning/{cn => CNTK}/SimpleNetworkBuilder.h (100%)
 rename MachineLearning/{cn => CNTK}/SimpleOutputWriter.h (100%)
 rename MachineLearning/{cn => CNTK}/SimpleRecurrentNetEvaluator.h (100%)
 rename MachineLearning/{cn => CNTK}/SynchronousExecutionEngine.h (100%)
 rename MachineLearning/{cn => CNTK}/TrainingCriterionNode.h (100%)
 rename MachineLearning/{cn => CNTK}/fileutil.cpp (100%)
 rename MachineLearning/{cn => CNTK}/modelEditor.txt (100%)
 rename MachineLearning/{cn => CNTK}/modelEditorFromScratch.txt (100%)
 rename MachineLearning/{cn => CNTK}/prebuild.bat (100%)
 rename MachineLearning/{cn => CNTK}/stdafx.cpp (100%)
 rename MachineLearning/{cn => CNTK}/stdafx.h (100%)
 rename MachineLearning/{cn => CNTK}/targetver.h (100%)
 rename MachineLearning/{cn => CNTK}/tests.cpp (100%)
 delete mode 100644 MachineLearning/PTaskHost/PTaskHost.cpp
 delete mode 100644 MachineLearning/PTaskHost/PTaskHost.h
 delete mode 100644 MachineLearning/PTaskHost/PTaskHost.vcxproj
 delete mode 100644 MachineLearning/PTaskHost/dllmain.cpp
 delete mode 100644 MachineLearning/PTaskHost/stdafx.cpp
 delete mode 100644 MachineLearning/PTaskHost/stdafx.h
 delete mode 100644 MachineLearning/PTaskHost/targetver.h
 delete mode 100644 Math/Math.sln
 delete mode 100644 Math/Math.vssscc

diff --git a/CNTK.sln b/CNTK.sln
new file mode 100644
index 000000000..3cd282cb6
--- /dev/null
+++ b/CNTK.sln
@@ -0,0 +1,267 @@
+
+Microsoft Visual Studio Solution File, Format Version 12.00
+# Visual Studio 2013
+VisualStudioVersion = 12.0.21005.1
+MinimumVisualStudioVersion = 10.0.40219.1
+Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "CNTKMath", "Math\Math\Math.vcxproj", "{60BDB847-D0C4-4FD3-A947-0C15C08BCDB5}"
+	ProjectSection(ProjectDependencies) = postProject
+		{B3DD765E-694E-4494-BAD7-37BBF2942517} = {B3DD765E-694E-4494-BAD7-37BBF2942517}
+	EndProjectSection
+EndProject
+Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "CNTK", "MachineLearning\CNTK\CNTK.vcxproj", "{E6F26F9A-FF64-4F0A-B749-CD309EE357EE}"
+	ProjectSection(ProjectDependencies) = postProject
+		{33D2FD22-DEF2-4507-A58A-368F641AEBE5} = {33D2FD22-DEF2-4507-A58A-368F641AEBE5}
+		{9A2F2441-5972-4EA8-9215-4119FCE0FB68} = {9A2F2441-5972-4EA8-9215-4119FCE0FB68}
+		{60BDB847-D0C4-4FD3-A947-0C15C08BCDB5} = {60BDB847-D0C4-4FD3-A947-0C15C08BCDB5}
+		{B3DD765E-694E-4494-BAD7-37BBF2942517} = {B3DD765E-694E-4494-BAD7-37BBF2942517}
+		{62836DC1-DF77-4B98-BF2D-45C943B7DDC6} = {62836DC1-DF77-4B98-BF2D-45C943B7DDC6}
+		{1D5787D4-52E4-45DB-951B-82F220EE0C6A} = {1D5787D4-52E4-45DB-951B-82F220EE0C6A}
+		{E6646FFE-3588-4276-8A15-8D65C22711C1} = {E6646FFE-3588-4276-8A15-8D65C22711C1}
+	EndProjectSection
+EndProject
+Project("{2150E333-8FDC-42A3-9474-1A3956D46DE8}") = "Unit Tests", "Unit Tests", "{D45DF403-6781-444E-B654-A96868C5BE68}"
+EndProject
+Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "CNTKMathTest", "Math\CNTKMathTest\CNTKMathTest.vcxproj", "{6CEE834A-8104-46A8-8902-64C81BD7928F}"
+EndProject
+Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "HTKMLFReader", "DataReader\HTKMLFReader\HTKMLFReader.vcxproj", "{33D2FD22-DEF2-4507-A58A-368F641AEBE5}"
+	ProjectSection(ProjectDependencies) = postProject
+		{60BDB847-D0C4-4FD3-A947-0C15C08BCDB5} = {60BDB847-D0C4-4FD3-A947-0C15C08BCDB5}
+	EndProjectSection
+EndProject
+Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "MathPerformanceTests", "Math\MathPerformanceTests\MathPerformanceTests.vcxproj", "{668BEED5-AC07-4F35-B3AE-EE65A7F9C976}"
+EndProject
+Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "UCIFastReader", "DataReader\UCIFastReader\UCIFastReader.vcxproj", "{E6646FFE-3588-4276-8A15-8D65C22711C1}"
+	ProjectSection(ProjectDependencies) = postProject
+		{60BDB847-D0C4-4FD3-A947-0C15C08BCDB5} = {60BDB847-D0C4-4FD3-A947-0C15C08BCDB5}
+		{1D5787D4-52E4-45DB-951B-82F220EE0C6A} = {1D5787D4-52E4-45DB-951B-82F220EE0C6A}
+	EndProjectSection
+EndProject
+Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "BinaryReader", "DataReader\BinaryReader\BinaryReader.vcxproj", "{1D5787D4-52E4-45DB-951B-82F220EE0C6A}"
+	ProjectSection(ProjectDependencies) = postProject
+		{60BDB847-D0C4-4FD3-A947-0C15C08BCDB5} = {60BDB847-D0C4-4FD3-A947-0C15C08BCDB5}
+	EndProjectSection
+EndProject
+Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "LUSequenceReader", "DataReader\LUSequenceReader\LUSequenceReader.vcxproj", "{62836DC1-DF77-4B98-BF2D-45C943B7DDC6}"
+	ProjectSection(ProjectDependencies) = postProject
+		{60BDB847-D0C4-4FD3-A947-0C15C08BCDB5} = {60BDB847-D0C4-4FD3-A947-0C15C08BCDB5}
+	EndProjectSection
+EndProject
+Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "CNTKEval", "MachineLearning\CNTKEval\CNTKEval.vcxproj", "{482999D1-B7E2-466E-9F8D-2119F93EAFD9}"
+	ProjectSection(ProjectDependencies) = postProject
+		{60BDB847-D0C4-4FD3-A947-0C15C08BCDB5} = {60BDB847-D0C4-4FD3-A947-0C15C08BCDB5}
+	EndProjectSection
+EndProject
+Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "CNTKEvalTest", "MachineLearning\CNTKEval\CNTKEvalTest\CNTKEvalTest.vcxproj", "{0F30EBCF-09F3-4EED-BF54-4214BCE53FEC}"
+	ProjectSection(ProjectDependencies) = postProject
+		{60BDB847-D0C4-4FD3-A947-0C15C08BCDB5} = {60BDB847-D0C4-4FD3-A947-0C15C08BCDB5}
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+		{B3DD765E-694E-4494-BAD7-37BBF2942517} = {DD043083-71A4-409A-AA91-F9C548DCF7EC}
+		{E7AD9034-C010-4FC7-9768-E7EE4EE94FFF} = {DD043083-71A4-409A-AA91-F9C548DCF7EC}
+		{6CEE834A-8104-46A8-8902-64C81BD7928F} = {D45DF403-6781-444E-B654-A96868C5BE68}
+		{668BEED5-AC07-4F35-B3AE-EE65A7F9C976} = {D45DF403-6781-444E-B654-A96868C5BE68}
+		{0F30EBCF-09F3-4EED-BF54-4214BCE53FEC} = {D45DF403-6781-444E-B654-A96868C5BE68}
+		{E6646FFE-3588-4276-8A15-8D65C22711C1} = {33EBFE78-A1A8-4961-8938-92A271941F94}
+		{1D5787D4-52E4-45DB-951B-82F220EE0C6A} = {33EBFE78-A1A8-4961-8938-92A271941F94}
+		{62836DC1-DF77-4B98-BF2D-45C943B7DDC6} = {33EBFE78-A1A8-4961-8938-92A271941F94}
+		{33D2FD22-DEF2-4507-A58A-368F641AEBE5} = {33EBFE78-A1A8-4961-8938-92A271941F94}
+		{9A2F2441-5972-4EA8-9215-4119FCE0FB68} = {33EBFE78-A1A8-4961-8938-92A271941F94}
+		{014DA766-B37B-4581-BC26-963EA5507931} = {33EBFE78-A1A8-4961-8938-92A271941F94}
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+	EndGlobalSection
+EndGlobal
diff --git a/CNTKSolution/CNTKSolution.sln b/CNTKSolution/CNTKSolution.sln
deleted file mode 100644
index 2fb8b01a1..000000000
--- a/CNTKSolution/CNTKSolution.sln
+++ /dev/null
@@ -1,154 +0,0 @@
-
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-# Visual Studio 2013
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-	ProjectSection(ProjectDependencies) = postProject
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-	ProjectSection(ProjectDependencies) = postProject
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-	ProjectSection(ProjectDependencies) = postProject
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-	ProjectSection(ProjectDependencies) = postProject
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-	EndProjectSection
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-	ProjectSection(ProjectDependencies) = postProject
-		{60BDB847-D0C4-4FD3-A947-0C15C08BCDB5} = {60BDB847-D0C4-4FD3-A947-0C15C08BCDB5}
-		{482999D1-B7E2-466E-9F8D-2119F93EAFD9} = {482999D1-B7E2-466E-9F8D-2119F93EAFD9}
-	EndProjectSection
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-Project("{2150E333-8FDC-42A3-9474-1A3956D46DE8}") = "Reader Plugins", "Reader Plugins", "{33EBFE78-A1A8-4961-8938-92A271941F94}"
-EndProject
-Project("{2150E333-8FDC-42A3-9474-1A3956D46DE8}") = "CNTK", "CNTK", "{DD043083-71A4-409A-AA91-F9C548DCF7EC}"
-EndProject
-Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "CNTKMathCUDA", "..\Math\Math\CNTKMathCUDA.vcxproj", "{B3DD765E-694E-4494-BAD7-37BBF2942517}"
-EndProject
-Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "LMSequenceReader", "..\DataReader\LMSequenceReader\LMSequenceReader.vcxproj", "{9A2F2441-5972-4EA8-9215-4119FCE0FB68}"
-	ProjectSection(ProjectDependencies) = postProject
-		{60BDB847-D0C4-4FD3-A947-0C15C08BCDB5} = {60BDB847-D0C4-4FD3-A947-0C15C08BCDB5}
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-EndProject
-Global
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-	EndGlobalSection
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-		{0F30EBCF-09F3-4EED-BF54-4214BCE53FEC} = {D45DF403-6781-444E-B654-A96868C5BE68}
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-		{33D2FD22-DEF2-4507-A58A-368F641AEBE5} = {33EBFE78-A1A8-4961-8938-92A271941F94}
-		{9A2F2441-5972-4EA8-9215-4119FCE0FB68} = {33EBFE78-A1A8-4961-8938-92A271941F94}
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diff --git a/Common/BestGpu.cpp b/Common/BestGpu.cpp
index cc3676d5f..286dd75e5 100644
--- a/Common/BestGpu.cpp
+++ b/Common/BestGpu.cpp
@@ -4,15 +4,21 @@
 // </copyright>
 //
 
+// This file requires the NVML library. Unfortunately, this library does not install an environment variable for locating it.
+// On Windows, the SDK gets installed to "c:\Program Files\NVIDIA Corporation\GDK\gdk_win7_amd64_release\nvml" (/include, /lib).
+// From the SDK documentation:
+// "The NVML library can be found at: %ProgramW6432%\"NVIDIA Corporation"\NVSMI\ on Windows, but will not be added to the path. To dynamically link to NVML, add this path to the PATH environmental variable. To dynamically load NVML, call LoadLibrary with this path."
+// "On Linux the NVML library will be found on the standard library path. For 64-bit Linux, both the 32-bit and 64-bit NVML libraries will be installed."
+
 #define _CRT_SECURE_NO_WARNINGS // "secure" CRT not available on all platforms  --add this at the top of all CPP files that give "function or variable may be unsafe" warnings
 #include "Platform.h"
 #include "BestGpu.h"
 #include "commandArgUtil.h" // for ConfigParameters
 #ifndef CPUONLY
 #pragma comment (lib, "cudart.lib")
-#pragma comment (lib, "nvml.lib")
 #include <cuda_runtime.h>
-#include <nvml.h>
+#include <nvml.h>                   // note: expected at "c:\Program Files\NVIDIA Corporation\GDK\gdk_win7_amd64_release\nvml\include" (Windows)
+#pragma comment (lib, "nvml.lib")   // note: expected at "c:\Program Files\NVIDIA Corporation\GDK\gdk_win7_amd64_release\nvml\lib" (Windows)
 #include <vector>
 #endif
 #include "CommonMatrix.h" // for CPUDEVICE and AUTOPLACEMATRIX
diff --git a/Common/Include/nvml.h b/Common/trash/nvml.h
similarity index 100%
rename from Common/Include/nvml.h
rename to Common/trash/nvml.h
diff --git a/DataReader/BinaryReader/BinaryReader.vcxproj b/DataReader/BinaryReader/BinaryReader.vcxproj
index 40f1aa78f..626ee37b3 100644
--- a/DataReader/BinaryReader/BinaryReader.vcxproj
+++ b/DataReader/BinaryReader/BinaryReader.vcxproj
@@ -1,18 +1,10 @@
 <?xml version="1.0" encoding="utf-8"?>
 <Project DefaultTargets="Build" ToolsVersion="12.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
   <ItemGroup Label="ProjectConfigurations">
-    <ProjectConfiguration Include="Debug|Win32">
-      <Configuration>Debug</Configuration>
-      <Platform>Win32</Platform>
-    </ProjectConfiguration>
     <ProjectConfiguration Include="Debug|x64">
       <Configuration>Debug</Configuration>
       <Platform>x64</Platform>
     </ProjectConfiguration>
-    <ProjectConfiguration Include="Release|Win32">
-      <Configuration>Release</Configuration>
-      <Platform>Win32</Platform>
-    </ProjectConfiguration>
     <ProjectConfiguration Include="Release|x64">
       <Configuration>Release</Configuration>
       <Platform>x64</Platform>
@@ -32,25 +24,12 @@
     <RootNamespace>UCIReader</RootNamespace>
   </PropertyGroup>
   <Import Project="$(VCTargetsPath)\Microsoft.Cpp.Default.props" />
-  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'" Label="Configuration">
-    <ConfigurationType>DynamicLibrary</ConfigurationType>
-    <UseDebugLibraries>true</UseDebugLibraries>
-    <PlatformToolset>v120</PlatformToolset>
-    <CharacterSet>Unicode</CharacterSet>
-  </PropertyGroup>
   <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'" Label="Configuration">
     <ConfigurationType>DynamicLibrary</ConfigurationType>
     <UseDebugLibraries>true</UseDebugLibraries>
     <PlatformToolset>v120</PlatformToolset>
     <CharacterSet>Unicode</CharacterSet>
   </PropertyGroup>
-  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'" Label="Configuration">
-    <ConfigurationType>DynamicLibrary</ConfigurationType>
-    <UseDebugLibraries>false</UseDebugLibraries>
-    <PlatformToolset>v120</PlatformToolset>
-    <WholeProgramOptimization>true</WholeProgramOptimization>
-    <CharacterSet>Unicode</CharacterSet>
-  </PropertyGroup>
   <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'" Label="Configuration">
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index 9e4d94bcd..f9767b093 100644
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-    <LibraryPath>$(SolutionDir)$(Platform)\$(Configuration);$(VCInstallDir)lib\amd64;$(VCInstallDir)atlmfc\lib\amd64;$(WindowsSDK_LibraryPath_x64);</LibraryPath>
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diff --git a/DataReader/LUSequenceReader/LUSequenceReader.vcxproj b/DataReader/LUSequenceReader/LUSequenceReader.vcxproj
index ad0bc7613..c6ffe7350 100644
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     <LibraryPath>$(SolutionDir)$(Platform)\$(Configuration);$(VCInstallDir)lib\amd64;$(VCInstallDir)atlmfc\lib\amd64;$(WindowsSDK_LibraryPath_x64);</LibraryPath>
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index 9e9adddf4..8f81f06ae 100644
--- a/DataReader/LibSVMBinaryReader/LibSVMBinaryReader.vcxproj
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@@ -1,18 +1,10 @@
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+      <Filter>CNTK-TechReport\figures</Filter>
+    </Image>
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+      <Filter>CNTK-TechReport\figures</Filter>
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+      <Filter>CNTK-TechReport\figures</Filter>
+    </Image>
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+      <Filter>CNTK-TechReport\figures</Filter>
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+      <Filter>CNTK-TechReport\figures</Filter>
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+      <Filter>CNTK-TechReport\figures</Filter>
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+      <Filter>CNTK-TechReport\figures</Filter>
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+      <Filter>CNTK-TechReport\figures</Filter>
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+      <Filter>CNTK-TechReport\figures</Filter>
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+      <Filter>CNTK-TechReport\figures</Filter>
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+      <Filter>CNTK-TechReport\figures</Filter>
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+    <Image Include="CNTK-TechReport\figures\SpeechErrorRate.png">
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+</Project>
\ No newline at end of file
diff --git a/Documentation/Configuration Files.docx b/Documentation/Documents/Configuration Files.docx
similarity index 100%
rename from Documentation/Configuration Files.docx
rename to Documentation/Documents/Configuration Files.docx
diff --git a/Documentation/External Buffer Behavior.docx b/Documentation/Documents/External Buffer Behavior.docx
similarity index 100%
rename from Documentation/External Buffer Behavior.docx
rename to Documentation/Documents/External Buffer Behavior.docx
diff --git a/Documentation/Model Editing Language.docx b/Documentation/Documents/Model Editing Language.docx
similarity index 100%
rename from Documentation/Model Editing Language.docx
rename to Documentation/Documents/Model Editing Language.docx
diff --git a/Documentation/Network Description Language.docx b/Documentation/Documents/Network Description Language.docx
similarity index 100%
rename from Documentation/Network Description Language.docx
rename to Documentation/Documents/Network Description Language.docx
diff --git a/Documentation/CNTK-Tutorial-ICASSP2015.pdf b/Documentation/Tutorial/CNTK-Tutorial-ICASSP2015.pdf
similarity index 100%
rename from Documentation/CNTK-Tutorial-ICASSP2015.pdf
rename to Documentation/Tutorial/CNTK-Tutorial-ICASSP2015.pdf
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new file mode 100644
index 000000000..d33be25ef
--- /dev/null
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@@ -0,0 +1,76 @@
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+<Project DefaultTargets="Build" ToolsVersion="12.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
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+      <Platform>Win32</Platform>
+    </ProjectConfiguration>
+    <ProjectConfiguration Include="Release|Win32">
+      <Configuration>Release</Configuration>
+      <Platform>Win32</Platform>
+    </ProjectConfiguration>
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+  <PropertyGroup Label="Globals">
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+    <RootNamespace>Linux</RootNamespace>
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+  <Import Project="$(VCTargetsPath)\Microsoft.Cpp.Default.props" />
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+    <ConfigurationType>Application</ConfigurationType>
+    <UseDebugLibraries>true</UseDebugLibraries>
+    <PlatformToolset>v120</PlatformToolset>
+    <CharacterSet>MultiByte</CharacterSet>
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+  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'" Label="Configuration">
+    <ConfigurationType>Application</ConfigurationType>
+    <UseDebugLibraries>false</UseDebugLibraries>
+    <PlatformToolset>v120</PlatformToolset>
+    <WholeProgramOptimization>true</WholeProgramOptimization>
+    <CharacterSet>MultiByte</CharacterSet>
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+  <Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
+  <ImportGroup Label="ExtensionSettings">
+  </ImportGroup>
+  <ImportGroup Label="PropertySheets" Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">
+    <Import Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" />
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+  <ImportGroup Label="PropertySheets" Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">
+    <Import Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" />
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+  <PropertyGroup Label="UserMacros" />
+  <PropertyGroup />
+  <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">
+    <ClCompile>
+      <WarningLevel>Level3</WarningLevel>
+      <Optimization>Disabled</Optimization>
+      <SDLCheck>true</SDLCheck>
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+    <Link>
+      <GenerateDebugInformation>true</GenerateDebugInformation>
+    </Link>
+  </ItemDefinitionGroup>
+  <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">
+    <ClCompile>
+      <WarningLevel>Level3</WarningLevel>
+      <Optimization>MaxSpeed</Optimization>
+      <FunctionLevelLinking>true</FunctionLevelLinking>
+      <IntrinsicFunctions>true</IntrinsicFunctions>
+      <SDLCheck>true</SDLCheck>
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+    <Link>
+      <GenerateDebugInformation>true</GenerateDebugInformation>
+      <EnableCOMDATFolding>true</EnableCOMDATFolding>
+      <OptimizeReferences>true</OptimizeReferences>
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+  </ItemDefinitionGroup>
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+    <None Include="..\Makefile.cpu" />
+    <None Include="..\Makefile.gpu" />
+    <None Include="..\Makefile_kaldi.cpu" />
+    <None Include="..\Makefile_kaldi.gpu" />
+    <None Include="..\README" />
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diff --git a/Linux/Linux.vcxproj.filters b/Linux/Linux.vcxproj.filters
new file mode 100644
index 000000000..662801080
--- /dev/null
+++ b/Linux/Linux.vcxproj.filters
@@ -0,0 +1,10 @@
+<?xml version="1.0" encoding="utf-8"?>
+<Project ToolsVersion="4.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
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+    <None Include="..\Makefile.gpu" />
+    <None Include="..\Makefile_kaldi.cpu" />
+    <None Include="..\Makefile_kaldi.gpu" />
+    <None Include="..\README" />
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\ No newline at end of file
diff --git a/MachineLearning/cn/cn.cpp b/MachineLearning/CNTK/CNTK.cpp
similarity index 100%
rename from MachineLearning/cn/cn.cpp
rename to MachineLearning/CNTK/CNTK.cpp
diff --git a/MachineLearning/cn/cn.vcxproj b/MachineLearning/CNTK/CNTK.vcxproj
similarity index 61%
rename from MachineLearning/cn/cn.vcxproj
rename to MachineLearning/CNTK/CNTK.vcxproj
index aa01c1d8b..bc8774852 100644
--- a/MachineLearning/cn/cn.vcxproj
+++ b/MachineLearning/CNTK/CNTK.vcxproj
@@ -1,18 +1,10 @@
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 <Project DefaultTargets="Build" ToolsVersion="12.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
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@@ -29,28 +21,16 @@
     <SccProvider>
     </SccProvider>
     <Keyword>Win32Proj</Keyword>
-    <RootNamespace>cn</RootNamespace>
+    <RootNamespace>CNTK</RootNamespace>
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   <Import Project="$(VCTargetsPath)\Microsoft.Cpp.Default.props" />
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+    <IncludePath>c:\Program Files\Microsoft MPI\Inc;..\..\Math\Math;..\..\Common\;..\..\Common\include;$(VCInstallDir)include;$(CUDA_PATH)\include;$(WindowsSDK_IncludePath);</IncludePath>
+    <LibraryPath>c:\Program Files\Microsoft MPI\Lib\amd64;$(SolutionDir)$(Platform)\$(Configuration);$(SolutionDir)..\Common\lib;$(VCInstallDir)lib\amd64;$(WindowsSDK_LibraryPath_x64);$(CUDA_PATH)\lib\$(Platform)</LibraryPath>
     <CustomBuildAfterTargets>Build</CustomBuildAfterTargets>
-  </PropertyGroup>
-  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">
-    <LinkIncremental>false</LinkIncremental>
+    <IntDir>$(Platform)\$(Configuration)\$(ProjectName)\</IntDir>
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-    <IncludePath>c:\Program Files\Microsoft MPI\Inc;..\..\Math\Math;..\..\Common\;..\..\Common\include;..\..\Common\PTask\include;$(VCInstallDir)include;$(VCInstallDir)atlmfc\include;$(CUDA_PATH)\include;$(WindowsSDK_IncludePath);</IncludePath>
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+    <IncludePath>c:\Program Files\Microsoft MPI\Inc;..\..\Math\Math;..\..\Common\;..\..\Common\include;$(VCInstallDir)include;$(VCInstallDir)atlmfc\include;$(CUDA_PATH)\include;$(WindowsSDK_IncludePath);</IncludePath>
+    <LibraryPath>c:\Program Files\Microsoft MPI\Lib\amd64;$(SolutionDir)$(Platform)\$(Configuration);$(SolutionDir)..\Common\lib;$(VCInstallDir)lib\amd64;$(WindowsSDK_LibraryPath_x64);$(CUDA_PATH)\lib\$(Platform)</LibraryPath>
     <CustomBuildAfterTargets>Build</CustomBuildAfterTargets>
-    <ExecutablePath>$(SolutionDir)..\Common\PTask\bin\;$(ExecutablePath)</ExecutablePath>
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@@ -117,19 +73,18 @@
       <OpenMPSupport>true</OpenMPSupport>
       <TreatWarningAsError>true</TreatWarningAsError>
       <AdditionalOptions>/bigobj %(AdditionalOptions)</AdditionalOptions>
+      <AdditionalIncludeDirectories>"c:\Program Files\NVIDIA Corporation\GDK\gdk_win7_amd64_release\nvml\include"</AdditionalIncludeDirectories>
     </ClCompile>
     <Link>
       <SubSystem>Console</SubSystem>
       <GenerateDebugInformation>true</GenerateDebugInformation>
-      <AdditionalDependencies>Delayimp.lib;nvml.lib;cntkMath.lib;kernel32.lib;user32.lib;gdi32.lib;winspool.lib;comdlg32.lib;advapi32.lib;shell32.lib;ole32.lib;oleaut32.lib;uuid.lib;odbc32.lib;odbccp32.lib;%(AdditionalDependencies)</AdditionalDependencies>
-      <AdditionalLibraryDirectories>$(SolutionDir)$(Platform)\$(Configuration)\</AdditionalLibraryDirectories>
-      <DelayLoadDLLs>CNTKMath.dll;nvml.dll;nvcuda.dll</DelayLoadDLLs>
+      <AdditionalDependencies>CNTKMath.lib; nvml.lib; kernel32.lib; user32.lib; shell32.lib; %(AdditionalDependencies)</AdditionalDependencies>
+      <AdditionalLibraryDirectories>"c:\Program Files\NVIDIA Corporation\GDK\gdk_win7_amd64_release\nvml\lib"</AdditionalLibraryDirectories>
+      <DelayLoadDLLs>CNTKMath.dll; nvml.dll; cudart64_70.dll</DelayLoadDLLs>
     </Link>
     <PostBuildEvent>
-      <Command>
-      </Command>
-      <Message>
-      </Message>
+      <Command>XCOPY /I /Y "%ProgramW6432%\NVIDIA Corporation\NVSMI\nvml*.dll" $(TargetDir)</Command>
+      <Message>Copying NVidia GDK extension DLL to target folder</Message>
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     <CustomBuildStep>
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@@ -144,25 +99,6 @@
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@@ -176,19 +112,21 @@
       <FavorSizeOrSpeed>Speed</FavorSizeOrSpeed>
       <AdditionalOptions>/d2Zi+ %(AdditionalOptions)</AdditionalOptions>
       <TreatWarningAsError>true</TreatWarningAsError>
+      <AdditionalIncludeDirectories>"c:\Program Files\NVIDIA Corporation\GDK\gdk_win7_amd64_release\nvml\include"</AdditionalIncludeDirectories>
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     <Link>
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+      <AdditionalDependencies>CNTKMath.lib; nvml.lib; kernel32.lib; user32.lib; shell32.lib; %(AdditionalDependencies)</AdditionalDependencies>
       <Profile>true</Profile>
-      <DelayLoadDLLs>CNTKMath.dll;nvml.dll;nvcuda.dll</DelayLoadDLLs>
+      <DelayLoadDLLs>CNTKMath.dll; nvml.dll; cudart64_70.dll</DelayLoadDLLs>
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     <PostBuildEvent>
-      <Command>copy $(SolutionDir)..\Common\PTask\bin\*.dll $(TargetDir)</Command>
-      <Message>Copy over the NVidia tools extention DLL</Message>
+      <Command>XCOPY /I /Y "%ProgramW6432%\NVIDIA Corporation\NVSMI\nvml*.dll" $(TargetDir)</Command>
+      <Message>Copying NVidia GDK extension DLL to target folder</Message>
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@@ -256,7 +194,7 @@
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     <ClCompile Include="..\..\Common\TimerUtility.cpp" />
-    <ClCompile Include="cn.cpp" />
+    <ClCompile Include="CNTK.cpp" />
     <ClCompile Include="ComputationNode.cpp" />
     <ClCompile Include="ModelEditLanguage.cpp" />
     <ClCompile Include="NetworkDescriptionLanguage.cpp" />
diff --git a/MachineLearning/cn/cn.vcxproj.filters b/MachineLearning/CNTK/CNTK.vcxproj.filters
similarity index 92%
rename from MachineLearning/cn/cn.vcxproj.filters
rename to MachineLearning/CNTK/CNTK.vcxproj.filters
index 8c07d0ef4..897a06e88 100644
--- a/MachineLearning/cn/cn.vcxproj.filters
+++ b/MachineLearning/CNTK/CNTK.vcxproj.filters
@@ -28,14 +28,11 @@
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-    <ClCompile Include="cn.cpp">
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-    </ClCompile>
     <ClCompile Include="stdafx.cpp">
-      <Filter>Main</Filter>
+      <Filter>Misc</Filter>
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-      <Filter>Main</Filter>
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       <Filter>Network</Filter>
@@ -43,6 +40,7 @@
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       <Filter>Common</Filter>
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+    <ClCompile Include="CNTK.cpp" />
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@@ -124,10 +122,10 @@
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@@ -144,7 +142,7 @@
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similarity index 100%
rename from MachineLearning/cn/cn.vcxproj.vspscc
rename to MachineLearning/CNTK/CNTK.vcxproj.vspscc
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similarity index 100%
rename from MachineLearning/cn/CompositeComputationNode.h
rename to MachineLearning/CNTK/CompositeComputationNode.h
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similarity index 100%
rename from MachineLearning/cn/ComputationNetwork.cpp
rename to MachineLearning/CNTK/ComputationNetwork.cpp
diff --git a/MachineLearning/cn/ComputationNetwork.h b/MachineLearning/CNTK/ComputationNetwork.h
similarity index 100%
rename from MachineLearning/cn/ComputationNetwork.h
rename to MachineLearning/CNTK/ComputationNetwork.h
diff --git a/MachineLearning/cn/ComputationNetworkHelper.h b/MachineLearning/CNTK/ComputationNetworkHelper.h
similarity index 100%
rename from MachineLearning/cn/ComputationNetworkHelper.h
rename to MachineLearning/CNTK/ComputationNetworkHelper.h
diff --git a/MachineLearning/cn/ComputationNode.cpp b/MachineLearning/CNTK/ComputationNode.cpp
similarity index 100%
rename from MachineLearning/cn/ComputationNode.cpp
rename to MachineLearning/CNTK/ComputationNode.cpp
diff --git a/MachineLearning/cn/ComputationNode.h b/MachineLearning/CNTK/ComputationNode.h
similarity index 100%
rename from MachineLearning/cn/ComputationNode.h
rename to MachineLearning/CNTK/ComputationNode.h
diff --git a/MachineLearning/cn/DefaultMacros.txt b/MachineLearning/CNTK/DefaultMacros.txt
similarity index 100%
rename from MachineLearning/cn/DefaultMacros.txt
rename to MachineLearning/CNTK/DefaultMacros.txt
diff --git a/MachineLearning/cn/EvaluationCriterionNode.h b/MachineLearning/CNTK/EvaluationCriterionNode.h
similarity index 100%
rename from MachineLearning/cn/EvaluationCriterionNode.h
rename to MachineLearning/CNTK/EvaluationCriterionNode.h
diff --git a/MachineLearning/cn/FullNetworkBuilder.h b/MachineLearning/CNTK/FullNetworkBuilder.h
similarity index 100%
rename from MachineLearning/cn/FullNetworkBuilder.h
rename to MachineLearning/CNTK/FullNetworkBuilder.h
diff --git a/MachineLearning/cn/IComputationNetBuilder.h b/MachineLearning/CNTK/IComputationNetBuilder.h
similarity index 100%
rename from MachineLearning/cn/IComputationNetBuilder.h
rename to MachineLearning/CNTK/IComputationNetBuilder.h
diff --git a/MachineLearning/cn/IExecutionEngine.h b/MachineLearning/CNTK/IExecutionEngine.h
similarity index 100%
rename from MachineLearning/cn/IExecutionEngine.h
rename to MachineLearning/CNTK/IExecutionEngine.h
diff --git a/MachineLearning/cn/ModelEditLanguage.cpp b/MachineLearning/CNTK/ModelEditLanguage.cpp
similarity index 100%
rename from MachineLearning/cn/ModelEditLanguage.cpp
rename to MachineLearning/CNTK/ModelEditLanguage.cpp
diff --git a/MachineLearning/cn/ModelEditLanguage.h b/MachineLearning/CNTK/ModelEditLanguage.h
similarity index 100%
rename from MachineLearning/cn/ModelEditLanguage.h
rename to MachineLearning/CNTK/ModelEditLanguage.h
diff --git a/MachineLearning/cn/NDLNetworkBuilder.h b/MachineLearning/CNTK/NDLNetworkBuilder.h
similarity index 100%
rename from MachineLearning/cn/NDLNetworkBuilder.h
rename to MachineLearning/CNTK/NDLNetworkBuilder.h
diff --git a/MachineLearning/cn/NDLUtil.h b/MachineLearning/CNTK/NDLUtil.h
similarity index 100%
rename from MachineLearning/cn/NDLUtil.h
rename to MachineLearning/CNTK/NDLUtil.h
diff --git a/MachineLearning/cn/NdlScript.txt b/MachineLearning/CNTK/NdlScript.txt
similarity index 100%
rename from MachineLearning/cn/NdlScript.txt
rename to MachineLearning/CNTK/NdlScript.txt
diff --git a/MachineLearning/cn/NetworkDescriptionLanguage.cpp b/MachineLearning/CNTK/NetworkDescriptionLanguage.cpp
similarity index 100%
rename from MachineLearning/cn/NetworkDescriptionLanguage.cpp
rename to MachineLearning/CNTK/NetworkDescriptionLanguage.cpp
diff --git a/MachineLearning/cn/NetworkDescriptionLanguage.h b/MachineLearning/CNTK/NetworkDescriptionLanguage.h
similarity index 100%
rename from MachineLearning/cn/NetworkDescriptionLanguage.h
rename to MachineLearning/CNTK/NetworkDescriptionLanguage.h
diff --git a/MachineLearning/cn/PTask.cpp b/MachineLearning/CNTK/PTask.cpp
similarity index 100%
rename from MachineLearning/cn/PTask.cpp
rename to MachineLearning/CNTK/PTask.cpp
diff --git a/MachineLearning/cn/PTask.h b/MachineLearning/CNTK/PTask.h
similarity index 100%
rename from MachineLearning/cn/PTask.h
rename to MachineLearning/CNTK/PTask.h
diff --git a/MachineLearning/cn/PTaskComputationNetwork.h b/MachineLearning/CNTK/PTaskComputationNetwork.h
similarity index 100%
rename from MachineLearning/cn/PTaskComputationNetwork.h
rename to MachineLearning/CNTK/PTaskComputationNetwork.h
diff --git a/MachineLearning/cn/PTaskExecutionEngine.h b/MachineLearning/CNTK/PTaskExecutionEngine.h
similarity index 100%
rename from MachineLearning/cn/PTaskExecutionEngine.h
rename to MachineLearning/CNTK/PTaskExecutionEngine.h
diff --git a/MachineLearning/cn/PTaskGraphBuilder.cpp b/MachineLearning/CNTK/PTaskGraphBuilder.cpp
similarity index 100%
rename from MachineLearning/cn/PTaskGraphBuilder.cpp
rename to MachineLearning/CNTK/PTaskGraphBuilder.cpp
diff --git a/MachineLearning/cn/PTaskGraphBuilder.h b/MachineLearning/CNTK/PTaskGraphBuilder.h
similarity index 100%
rename from MachineLearning/cn/PTaskGraphBuilder.h
rename to MachineLearning/CNTK/PTaskGraphBuilder.h
diff --git a/MachineLearning/cn/RecurrentNetworkBuilder.h b/MachineLearning/CNTK/RecurrentNetworkBuilder.h
similarity index 100%
rename from MachineLearning/cn/RecurrentNetworkBuilder.h
rename to MachineLearning/CNTK/RecurrentNetworkBuilder.h
diff --git a/MachineLearning/cn/SGD.h b/MachineLearning/CNTK/SGD.h
similarity index 100%
rename from MachineLearning/cn/SGD.h
rename to MachineLearning/CNTK/SGD.h
diff --git a/MachineLearning/cn/SimpleEvaluator.h b/MachineLearning/CNTK/SimpleEvaluator.h
similarity index 100%
rename from MachineLearning/cn/SimpleEvaluator.h
rename to MachineLearning/CNTK/SimpleEvaluator.h
diff --git a/MachineLearning/cn/SimpleNetworkBuilder.cpp b/MachineLearning/CNTK/SimpleNetworkBuilder.cpp
similarity index 100%
rename from MachineLearning/cn/SimpleNetworkBuilder.cpp
rename to MachineLearning/CNTK/SimpleNetworkBuilder.cpp
diff --git a/MachineLearning/cn/SimpleNetworkBuilder.h b/MachineLearning/CNTK/SimpleNetworkBuilder.h
similarity index 100%
rename from MachineLearning/cn/SimpleNetworkBuilder.h
rename to MachineLearning/CNTK/SimpleNetworkBuilder.h
diff --git a/MachineLearning/cn/SimpleOutputWriter.h b/MachineLearning/CNTK/SimpleOutputWriter.h
similarity index 100%
rename from MachineLearning/cn/SimpleOutputWriter.h
rename to MachineLearning/CNTK/SimpleOutputWriter.h
diff --git a/MachineLearning/cn/SimpleRecurrentNetEvaluator.h b/MachineLearning/CNTK/SimpleRecurrentNetEvaluator.h
similarity index 100%
rename from MachineLearning/cn/SimpleRecurrentNetEvaluator.h
rename to MachineLearning/CNTK/SimpleRecurrentNetEvaluator.h
diff --git a/MachineLearning/cn/SynchronousExecutionEngine.h b/MachineLearning/CNTK/SynchronousExecutionEngine.h
similarity index 100%
rename from MachineLearning/cn/SynchronousExecutionEngine.h
rename to MachineLearning/CNTK/SynchronousExecutionEngine.h
diff --git a/MachineLearning/cn/TrainingCriterionNode.h b/MachineLearning/CNTK/TrainingCriterionNode.h
similarity index 100%
rename from MachineLearning/cn/TrainingCriterionNode.h
rename to MachineLearning/CNTK/TrainingCriterionNode.h
diff --git a/MachineLearning/cn/fileutil.cpp b/MachineLearning/CNTK/fileutil.cpp
similarity index 100%
rename from MachineLearning/cn/fileutil.cpp
rename to MachineLearning/CNTK/fileutil.cpp
diff --git a/MachineLearning/cn/modelEditor.txt b/MachineLearning/CNTK/modelEditor.txt
similarity index 100%
rename from MachineLearning/cn/modelEditor.txt
rename to MachineLearning/CNTK/modelEditor.txt
diff --git a/MachineLearning/cn/modelEditorFromScratch.txt b/MachineLearning/CNTK/modelEditorFromScratch.txt
similarity index 100%
rename from MachineLearning/cn/modelEditorFromScratch.txt
rename to MachineLearning/CNTK/modelEditorFromScratch.txt
diff --git a/MachineLearning/cn/prebuild.bat b/MachineLearning/CNTK/prebuild.bat
similarity index 100%
rename from MachineLearning/cn/prebuild.bat
rename to MachineLearning/CNTK/prebuild.bat
diff --git a/MachineLearning/cn/stdafx.cpp b/MachineLearning/CNTK/stdafx.cpp
similarity index 100%
rename from MachineLearning/cn/stdafx.cpp
rename to MachineLearning/CNTK/stdafx.cpp
diff --git a/MachineLearning/cn/stdafx.h b/MachineLearning/CNTK/stdafx.h
similarity index 100%
rename from MachineLearning/cn/stdafx.h
rename to MachineLearning/CNTK/stdafx.h
diff --git a/MachineLearning/cn/targetver.h b/MachineLearning/CNTK/targetver.h
similarity index 100%
rename from MachineLearning/cn/targetver.h
rename to MachineLearning/CNTK/targetver.h
diff --git a/MachineLearning/cn/tests.cpp b/MachineLearning/CNTK/tests.cpp
similarity index 100%
rename from MachineLearning/cn/tests.cpp
rename to MachineLearning/CNTK/tests.cpp
diff --git a/MachineLearning/CNTKEval/CNTKEval.vcxproj b/MachineLearning/CNTKEval/CNTKEval.vcxproj
index 2e179069d..baab9935c 100644
--- a/MachineLearning/CNTKEval/CNTKEval.vcxproj
+++ b/MachineLearning/CNTKEval/CNTKEval.vcxproj
@@ -50,13 +50,15 @@
   <PropertyGroup Label="UserMacros" />
   <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'">
     <LinkIncremental>true</LinkIncremental>
-    <IncludePath>..\cn;..\..\common\include;..\..\math\math;$(CUDA_PATH)\include;$(VCInstallDir)include;$(VCInstallDir)atlmfc\include;$(WindowsSDK_IncludePath)</IncludePath>
+    <IncludePath>..\CNTK;..\..\common\include;..\..\math\math;$(CUDA_PATH)\include;$(VCInstallDir)include;$(WindowsSDK_IncludePath)</IncludePath>
     <LibraryPath>$(CUDA_PATH)\lib\$(Platform);$(SolutionDir)$(Platform)\;$(Configuration);$(SolutionDir)..\Common\lib;$(SolutionDir)..\CNTK\Common\lib;$(Configuration)\;$(SolutionDir)..\..\cntk\Common\lib;$(VCInstallDir)lib\amd64;$(VCInstallDir)atlmfc\lib\amd64;$(WindowsSDK_LibraryPath_x64);$(CUDA_PATH)\lib\;$(Platform)</LibraryPath>
+    <IntDir>$(Platform)\$(Configuration)\$(ProjectName)\</IntDir>
   </PropertyGroup>
   <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'">
     <LinkIncremental>false</LinkIncremental>
-    <IncludePath>..\cn;..\..\common\include;..\..\math\math;..\..\common\Ptask\include;$(CUDA_PATH)\include;$(VCInstallDir)include;$(VCInstallDir)atlmfc\include;$(WindowsSDK_IncludePath)</IncludePath>
+    <IncludePath>..\CNTK;..\..\common\include;..\..\math\math;$(CUDA_PATH)\include;$(VCInstallDir)include;$(WindowsSDK_IncludePath)</IncludePath>
     <LibraryPath>$(CUDA_PATH)\lib\$(Platform);$(SolutionDir)$(Platform)\;$(Configuration);$(SolutionDir)..\Common\lib;$(SolutionDir)..\CNTK\Common\lib;$(Configuration)\;$(SolutionDir)..\..\cntk\Common\lib;$(Configuration)\;$(VCInstallDir)lib\amd64;$(VCInstallDir)atlmfc\lib\amd64;$(WindowsSDK_LibraryPath_x64)</LibraryPath>
+    <IntDir>$(Platform)\$(Configuration)\$(ProjectName)\</IntDir>
   </PropertyGroup>
   <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'">
     <ClCompile>
@@ -65,16 +67,20 @@
       <Optimization>Disabled</Optimization>
       <PreprocessorDefinitions>EVALDLL;WIN32;_DEBUG;_WINDOWS;_USRDLL;UCIREADER_EXPORTS;%(PreprocessorDefinitions)</PreprocessorDefinitions>
       <SDLCheck>true</SDLCheck>
-      <AdditionalIncludeDirectories>..\..\common\include;..\..\math\math</AdditionalIncludeDirectories>
+      <AdditionalIncludeDirectories>..\Common\include;..\Math\Math;"c:\Program Files\NVIDIA Corporation\GDK\gdk_win7_amd64_release\nvml\include"</AdditionalIncludeDirectories>
       <TreatWarningAsError>true</TreatWarningAsError>
     </ClCompile>
     <Link>
       <SubSystem>Windows</SubSystem>
       <GenerateDebugInformation>true</GenerateDebugInformation>
-      <AdditionalDependencies>Delayimp.lib;cntkMath.lib;kernel32.lib;user32.lib;gdi32.lib;winspool.lib;comdlg32.lib;advapi32.lib;shell32.lib;ole32.lib;oleaut32.lib;uuid.lib;odbc32.lib;odbccp32.lib;%(AdditionalDependencies)</AdditionalDependencies>
-      <AdditionalLibraryDirectories>$(SolutionDir)$(Platform)\$(Configuration)\;..\..\math\$(Platform)\$(Configuration);..\$(Platform)\$(Configuration)</AdditionalLibraryDirectories>
-      <DelayLoadDLLs>CNTKMath.dll;nvml.dll</DelayLoadDLLs>
+      <AdditionalDependencies>CNTKMath.lib; nvml.lib; kernel32.lib; user32.lib; shell32.lib; %(AdditionalDependencies)</AdditionalDependencies>
+      <AdditionalLibraryDirectories>$(SolutionDir)$(Platform)\$(Configuration)\; "c:\Program Files\NVIDIA Corporation\GDK\gdk_win7_amd64_release\nvml\lib"</AdditionalLibraryDirectories>
+      <DelayLoadDLLs>CNTKMath.dll; nvml.dll; cudart64_70.dll</DelayLoadDLLs>
     </Link>
+    <PostBuildEvent>
+      <Command>XCOPY /I /Y "%ProgramW6432%\NVIDIA Corporation\NVSMI\nvml*.dll" $(TargetDir)</Command>
+      <Message>Copying NVidia GDK extension DLL to target folder</Message>
+    </PostBuildEvent>
   </ItemDefinitionGroup>
   <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'">
     <ClCompile>
@@ -85,7 +91,7 @@
       <IntrinsicFunctions>true</IntrinsicFunctions>
       <PreprocessorDefinitions>EVALDLL;WIN32;NDEBUG;_WINDOWS;_USRDLL;UCIREADER_EXPORTS;%(PreprocessorDefinitions)</PreprocessorDefinitions>
       <SDLCheck>true</SDLCheck>
-      <AdditionalIncludeDirectories>..\..\common\include;..\..\math\math</AdditionalIncludeDirectories>
+      <AdditionalIncludeDirectories>..\Common\include; ..\Math\Math; "c:\Program Files\NVIDIA Corporation\GDK\gdk_win7_amd64_release\nvml\include"</AdditionalIncludeDirectories>
       <OpenMPSupport>false</OpenMPSupport>
       <AdditionalOptions>/d2Zi+ %(AdditionalOptions)</AdditionalOptions>
       <RuntimeLibrary>MultiThreadedDLL</RuntimeLibrary>
@@ -96,11 +102,15 @@
       <GenerateDebugInformation>true</GenerateDebugInformation>
       <EnableCOMDATFolding>true</EnableCOMDATFolding>
       <OptimizeReferences>true</OptimizeReferences>
-      <AdditionalDependencies>Delayimp.lib;cntkMath.lib;kernel32.lib;user32.lib;gdi32.lib;winspool.lib;comdlg32.lib;advapi32.lib;shell32.lib;ole32.lib;oleaut32.lib;uuid.lib;odbc32.lib;odbccp32.lib;%(AdditionalDependencies)</AdditionalDependencies>
-      <AdditionalLibraryDirectories>..\..\math\$(Platform)\$(Configuration);$(SolutionDir)$(Platform)\$(Configuration)\</AdditionalLibraryDirectories>
+      <AdditionalDependencies>CNTKMath.lib; nvml.lib; kernel32.lib; user32.lib; shell32.lib; %(AdditionalDependencies)</AdditionalDependencies>
+      <AdditionalLibraryDirectories>$(SolutionDir)$(Platform)\$(Configuration)\; "c:\Program Files\NVIDIA Corporation\GDK\gdk_win7_amd64_release\nvml\lib"</AdditionalLibraryDirectories>
       <Profile>true</Profile>
-      <DelayLoadDLLs>CNTKMath.dll;nvml.dll; cudart64_70.dll</DelayLoadDLLs>
+      <DelayLoadDLLs>CNTKMath.dll; nvml.dll; cudart64_70.dll</DelayLoadDLLs>
     </Link>
+    <PostBuildEvent>
+      <Command>XCOPY /I /Y "%ProgramW6432%\NVIDIA Corporation\NVSMI\nvml*.dll" $(TargetDir)</Command>
+      <Message>Copying NVidia GDK extension DLL to target folder</Message>
+    </PostBuildEvent>
   </ItemDefinitionGroup>
   <ItemGroup>
     <ClInclude Include="..\..\Common\Include\basetypes.h" />
@@ -129,7 +139,7 @@
       <PrecompiledHeader>NotUsing</PrecompiledHeader>
     </ClCompile>
     <ClCompile Include="..\..\Common\TimerUtility.cpp" />
-    <ClCompile Include="..\cn\ComputationNode.cpp">
+    <ClCompile Include="..\CNTK\ComputationNode.cpp">
       <PrecompiledHeader>NotUsing</PrecompiledHeader>
     </ClCompile>
     <ClCompile Include="dllmain.cpp">
@@ -142,11 +152,6 @@
     </ClCompile>
     <ClCompile Include="CNTKEval.cpp" />
   </ItemGroup>
-  <ItemGroup>
-    <ProjectReference Include="..\..\Math\Math\Math.vcxproj">
-      <Project>{60bdb847-d0c4-4fd3-a947-0c15c08bcdb5}</Project>
-    </ProjectReference>
-  </ItemGroup>
   <Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
   <ImportGroup Label="ExtensionTargets">
   </ImportGroup>
diff --git a/MachineLearning/CNTKEval/CNTKEval.vcxproj.filters b/MachineLearning/CNTKEval/CNTKEval.vcxproj.filters
index fa82e0233..df2805694 100644
--- a/MachineLearning/CNTKEval/CNTKEval.vcxproj.filters
+++ b/MachineLearning/CNTKEval/CNTKEval.vcxproj.filters
@@ -2,7 +2,6 @@
 <Project ToolsVersion="4.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
   <ItemGroup>
     <ClCompile Include="..\..\Common\BestGpu.cpp" />
-    <ClCompile Include="..\cn\ComputationNode.cpp" />
     <ClCompile Include="dllmain.cpp" />
     <ClCompile Include="stdafx.cpp" />
     <ClCompile Include="CNTKEval.cpp" />
@@ -21,6 +20,7 @@
     <ClCompile Include="..\..\Common\TimerUtility.cpp">
       <Filter>Common</Filter>
     </ClCompile>
+    <ClCompile Include="..\CNTK\ComputationNode.cpp" />
   </ItemGroup>
   <ItemGroup>
     <ClInclude Include="EvalReader.h" />
diff --git a/MachineLearning/CNTKEval/CNTKEvalTest/CNTKEvalTest.vcxproj b/MachineLearning/CNTKEval/CNTKEvalTest/CNTKEvalTest.vcxproj
index bf78bc036..d99bd6ae4 100644
--- a/MachineLearning/CNTKEval/CNTKEvalTest/CNTKEvalTest.vcxproj
+++ b/MachineLearning/CNTKEval/CNTKEvalTest/CNTKEvalTest.vcxproj
@@ -1,18 +1,10 @@
 <?xml version="1.0" encoding="utf-8"?>
 <Project DefaultTargets="Build" ToolsVersion="12.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
   <ItemGroup Label="ProjectConfigurations">
-    <ProjectConfiguration Include="Debug|Win32">
-      <Configuration>Debug</Configuration>
-      <Platform>Win32</Platform>
-    </ProjectConfiguration>
     <ProjectConfiguration Include="Debug|x64">
       <Configuration>Debug</Configuration>
       <Platform>x64</Platform>
     </ProjectConfiguration>
-    <ProjectConfiguration Include="Release|Win32">
-      <Configuration>Release</Configuration>
-      <Platform>Win32</Platform>
-    </ProjectConfiguration>
     <ProjectConfiguration Include="Release|x64">
       <Configuration>Release</Configuration>
       <Platform>x64</Platform>
@@ -24,25 +16,12 @@
     <RootNamespace>CNTKEvalTest</RootNamespace>
   </PropertyGroup>
   <Import Project="$(VCTargetsPath)\Microsoft.Cpp.Default.props" />
-  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'" Label="Configuration">
-    <ConfigurationType>Application</ConfigurationType>
-    <UseDebugLibraries>true</UseDebugLibraries>
-    <PlatformToolset>v120</PlatformToolset>
-    <CharacterSet>Unicode</CharacterSet>
-  </PropertyGroup>
   <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'" Label="Configuration">
     <ConfigurationType>Application</ConfigurationType>
     <UseDebugLibraries>true</UseDebugLibraries>
     <PlatformToolset>v120</PlatformToolset>
     <CharacterSet>Unicode</CharacterSet>
   </PropertyGroup>
-  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'" Label="Configuration">
-    <ConfigurationType>Application</ConfigurationType>
-    <UseDebugLibraries>false</UseDebugLibraries>
-    <PlatformToolset>v120</PlatformToolset>
-    <WholeProgramOptimization>true</WholeProgramOptimization>
-    <CharacterSet>Unicode</CharacterSet>
-  </PropertyGroup>
   <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'" Label="Configuration">
     <ConfigurationType>Application</ConfigurationType>
     <UseDebugLibraries>false</UseDebugLibraries>
@@ -53,48 +32,25 @@
   <Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
   <ImportGroup Label="ExtensionSettings">
   </ImportGroup>
-  <ImportGroup Label="PropertySheets" Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">
-    <Import Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" />
-  </ImportGroup>
   <ImportGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'" Label="PropertySheets">
     <Import Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" />
   </ImportGroup>
-  <ImportGroup Label="PropertySheets" Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">
-    <Import Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" />
-  </ImportGroup>
   <ImportGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'" Label="PropertySheets">
     <Import Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" />
   </ImportGroup>
   <PropertyGroup Label="UserMacros" />
-  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">
-    <LinkIncremental>true</LinkIncremental>
-  </PropertyGroup>
   <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'">
     <LinkIncremental>true</LinkIncremental>
     <IncludePath>..\..\..\Math\Math;..\..\..\Common\include;$(VCInstallDir)include;$(VCInstallDir)atlmfc\include;$(WindowsSDK_IncludePath);</IncludePath>
     <LibraryPath>$(SolutionDir)$(Platform)\$(Configuration);$(VCInstallDir)lib\amd64;$(VCInstallDir)atlmfc\lib\amd64;$(WindowsSDK_LibraryPath_x64);</LibraryPath>
-  </PropertyGroup>
-  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">
-    <LinkIncremental>false</LinkIncremental>
+    <IntDir>$(Platform)\$(Configuration)\$(ProjectName)\</IntDir>
   </PropertyGroup>
   <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'">
     <LinkIncremental>false</LinkIncremental>
     <IncludePath>..\..\..\Math\Math;..\..\..\Common\include;$(VCInstallDir)include;$(VCInstallDir)atlmfc\include;$(WindowsSDK_IncludePath);</IncludePath>
     <LibraryPath>$(SolutionDir)$(Platform)\$(Configuration);$(VCInstallDir)lib\amd64;$(VCInstallDir)atlmfc\lib\amd64;$(WindowsSDK_LibraryPath_x64);</LibraryPath>
+    <IntDir>$(Platform)\$(Configuration)\$(ProjectName)\</IntDir>
   </PropertyGroup>
-  <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">
-    <ClCompile>
-      <PrecompiledHeader>Use</PrecompiledHeader>
-      <WarningLevel>Level3</WarningLevel>
-      <Optimization>Disabled</Optimization>
-      <PreprocessorDefinitions>WIN32;_DEBUG;_CONSOLE;%(PreprocessorDefinitions)</PreprocessorDefinitions>
-      <SDLCheck>true</SDLCheck>
-    </ClCompile>
-    <Link>
-      <SubSystem>Console</SubSystem>
-      <GenerateDebugInformation>true</GenerateDebugInformation>
-    </Link>
-  </ItemDefinitionGroup>
   <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'">
     <ClCompile>
       <PrecompiledHeader>Use</PrecompiledHeader>
@@ -110,23 +66,6 @@
       <AdditionalDependencies>cntkMath.lib;kernel32.lib;user32.lib;gdi32.lib;winspool.lib;comdlg32.lib;advapi32.lib;shell32.lib;ole32.lib;oleaut32.lib;uuid.lib;odbc32.lib;odbccp32.lib;%(AdditionalDependencies)</AdditionalDependencies>
     </Link>
   </ItemDefinitionGroup>
-  <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">
-    <ClCompile>
-      <WarningLevel>Level3</WarningLevel>
-      <PrecompiledHeader>Use</PrecompiledHeader>
-      <Optimization>MaxSpeed</Optimization>
-      <FunctionLevelLinking>true</FunctionLevelLinking>
-      <IntrinsicFunctions>true</IntrinsicFunctions>
-      <PreprocessorDefinitions>WIN32;NDEBUG;_CONSOLE;%(PreprocessorDefinitions)</PreprocessorDefinitions>
-      <SDLCheck>true</SDLCheck>
-    </ClCompile>
-    <Link>
-      <SubSystem>Console</SubSystem>
-      <GenerateDebugInformation>true</GenerateDebugInformation>
-      <EnableCOMDATFolding>true</EnableCOMDATFolding>
-      <OptimizeReferences>true</OptimizeReferences>
-    </Link>
-  </ItemDefinitionGroup>
   <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'">
     <ClCompile>
       <WarningLevel>Level4</WarningLevel>
@@ -170,9 +109,7 @@
     </ClCompile>
     <ClCompile Include="CNTKEvalTest.cpp" />
     <ClCompile Include="stdafx.cpp">
-      <PrecompiledHeader Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">Create</PrecompiledHeader>
       <PrecompiledHeader Condition="'$(Configuration)|$(Platform)'=='Debug|x64'">Create</PrecompiledHeader>
-      <PrecompiledHeader Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">Create</PrecompiledHeader>
       <PrecompiledHeader Condition="'$(Configuration)|$(Platform)'=='Release|x64'">Create</PrecompiledHeader>
     </ClCompile>
   </ItemGroup>
diff --git a/MachineLearning/PTaskHost/PTaskHost.cpp b/MachineLearning/PTaskHost/PTaskHost.cpp
deleted file mode 100644
index d56f63d12..000000000
--- a/MachineLearning/PTaskHost/PTaskHost.cpp
+++ /dev/null
@@ -1,59 +0,0 @@
-
-#include "stdafx.h"
-#include "PTaskHost.h"
-
-#ifdef USE_PTASK
-
-PTASKHOST_API void __stdcall
-HostTask(LPDEPENDENTCONTEXT depContext)
-{
-    printf("Host task called...\n");
-
-    /*
-    assert(depContext->nArguments == 4 || depContext->nArguments == 5); // some versions pass a sync variable too
-    assert(depContext->ppArguments != NULL);
-                
-    if(depContext->pbIsDependentBinding[0]) {
-
-        void * pvStream = depContext->pStreams[0];
-        cudaStream_t hStream = reinterpret_cast<cudaStream_t>(pvStream);
-        size_t device = reinterpret_cast<size_t>(depContext->pDependentDevices[0]);
-        onstream override(hStream);
-        onptaskdevice overridedev(device);
-
-        // in this case the depContext->ppArguments[*]  are device pointers
-        GEMM_PARAMS * pParams = (GEMM_PARAMS*) depContext->ppArguments[depContext->nArguments-1];
-        MARKRANGEENTER(L"SGemm-A,B,C ctors");
-        cudamatrixops A(pParams->ADim.rows, pParams->ADim.cols, pParams->ADim.colstride, (float *)depContext->ppArguments[0], "GEMM-A");
-        cudamatrixops B(pParams->BDim.rows, pParams->BDim.cols, pParams->BDim.colstride, (float *)depContext->ppArguments[1], "GEMM-B");
-        cudamatrixops C(pParams->CDim.rows, pParams->CDim.cols, pParams->CDim.colstride, (float *)depContext->ppArguments[2]);
-        MARKRANGEEXIT();
-        if (pParams->scale < 1e-12 && pParams->scale != 0.0f) {
-            fprintf(stderr, "!!Scale small, but not equal to zero in GEMM!!\n");
-            pParams->scale = 0.0f;
-        }
-        else
-        {
-            DEPMATRIX3NANCHECK(depContext, SGemm, A, B, C);
-        }
-        MARKRANGEENTER(L"gemm");
-        C.gemm(pParams->scale, A, pParams->Aistransposed, B, pParams->Bistransposed, pParams->ABweight);
-        MARKRANGEEXIT();
-        // TODO: check that ABweight and thisscale can be parameters to the function and don't need to be available when the function actually runs on GPU
-        //cublasDestroy(handle);
-    } else {
-        // in this case the depContext->ppArguments[*]  are host pointers                 
-        // call host version if it exists
-        assert(false);  // no native version
-    }
-    */
-}
-
-#else
-#include <stdio.h>
-PTASKHOST_API void __stdcall
-DummyTask()
-{
-    printf("This should never be called.\n");
-}
-#endif
diff --git a/MachineLearning/PTaskHost/PTaskHost.h b/MachineLearning/PTaskHost/PTaskHost.h
deleted file mode 100644
index 7846a1d9c..000000000
--- a/MachineLearning/PTaskHost/PTaskHost.h
+++ /dev/null
@@ -1,31 +0,0 @@
-// The following ifdef block is the standard way of creating macros which make exporting 
-// from a DLL simpler. All files within this DLL are compiled with the PTASKHOST_EXPORTS
-// symbol defined on the command line. This symbol should not be defined on any project
-// that uses this DLL. This way any other project whose source files include this file see 
-// PTASKHOST_API functions as being imported from a DLL, whereas this DLL sees symbols
-// defined with this macro as being exported.
-#ifdef _WIN32
-#ifdef PTASKHOST_EXPORTS
-#define PTASKHOST_API __declspec(dllexport)
-#else
-#define PTASKHOST_API __declspec(dllimport)
-#endif
-#else
-#define PTASKHOST_API
-#endif
-
-#include "PTask.h"
-
-#ifdef USE_PTASK
-extern "C" {
-
-PTASKHOST_API void __stdcall HostTask(LPDEPENDENTCONTEXT depContext);
-
-}
-#else
-extern "C" {
-
-PTASKHOST_API void __stdcall DummyFunction();
-
-}
-#endif
diff --git a/MachineLearning/PTaskHost/PTaskHost.vcxproj b/MachineLearning/PTaskHost/PTaskHost.vcxproj
deleted file mode 100644
index 47dc08fd1..000000000
--- a/MachineLearning/PTaskHost/PTaskHost.vcxproj
+++ /dev/null
@@ -1,174 +0,0 @@
-<?xml version="1.0" encoding="utf-8"?>
-<Project DefaultTargets="Build" ToolsVersion="4.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
-  <ItemGroup Label="ProjectConfigurations">
-    <ProjectConfiguration Include="Debug|Win32">
-      <Configuration>Debug</Configuration>
-      <Platform>Win32</Platform>
-    </ProjectConfiguration>
-    <ProjectConfiguration Include="Debug|x64">
-      <Configuration>Debug</Configuration>
-      <Platform>x64</Platform>
-    </ProjectConfiguration>
-    <ProjectConfiguration Include="Release|Win32">
-      <Configuration>Release</Configuration>
-      <Platform>Win32</Platform>
-    </ProjectConfiguration>
-    <ProjectConfiguration Include="Release|x64">
-      <Configuration>Release</Configuration>
-      <Platform>x64</Platform>
-    </ProjectConfiguration>
-  </ItemGroup>
-  <PropertyGroup Label="Globals">
-    <ProjectGuid>{6CFF031C-445E-4C55-826B-FA4DF2EEF44B}</ProjectGuid>
-    <Keyword>Win32Proj</Keyword>
-    <RootNamespace>PTaskHost</RootNamespace>
-  </PropertyGroup>
-  <Import Project="$(VCTargetsPath)\Microsoft.Cpp.Default.props" />
-  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'" Label="Configuration">
-    <ConfigurationType>DynamicLibrary</ConfigurationType>
-    <UseDebugLibraries>true</UseDebugLibraries>
-    <PlatformToolset>v110</PlatformToolset>
-    <CharacterSet>Unicode</CharacterSet>
-  </PropertyGroup>
-  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'" Label="Configuration">
-    <ConfigurationType>DynamicLibrary</ConfigurationType>
-    <UseDebugLibraries>true</UseDebugLibraries>
-    <PlatformToolset>v110</PlatformToolset>
-    <CharacterSet>Unicode</CharacterSet>
-  </PropertyGroup>
-  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'" Label="Configuration">
-    <ConfigurationType>DynamicLibrary</ConfigurationType>
-    <UseDebugLibraries>false</UseDebugLibraries>
-    <PlatformToolset>v110</PlatformToolset>
-    <WholeProgramOptimization>true</WholeProgramOptimization>
-    <CharacterSet>Unicode</CharacterSet>
-  </PropertyGroup>
-  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'" Label="Configuration">
-    <ConfigurationType>DynamicLibrary</ConfigurationType>
-    <UseDebugLibraries>false</UseDebugLibraries>
-    <PlatformToolset>v110</PlatformToolset>
-    <WholeProgramOptimization>true</WholeProgramOptimization>
-    <CharacterSet>Unicode</CharacterSet>
-  </PropertyGroup>
-  <Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
-  <ImportGroup Label="ExtensionSettings">
-  </ImportGroup>
-  <ImportGroup Label="PropertySheets" Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">
-    <Import Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" />
-  </ImportGroup>
-  <ImportGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'" Label="PropertySheets">
-    <Import Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" />
-  </ImportGroup>
-  <ImportGroup Label="PropertySheets" Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">
-    <Import Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" />
-  </ImportGroup>
-  <ImportGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'" Label="PropertySheets">
-    <Import Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" />
-  </ImportGroup>
-  <PropertyGroup Label="UserMacros" />
-  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">
-    <LinkIncremental>true</LinkIncremental>
-  </PropertyGroup>
-  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'">
-    <LinkIncremental>true</LinkIncremental>
-    <IncludePath>..\..\Common\PTask\include;$(IncludePath)</IncludePath>
-  </PropertyGroup>
-  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">
-    <LinkIncremental>false</LinkIncremental>
-  </PropertyGroup>
-  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'">
-    <LinkIncremental>false</LinkIncremental>
-    <IncludePath>..\..\Common\PTask\include;$(IncludePath)</IncludePath>
-  </PropertyGroup>
-  <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">
-    <ClCompile>
-      <PrecompiledHeader>Use</PrecompiledHeader>
-      <WarningLevel>Level3</WarningLevel>
-      <Optimization>Disabled</Optimization>
-      <PreprocessorDefinitions>WIN32;_DEBUG;_WINDOWS;_USRDLL;PTASKHOST_EXPORTS;%(PreprocessorDefinitions)</PreprocessorDefinitions>
-    </ClCompile>
-    <Link>
-      <SubSystem>Windows</SubSystem>
-      <GenerateDebugInformation>true</GenerateDebugInformation>
-    </Link>
-  </ItemDefinitionGroup>
-  <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'">
-    <ClCompile>
-      <PrecompiledHeader>Use</PrecompiledHeader>
-      <WarningLevel>Level3</WarningLevel>
-      <Optimization>Disabled</Optimization>
-      <PreprocessorDefinitions>WIN32;_DEBUG;_WINDOWS;_USRDLL;PTASKHOST_EXPORTS;%(PreprocessorDefinitions)</PreprocessorDefinitions>
-      <AdditionalIncludeDirectories>$(ProjectDir)\..\cn;%(AdditionalIncludeDirectories)</AdditionalIncludeDirectories>
-    </ClCompile>
-    <Link>
-      <SubSystem>Windows</SubSystem>
-      <GenerateDebugInformation>true</GenerateDebugInformation>
-    </Link>
-  </ItemDefinitionGroup>
-  <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">
-    <ClCompile>
-      <WarningLevel>Level3</WarningLevel>
-      <PrecompiledHeader>Use</PrecompiledHeader>
-      <Optimization>MaxSpeed</Optimization>
-      <FunctionLevelLinking>true</FunctionLevelLinking>
-      <IntrinsicFunctions>true</IntrinsicFunctions>
-      <PreprocessorDefinitions>WIN32;NDEBUG;_WINDOWS;_USRDLL;PTASKHOST_EXPORTS;%(PreprocessorDefinitions)</PreprocessorDefinitions>
-    </ClCompile>
-    <Link>
-      <SubSystem>Windows</SubSystem>
-      <GenerateDebugInformation>true</GenerateDebugInformation>
-      <EnableCOMDATFolding>true</EnableCOMDATFolding>
-      <OptimizeReferences>true</OptimizeReferences>
-      <Profile>true</Profile>
-    </Link>
-  </ItemDefinitionGroup>
-  <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'">
-    <ClCompile>
-      <WarningLevel>Level3</WarningLevel>
-      <PrecompiledHeader>Use</PrecompiledHeader>
-      <Optimization>MaxSpeed</Optimization>
-      <FunctionLevelLinking>true</FunctionLevelLinking>
-      <IntrinsicFunctions>true</IntrinsicFunctions>
-      <PreprocessorDefinitions>WIN32;NDEBUG;_WINDOWS;_USRDLL;PTASKHOST_EXPORTS;%(PreprocessorDefinitions)</PreprocessorDefinitions>
-      <AdditionalIncludeDirectories>$(ProjectDir)\..\cn;%(AdditionalIncludeDirectories)</AdditionalIncludeDirectories>
-    </ClCompile>
-    <Link>
-      <SubSystem>Windows</SubSystem>
-      <GenerateDebugInformation>true</GenerateDebugInformation>
-      <EnableCOMDATFolding>true</EnableCOMDATFolding>
-      <OptimizeReferences>true</OptimizeReferences>
-      <Profile>true</Profile>
-    </Link>
-  </ItemDefinitionGroup>
-  <ItemGroup>
-    <ClInclude Include="PTaskHost.h" />
-    <ClInclude Include="stdafx.h" />
-    <ClInclude Include="targetver.h" />
-  </ItemGroup>
-  <ItemGroup>
-    <ClCompile Include="dllmain.cpp">
-      <CompileAsManaged Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">false</CompileAsManaged>
-      <CompileAsManaged Condition="'$(Configuration)|$(Platform)'=='Debug|x64'">false</CompileAsManaged>
-      <PrecompiledHeader Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">
-      </PrecompiledHeader>
-      <PrecompiledHeader Condition="'$(Configuration)|$(Platform)'=='Debug|x64'">
-      </PrecompiledHeader>
-      <CompileAsManaged Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">false</CompileAsManaged>
-      <CompileAsManaged Condition="'$(Configuration)|$(Platform)'=='Release|x64'">false</CompileAsManaged>
-      <PrecompiledHeader Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">
-      </PrecompiledHeader>
-      <PrecompiledHeader Condition="'$(Configuration)|$(Platform)'=='Release|x64'">
-      </PrecompiledHeader>
-    </ClCompile>
-    <ClCompile Include="PTaskHost.cpp" />
-    <ClCompile Include="stdafx.cpp">
-      <PrecompiledHeader Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">Create</PrecompiledHeader>
-      <PrecompiledHeader Condition="'$(Configuration)|$(Platform)'=='Debug|x64'">Create</PrecompiledHeader>
-      <PrecompiledHeader Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">Create</PrecompiledHeader>
-      <PrecompiledHeader Condition="'$(Configuration)|$(Platform)'=='Release|x64'">Create</PrecompiledHeader>
-    </ClCompile>
-  </ItemGroup>
-  <Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
-  <ImportGroup Label="ExtensionTargets">
-  </ImportGroup>
-</Project>
\ No newline at end of file
diff --git a/MachineLearning/PTaskHost/dllmain.cpp b/MachineLearning/PTaskHost/dllmain.cpp
deleted file mode 100644
index 465ae722c..000000000
--- a/MachineLearning/PTaskHost/dllmain.cpp
+++ /dev/null
@@ -1,19 +0,0 @@
-// dllmain.cpp : Defines the entry point for the DLL application.
-#include "stdafx.h"
-
-BOOL APIENTRY DllMain( HMODULE hModule,
-                       DWORD  ul_reason_for_call,
-                       LPVOID lpReserved
-                     )
-{
-    switch (ul_reason_for_call)
-    {
-    case DLL_PROCESS_ATTACH:
-    case DLL_THREAD_ATTACH:
-    case DLL_THREAD_DETACH:
-    case DLL_PROCESS_DETACH:
-        break;
-    }
-    return TRUE;
-}
-
diff --git a/MachineLearning/PTaskHost/stdafx.cpp b/MachineLearning/PTaskHost/stdafx.cpp
deleted file mode 100644
index 9fe3fd3b0..000000000
--- a/MachineLearning/PTaskHost/stdafx.cpp
+++ /dev/null
@@ -1,8 +0,0 @@
-// stdafx.cpp : source file that includes just the standard includes
-// PTaskHost.pch will be the pre-compiled header
-// stdafx.obj will contain the pre-compiled type information
-
-#include "stdafx.h"
-
-// TODO: reference any additional headers you need in STDAFX.H
-// and not in this file
diff --git a/MachineLearning/PTaskHost/stdafx.h b/MachineLearning/PTaskHost/stdafx.h
deleted file mode 100644
index f3a07375c..000000000
--- a/MachineLearning/PTaskHost/stdafx.h
+++ /dev/null
@@ -1,16 +0,0 @@
-// stdafx.h : include file for standard system include files,
-// or project specific include files that are used frequently, but
-// are changed infrequently
-//
-
-#pragma once
-
-#include "targetver.h"
-
-#define WIN32_LEAN_AND_MEAN             // Exclude rarely-used stuff from Windows headers
-// Windows Header Files:
-#include <windows.h>
-
-
-
-// TODO: reference additional headers your program requires here
diff --git a/MachineLearning/PTaskHost/targetver.h b/MachineLearning/PTaskHost/targetver.h
deleted file mode 100644
index 87c0086de..000000000
--- a/MachineLearning/PTaskHost/targetver.h
+++ /dev/null
@@ -1,8 +0,0 @@
-#pragma once
-
-// Including SDKDDKVer.h defines the highest available Windows platform.
-
-// If you wish to build your application for a previous Windows platform, include WinSDKVer.h and
-// set the _WIN32_WINNT macro to the platform you wish to support before including SDKDDKVer.h.
-
-#include <SDKDDKVer.h>
diff --git a/Makefile.cpu b/Makefile.cpu
index 0d9ef8e7f..5e7ee5db5 100644
--- a/Makefile.cpu
+++ b/Makefile.cpu
@@ -59,7 +59,7 @@ else
 	MATHLIB_DEFINE = -DUSE_ACML
 endif
 
-INCFLAGS = -I Common/Include -I Math/Math -I MachineLearning/cn -I $(MATHLIB_INCLUDE)  
+INCFLAGS = -I Common/Include -I Math/Math -I MachineLearning/CNTK -I $(MATHLIB_INCLUDE)  
 
 CFLAGS = -msse3 -std=c++0x -std=c++11 -DCPUONLY -D_POSIX_SOURCE -D_XOPEN_SOURCE=600 -D__USE_XOPEN2K $(MATHLIB_DEFINE) -fopenmp -fpermissive -fPIC
 
@@ -67,9 +67,9 @@ COMMON_SRC = Common/fileutil.cpp Common/DataWriter.cpp Common/ConfigFile.cpp Com
              Common/Eval.cpp Common/File.cpp Common/BestGpu.cpp  Common/TimerUtility.cpp
 
 MATH_SRC = Math/Math/Matrix.cpp Math/Math/CPUMatrix.cpp Math/Math/CPUSparseMatrix.cpp Math/Math/NoGPU.cpp
-CN_SRC =  MachineLearning/cn/NetworkDescriptionLanguage.cpp MachineLearning/cn/cn.cpp MachineLearning/cn/ComputationNode.cpp \
-          MachineLearning/cn/ModelEditLanguage.cpp MachineLearning/cn/PTaskGraphBuilder.cpp \
-          MachineLearning/cn/SimpleNetworkBuilder.cpp MachineLearning/cn/tests.cpp MachineLearning/CNTKEval/CNTKEval.cpp
+CN_SRC =  MachineLearning/CNTK/NetworkDescriptionLanguage.cpp MachineLearning/CNTK/CNTK.cpp MachineLearning/CNTK/ComputationNode.cpp \
+          MachineLearning/CNTK/ModelEditLanguage.cpp MachineLearning/CNTK/PTaskGraphBuilder.cpp \
+          MachineLearning/CNTK/SimpleNetworkBuilder.cpp MachineLearning/CNTK/tests.cpp MachineLearning/CNTKEval/CNTKEval.cpp
 BINARYREADER_SRC = DataReader/BinaryReader/BinaryWriter.cpp DataReader/BinaryReader/BinaryReader.cpp DataReader/BinaryReader/BinaryFile.cpp
 HTKMLFREADER_SRC = DataReader/HTKMLFReader_linux/HTKMLFWriter.cpp DataReader/HTKMLFReader_linux/DataWriter.cpp DataReader/HTKMLFReader_linux/DataReader.cpp DataReader/HTKMLFReader_linux/HTKMLFReader.cpp
 SEQUENCEREADER_SRC = DataReader/SequenceReader/SequenceReader.cpp DataReader/SequenceReader/SequenceParser.cpp DataReader/SequenceReader/Exports.cpp
@@ -92,8 +92,8 @@ DEP := $(patsubst %.o, %.d, $(OBJ))
 
 SEPARATOR = "=-----------------------------------------------------------="
 
-#all: $(BINDIR)/cn.exe $(BINDIR)/UCIFastReader.so $(BINDIR)/SequenceReader.so $(BINDIR)/LUSequenceReader.so $(BINDIR)/HTKMLFReader.so $(BINDIR)/BinaryReader.so
-all: $(BINDIR)/cn.exe $(BINDIR)/UCIFastReader.so $(BINDIR)/SequenceReader.so $(BINDIR)/LUSequenceReader.so $(BINDIR)/HTKMLFReader.so
+#all: $(BINDIR)/cntk $(BINDIR)/UCIFastReader.so $(BINDIR)/SequenceReader.so $(BINDIR)/LUSequenceReader.so $(BINDIR)/HTKMLFReader.so $(BINDIR)/BinaryReader.so
+all: $(BINDIR)/cntk $(BINDIR)/UCIFastReader.so $(BINDIR)/SequenceReader.so $(BINDIR)/LUSequenceReader.so $(BINDIR)/HTKMLFReader.so
 
 	ln -sf $(CURDIR)/$(BINDIR)/* bin
 	
@@ -117,7 +117,7 @@ $(BINDIR)/BinaryReader.so: $(BINARYREADER_OBJ) $(CORE_OBJ)
 	@echo $(SEPARATOR)
 	$(CC) $(BUILDTYPE_OPT) -fPIC -shared -o $@ $^
 
-$(BINDIR)/cn.exe: $(CORE_OBJ)
+$(BINDIR)/cntk: $(CORE_OBJ)
 	@echo $(SEPARATOR)
 	@mkdir -p $(dir $@)
 	@echo building output for $(ARCH) with build type $(BUILDTYPE) ...
diff --git a/Makefile.gpu b/Makefile.gpu
index da7cbfbb9..028eaf039 100644
--- a/Makefile.gpu
+++ b/Makefile.gpu
@@ -66,7 +66,7 @@ CUDA_PATH = /usr/local/cuda-7.0
 CUDA_INCLUDE = $(CUDA_PATH)/include
 CUDA_LIB = -L$(CUDA_PATH)/lib64 -lcublas -lcudart -lcuda -lcurand -lcusparse -lnvidia-ml
 
-INCFLAGS = -I Common/Include -I Math/Math -I MachineLearning/cn -I $(CUDA_INCLUDE) -I $(MATHLIB_INCLUDE)
+INCFLAGS = -I Common/Include -I Math/Math -I MachineLearning/CNTK -I $(CUDA_INCLUDE) -I $(MATHLIB_INCLUDE)
 
 CFLAGS = -msse3 -std=c++0x -std=c++11 -D_POSIX_SOURCE -D_XOPEN_SOURCE=600 -D__USE_XOPEN2K $(MATHLIB_DEFINE) -fopenmp -fpermissive
 
@@ -76,9 +76,9 @@ COMMON_SRC = Common/fileutil.cpp Common/DataWriter.cpp Common/ConfigFile.cpp Com
              Common/Eval.cpp Common/File.cpp Common/BestGpu.cpp Common/TimerUtility.cpp
 MATH_SRC = Math/Math/Matrix.cpp Math/Math/GPUMatrix.cu Math/Math/GPUMatrixCUDAKernels.cu Math/Math/GPUSparseMatrix.cu Math/Math/GPUWatcher.cu \
 		   Math/Math/CPUMatrix.cpp Math/Math/CPUSparseMatrix.cpp #Math/Math/InstantiateTemplates.cu
-CN_SRC =  MachineLearning/cn/NetworkDescriptionLanguage.cpp MachineLearning/cn/cn.cpp MachineLearning/cn/ComputationNode.cpp \
-          MachineLearning/cn/ModelEditLanguage.cpp MachineLearning/cn/PTaskGraphBuilder.cpp \
-          MachineLearning/cn/SimpleNetworkBuilder.cpp MachineLearning/cn/tests.cpp MachineLearning/CNTKEval/CNTKEval.cpp
+CN_SRC =  MachineLearning/CNTK/NetworkDescriptionLanguage.cpp MachineLearning/CNTK/CNTK.cpp MachineLearning/CNTK/ComputationNode.cpp \
+          MachineLearning/CNTK/ModelEditLanguage.cpp MachineLearning/CNTK/PTaskGraphBuilder.cpp \
+          MachineLearning/CNTK/SimpleNetworkBuilder.cpp MachineLearning/CNTK/tests.cpp MachineLearning/CNTKEval/CNTKEval.cpp
 BINARYREADER_SRC = #DataReader/BinaryReader/BinaryWriter.cpp DataReader/BinaryReader/BinaryReader.cpp DataReader/BinaryReader/BinaryFile.cpp
 HTKMLFREADER_SRC = DataReader/HTKMLFReader_linux/HTKMLFWriter.cpp DataReader/HTKMLFReader_linux/DataWriter.cpp DataReader/HTKMLFReader_linux/DataReader.cpp DataReader/HTKMLFReader_linux/HTKMLFReader.cpp
 SEQUENCEREADER_SRC = DataReader/SequenceReader/SequenceReader.cpp DataReader/SequenceReader/SequenceParser.cpp DataReader/SequenceReader/Exports.cpp
@@ -102,7 +102,7 @@ DEP := $(patsubst %.o, %.d, $(OBJ))
 
 SEPARATOR = "=-----------------------------------------------------------="
 
-all: $(BINDIR)/cn.exe $(BINDIR)/UCIFastReader.so $(BINDIR)/SequenceReader.so $(BINDIR)/LUSequenceReader.so $(BINDIR)/HTKMLFReader.so
+all: $(BINDIR)/cntk $(BINDIR)/UCIFastReader.so $(BINDIR)/SequenceReader.so $(BINDIR)/LUSequenceReader.so $(BINDIR)/HTKMLFReader.so
 	ln -sf $(CURDIR)/$(BINDIR)/* bin
 
 $(BINDIR)/UCIFastReader.so: $(UCIFASTREADER_OBJ) $(CORE_OBJ)
@@ -128,7 +128,7 @@ $(BINDIR)/HTKMLFReader.so: $(HTKMLFREADER_OBJ) $(CORE_OBJ)
 #BinaryReader: ${BINARYREADER_SRC:.cpp=.o} ${COMMON_SRC:.cpp=.o}
 #	$(CC) -o $(addsuffix .so, $@) $^ -fPIC -shared 
 
-$(BINDIR)/cn.exe: $(CORE_OBJ)
+$(BINDIR)/cntk: $(CORE_OBJ)
 	@echo $(SEPARATOR)
 	@mkdir -p $(dir $@)
 	@echo building output for $(ARCH) with build type $(BUILDTYPE)
diff --git a/Makefile_kaldi.cpu b/Makefile_kaldi.cpu
index 2d01f61f9..145dbbd48 100644
--- a/Makefile_kaldi.cpu
+++ b/Makefile_kaldi.cpu
@@ -63,7 +63,7 @@ else
 endif
 KALDI_LIB = -LDataReader/KaldiReader/base/kaldi-base
 
-INCFLAGS = -I Common/Include -I Math/Math -I MachineLearning/cn -I $(MATHLIB_INCLUDE)  -I DataReader/KaldiReader  
+INCFLAGS = -I Common/Include -I Math/Math -I MachineLearning/CNTK -I $(MATHLIB_INCLUDE)  -I DataReader/KaldiReader  
 
 
 CFLAGS = -msse3 -std=c++0x -std=c++11 -DCPUONLY -D_POSIX_SOURCE -D_XOPEN_SOURCE=600 -D__USE_XOPEN2K -DHAVE_POSIX_MEMALIGN ${KALDI_DEFINE} $(MATHLIB_DEFINE) -fopenmp -fpermissive -fPIC
@@ -72,9 +72,9 @@ COMMON_SRC = Common/fileutil.cpp Common/DataWriter.cpp Common/ConfigFile.cpp Com
              Common/Eval.cpp Common/File.cpp Common/BestGpu.cpp  Common/TimerUtility.cpp
 
 MATH_SRC = Math/Math/Matrix.cpp Math/Math/CPUMatrix.cpp Math/Math/CPUSparseMatrix.cpp Math/Math/NoGPU.cpp
-CN_SRC =  MachineLearning/cn/NetworkDescriptionLanguage.cpp MachineLearning/cn/cn.cpp MachineLearning/cn/ComputationNode.cpp \
-          MachineLearning/cn/ModelEditLanguage.cpp MachineLearning/cn/PTaskGraphBuilder.cpp \
-          MachineLearning/cn/SimpleNetworkBuilder.cpp MachineLearning/cn/tests.cpp MachineLearning/CNTKEval/CNTKEval.cpp
+CN_SRC =  MachineLearning/CNTK/NetworkDescriptionLanguage.cpp MachineLearning/CNTK/CNTK.cpp MachineLearning/CNTK/ComputationNode.cpp \
+          MachineLearning/CNTK/ModelEditLanguage.cpp MachineLearning/CNTK/PTaskGraphBuilder.cpp \
+          MachineLearning/CNTK/SimpleNetworkBuilder.cpp MachineLearning/CNTK/tests.cpp MachineLearning/CNTKEval/CNTKEval.cpp
 BINARYREADER_SRC = DataReader/BinaryReader/BinaryWriter.cpp DataReader/BinaryReader/BinaryReader.cpp DataReader/BinaryReader/BinaryFile.cpp
 HTKMLFREADER_SRC = DataReader/HTKMLFReader_linux/HTKMLFWriter.cpp DataReader/HTKMLFReader_linux/DataWriter.cpp DataReader/HTKMLFReader_linux/DataReader.cpp DataReader/HTKMLFReader_linux/HTKMLFReader.cpp
 KALDIREADER_SRC = DataReader/KaldiReader/HTKMLFWriter.cpp DataReader/KaldiReader/DataWriter.cpp DataReader/KaldiReader/DataReader.cpp DataReader/KaldiReader/HTKMLFReader.cpp
@@ -108,8 +108,8 @@ DEP := $(patsubst %.o, %.d, $(OBJ))
 
 SEPARATOR = "=-----------------------------------------------------------="
 
-#all: $(BINDIR)/cn.exe $(BINDIR)/UCIFastReader.so $(BINDIR)/SequenceReader.so $(BINDIR)/LUSequenceReader.so $(BINDIR)/HTKMLFReader.so $(BINDIR)/BinaryReader.so
-all: $(BINDIR)/cn.exe $(BINDIR)/UCIFastReader.so $(BINDIR)/LMSequenceReader.so $(BINDIR)/LUSequenceReader.so $(BINDIR)/HTKMLFReader.so $(BINDIR)/KaldiReader.so 
+#all: $(BINDIR)/cntk $(BINDIR)/UCIFastReader.so $(BINDIR)/SequenceReader.so $(BINDIR)/LUSequenceReader.so $(BINDIR)/HTKMLFReader.so $(BINDIR)/BinaryReader.so
+all: $(BINDIR)/cntk $(BINDIR)/UCIFastReader.so $(BINDIR)/LMSequenceReader.so $(BINDIR)/LUSequenceReader.so $(BINDIR)/HTKMLFReader.so $(BINDIR)/KaldiReader.so 
 
 	ln -sf $(CURDIR)/$(BINDIR)/* bin
 	
@@ -138,7 +138,7 @@ $(BINDIR)/KaldiReader.so: $(KALDIREADER_OBJ) $(CORE_OBJ) $(KALDI_OBJ)
 	$(CC) $(BUILDTYPE_OPT) -fPIC -shared -o $@ $^
 
 
-$(BINDIR)/cn.exe: $(CORE_OBJ)
+$(BINDIR)/cntk: $(CORE_OBJ)
 	@echo $(SEPARATOR)
 	@mkdir -p $(dir $@)
 	@echo building output for $(ARCH) with build type $(BUILDTYPE) ...
diff --git a/Makefile_kaldi.gpu b/Makefile_kaldi.gpu
index 480341540..7b4fe76ef 100644
--- a/Makefile_kaldi.gpu
+++ b/Makefile_kaldi.gpu
@@ -69,7 +69,7 @@ CUDA_PATH = /usr/local/cuda-7.0
 CUDA_INCLUDE = $(CUDA_PATH)/include
 CUDA_LIB = -L$(CUDA_PATH)/lib64 -lcublas -lcudart -lcuda -lcurand -lcusparse -lnvidia-ml
 
-INCFLAGS = -I Common/Include -I Math/Math -I MachineLearning/cn -I $(CUDA_INCLUDE) -I $(MATHLIB_INCLUDE) -I DataReader/KaldiReader  
+INCFLAGS = -I Common/Include -I Math/Math -I MachineLearning/CNTK -I $(CUDA_INCLUDE) -I $(MATHLIB_INCLUDE) -I DataReader/KaldiReader  
 
 CFLAGS = -msse3 -std=c++0x -std=c++11 -D_POSIX_SOURCE -D_XOPEN_SOURCE=600 -D__USE_XOPEN2K -DHAVE_POSIX_MEMALIGN ${KALDI_DEFINE} $(MATHLIB_DEFINE) -fopenmp -fpermissive
 
@@ -79,9 +79,9 @@ COMMON_SRC = Common/fileutil.cpp Common/DataWriter.cpp Common/ConfigFile.cpp Com
              Common/Eval.cpp Common/File.cpp Common/BestGpu.cpp Common/TimerUtility.cpp
 MATH_SRC = Math/Math/Matrix.cpp Math/Math/GPUMatrix.cu Math/Math/GPUMatrixCUDAKernels.cu Math/Math/GPUSparseMatrix.cu Math/Math/GPUWatcher.cu \
 		   Math/Math/CPUMatrix.cpp Math/Math/CPUSparseMatrix.cpp #Math/Math/InstantiateTemplates.cu
-CN_SRC =  MachineLearning/cn/NetworkDescriptionLanguage.cpp MachineLearning/cn/cn.cpp MachineLearning/cn/ComputationNode.cpp \
-          MachineLearning/cn/ModelEditLanguage.cpp MachineLearning/cn/PTaskGraphBuilder.cpp \
-          MachineLearning/cn/SimpleNetworkBuilder.cpp MachineLearning/cn/tests.cpp MachineLearning/CNTKEval/CNTKEval.cpp
+CN_SRC =  MachineLearning/CNTK/NetworkDescriptionLanguage.cpp MachineLearning/CNTK/CNTK.cpp MachineLearning/CNTK/ComputationNode.cpp \
+          MachineLearning/CNTK/ModelEditLanguage.cpp MachineLearning/CNTK/PTaskGraphBuilder.cpp \
+          MachineLearning/CNTK/SimpleNetworkBuilder.cpp MachineLearning/CNTK/tests.cpp MachineLearning/CNTKEval/CNTKEval.cpp
 BINARYREADER_SRC = #DataReader/BinaryReader/BinaryWriter.cpp DataReader/BinaryReader/BinaryReader.cpp DataReader/BinaryReader/BinaryFile.cpp
 HTKMLFREADER_SRC = DataReader/HTKMLFReader_linux/HTKMLFWriter.cpp DataReader/HTKMLFReader_linux/DataWriter.cpp DataReader/HTKMLFReader_linux/DataReader.cpp DataReader/HTKMLFReader_linux/HTKMLFReader.cpp
 KALDIREADER_SRC = DataReader/KaldiReader/HTKMLFWriter.cpp DataReader/KaldiReader/DataWriter.cpp DataReader/KaldiReader/DataReader.cpp DataReader/KaldiReader/HTKMLFReader.cpp
@@ -118,7 +118,7 @@ DEP := $(patsubst %.o, %.d, $(OBJ))
 
 SEPARATOR = "=-----------------------------------------------------------="
 
-all: $(BINDIR)/cn.exe $(BINDIR)/UCIFastReader.so $(BINDIR)/LMSequenceReader.so $(BINDIR)/LUSequenceReader.so $(BINDIR)/HTKMLFReader.so $(BINDIR)/KaldiReader.so $(BINDIR)/KaldiWriter.so
+all: $(BINDIR)/cntk $(BINDIR)/UCIFastReader.so $(BINDIR)/LMSequenceReader.so $(BINDIR)/LUSequenceReader.so $(BINDIR)/HTKMLFReader.so $(BINDIR)/KaldiReader.so $(BINDIR)/KaldiWriter.so
 
 
 	ln -sf $(CURDIR)/$(BINDIR)/* bin
@@ -154,7 +154,7 @@ $(BINDIR)/KaldiWriter.so: $(KALDIREADER_OBJ) $(CORE_OBJ)
 #BinaryReader: ${BINARYREADER_SRC:.cpp=.o} ${COMMON_SRC:.cpp=.o}
 #	$(CC) -o $(addsuffix .so, $@) $^ -fPIC -shared 
 
-$(BINDIR)/cn.exe: $(CORE_OBJ)
+$(BINDIR)/cntk: $(CORE_OBJ)
 	@echo $(SEPARATOR)
 	@mkdir -p $(dir $@)
 	@echo building output for $(ARCH) with build type $(BUILDTYPE)
diff --git a/Math/CNTKMathTest/CNTKMathTest.vcxproj b/Math/CNTKMathTest/CNTKMathTest.vcxproj
index 28f5b7fc0..d40fc7bb4 100644
--- a/Math/CNTKMathTest/CNTKMathTest.vcxproj
+++ b/Math/CNTKMathTest/CNTKMathTest.vcxproj
@@ -1,18 +1,10 @@
 <?xml version="1.0" encoding="utf-8"?>
 <Project DefaultTargets="Build" ToolsVersion="12.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
   <ItemGroup Label="ProjectConfigurations">
-    <ProjectConfiguration Include="Debug|Win32">
-      <Configuration>Debug</Configuration>
-      <Platform>Win32</Platform>
-    </ProjectConfiguration>
     <ProjectConfiguration Include="Debug|x64">
       <Configuration>Debug</Configuration>
       <Platform>x64</Platform>
     </ProjectConfiguration>
-    <ProjectConfiguration Include="Release|Win32">
-      <Configuration>Release</Configuration>
-      <Platform>Win32</Platform>
-    </ProjectConfiguration>
     <ProjectConfiguration Include="Release|x64">
       <Configuration>Release</Configuration>
       <Platform>x64</Platform>
@@ -32,13 +24,6 @@
     <RootNamespace>CNTKMathTest</RootNamespace>
   </PropertyGroup>
   <Import Project="$(VCTargetsPath)\Microsoft.Cpp.Default.props" />
-  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'" Label="Configuration">
-    <ConfigurationType>DynamicLibrary</ConfigurationType>
-    <UseDebugLibraries>true</UseDebugLibraries>
-    <PlatformToolset>v120</PlatformToolset>
-    <CharacterSet>Unicode</CharacterSet>
-    <UseOfMfc>false</UseOfMfc>
-  </PropertyGroup>
   <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'" Label="Configuration">
     <ConfigurationType>DynamicLibrary</ConfigurationType>
     <UseDebugLibraries>true</UseDebugLibraries>
@@ -46,14 +31,6 @@
     <CharacterSet>Unicode</CharacterSet>
     <UseOfMfc>false</UseOfMfc>
   </PropertyGroup>
-  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'" Label="Configuration">
-    <ConfigurationType>DynamicLibrary</ConfigurationType>
-    <UseDebugLibraries>false</UseDebugLibraries>
-    <PlatformToolset>v120</PlatformToolset>
-    <WholeProgramOptimization>true</WholeProgramOptimization>
-    <CharacterSet>Unicode</CharacterSet>
-    <UseOfMfc>false</UseOfMfc>
-  </PropertyGroup>
   <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'" Label="Configuration">
     <ConfigurationType>DynamicLibrary</ConfigurationType>
     <UseDebugLibraries>false</UseDebugLibraries>
@@ -66,48 +43,23 @@
   <ImportGroup Label="ExtensionSettings">
     <Import Project="$(VCTargetsPath)\BuildCustomizations\CUDA 7.0.props" />
   </ImportGroup>
-  <ImportGroup Label="PropertySheets" Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">
-    <Import Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" />
-  </ImportGroup>
   <ImportGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'" Label="PropertySheets">
     <Import Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" />
   </ImportGroup>
-  <ImportGroup Label="PropertySheets" Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">
-    <Import Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" />
-  </ImportGroup>
   <ImportGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'" Label="PropertySheets">
     <Import Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" />
   </ImportGroup>
   <PropertyGroup Label="UserMacros" />
-  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">
-    <LinkIncremental>true</LinkIncremental>
-  </PropertyGroup>
   <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'">
     <LinkIncremental>true</LinkIncremental>
     <IncludePath>..\..\common\include\;$(IncludePath)</IncludePath>
-  </PropertyGroup>
-  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">
-    <LinkIncremental>true</LinkIncremental>
+    <IntDir>$(Platform)\$(Configuration)\$(ProjectName)\</IntDir>
   </PropertyGroup>
   <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'">
     <LinkIncremental>true</LinkIncremental>
     <IncludePath>..\..\common\include\;$(IncludePath);$(VCInstallDir)include;$(VCInstallDir)atlmfc\include;$(WindowsSDK_IncludePath);</IncludePath>
+    <IntDir>$(Platform)\$(Configuration)\$(ProjectName)\</IntDir>
   </PropertyGroup>
-  <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">
-    <ClCompile>
-      <PrecompiledHeader>Use</PrecompiledHeader>
-      <WarningLevel>Level3</WarningLevel>
-      <Optimization>Disabled</Optimization>
-      <AdditionalIncludeDirectories>$(VCInstallDir)UnitTest\include;%(AdditionalIncludeDirectories)</AdditionalIncludeDirectories>
-      <PreprocessorDefinitions>WIN32;_DEBUG;%(PreprocessorDefinitions)</PreprocessorDefinitions>
-      <UseFullPaths>true</UseFullPaths>
-    </ClCompile>
-    <Link>
-      <SubSystem>Windows</SubSystem>
-      <GenerateDebugInformation>true</GenerateDebugInformation>
-      <AdditionalLibraryDirectories>$(VCInstallDir)UnitTest\lib;%(AdditionalLibraryDirectories)</AdditionalLibraryDirectories>
-    </Link>
-  </ItemDefinitionGroup>
   <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'">
     <ClCompile>
       <PrecompiledHeader>NotUsing</PrecompiledHeader>
@@ -129,25 +81,6 @@
       <CodeGeneration>compute_20,sm_20;compute_30,sm_30;%(CodeGeneration)</CodeGeneration>
     </CudaCompile>
   </ItemDefinitionGroup>
-  <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">
-    <ClCompile>
-      <WarningLevel>Level3</WarningLevel>
-      <PrecompiledHeader>Use</PrecompiledHeader>
-      <Optimization>MaxSpeed</Optimization>
-      <FunctionLevelLinking>true</FunctionLevelLinking>
-      <IntrinsicFunctions>true</IntrinsicFunctions>
-      <AdditionalIncludeDirectories>$(VCInstallDir)UnitTest\include;%(AdditionalIncludeDirectories)</AdditionalIncludeDirectories>
-      <PreprocessorDefinitions>WIN32;NDEBUG;%(PreprocessorDefinitions)</PreprocessorDefinitions>
-      <UseFullPaths>true</UseFullPaths>
-    </ClCompile>
-    <Link>
-      <SubSystem>Windows</SubSystem>
-      <GenerateDebugInformation>true</GenerateDebugInformation>
-      <EnableCOMDATFolding>true</EnableCOMDATFolding>
-      <OptimizeReferences>true</OptimizeReferences>
-      <AdditionalLibraryDirectories>$(VCInstallDir)UnitTest\lib;%(AdditionalLibraryDirectories)</AdditionalLibraryDirectories>
-    </Link>
-  </ItemDefinitionGroup>
   <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'">
     <ClCompile>
       <WarningLevel>Level4</WarningLevel>
@@ -186,9 +119,7 @@
     <ClCompile Include="MatrixSparseDenseInteractionsTests.cpp" />
     <ClCompile Include="MatrixUnitTests.cpp" />
     <ClCompile Include="stdafx.cpp">
-      <PrecompiledHeader Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">Create</PrecompiledHeader>
       <PrecompiledHeader Condition="'$(Configuration)|$(Platform)'=='Debug|x64'">Create</PrecompiledHeader>
-      <PrecompiledHeader Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">Create</PrecompiledHeader>
       <PrecompiledHeader Condition="'$(Configuration)|$(Platform)'=='Release|x64'">Create</PrecompiledHeader>
     </ClCompile>
     <ClCompile Include="CPUMatrixUnitTests.cpp" />
diff --git a/Math/Math.sln b/Math/Math.sln
deleted file mode 100644
index e0712ce00..000000000
--- a/Math/Math.sln
+++ /dev/null
@@ -1,75 +0,0 @@
-
-Microsoft Visual Studio Solution File, Format Version 12.00
-# Visual Studio 2012
-Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "CNTKMath", "Math\Math.vcxproj", "{60BDB847-D0C4-4FD3-A947-0C15C08BCDB5}"
-EndProject
-Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "CNTKMathTest", "CNTKMathTest\CNTKMathTest.vcxproj", "{6CEE834A-8104-46A8-8902-64C81BD7928F}"
-EndProject
-Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "MathPerformanceTests", "MathPerformanceTests\MathPerformanceTests.vcxproj", "{668BEED5-AC07-4F35-B3AE-EE65A7F9C976}"
-EndProject
-Global
-	GlobalSection(TeamFoundationVersionControl) = preSolution
-		SccNumberOfProjects = 4
-		SccEnterpriseProvider = {4CA58AB2-18FA-4F8D-95D4-32DDF27D184C}
-		SccTeamFoundationServer = http://vstfcodebox:8080/tfs/kappa
-		SccLocalPath0 = .
-		SccProjectUniqueName1 = Math\\Math.vcxproj
-		SccProjectName1 = Math
-		SccLocalPath1 = Math
-		SccProjectUniqueName2 = CNTKMathTest\\CNTKMathTest.vcxproj
-		SccProjectName2 = CNTKMathTest
-		SccLocalPath2 = CNTKMathTest
-		SccProjectUniqueName3 = MathPerformanceTests\\MathPerformanceTests.vcxproj
-		SccProjectName3 = MathPerformanceTests
-		SccLocalPath3 = MathPerformanceTests
-	EndGlobalSection
-	GlobalSection(SolutionConfigurationPlatforms) = preSolution
-		Debug|Mixed Platforms = Debug|Mixed Platforms
-		Debug|Win32 = Debug|Win32
-		Debug|x64 = Debug|x64
-		Release|Mixed Platforms = Release|Mixed Platforms
-		Release|Win32 = Release|Win32
-		Release|x64 = Release|x64
-	EndGlobalSection
-	GlobalSection(ProjectConfigurationPlatforms) = postSolution
-		{60BDB847-D0C4-4FD3-A947-0C15C08BCDB5}.Debug|Mixed Platforms.ActiveCfg = Debug|Win32
-		{60BDB847-D0C4-4FD3-A947-0C15C08BCDB5}.Debug|Mixed Platforms.Build.0 = Debug|Win32
-		{60BDB847-D0C4-4FD3-A947-0C15C08BCDB5}.Debug|Win32.ActiveCfg = Debug|Win32
-		{60BDB847-D0C4-4FD3-A947-0C15C08BCDB5}.Debug|Win32.Build.0 = Debug|Win32
-		{60BDB847-D0C4-4FD3-A947-0C15C08BCDB5}.Debug|x64.ActiveCfg = Debug|x64
-		{60BDB847-D0C4-4FD3-A947-0C15C08BCDB5}.Debug|x64.Build.0 = Debug|x64
-		{60BDB847-D0C4-4FD3-A947-0C15C08BCDB5}.Release|Mixed Platforms.ActiveCfg = Release|Win32
-		{60BDB847-D0C4-4FD3-A947-0C15C08BCDB5}.Release|Mixed Platforms.Build.0 = Release|Win32
-		{60BDB847-D0C4-4FD3-A947-0C15C08BCDB5}.Release|Win32.ActiveCfg = Release|Win32
-		{60BDB847-D0C4-4FD3-A947-0C15C08BCDB5}.Release|Win32.Build.0 = Release|Win32
-		{60BDB847-D0C4-4FD3-A947-0C15C08BCDB5}.Release|x64.ActiveCfg = Release|x64
-		{60BDB847-D0C4-4FD3-A947-0C15C08BCDB5}.Release|x64.Build.0 = Release|x64
-		{6CEE834A-8104-46A8-8902-64C81BD7928F}.Debug|Mixed Platforms.ActiveCfg = Debug|Win32
-		{6CEE834A-8104-46A8-8902-64C81BD7928F}.Debug|Mixed Platforms.Build.0 = Debug|Win32
-		{6CEE834A-8104-46A8-8902-64C81BD7928F}.Debug|Win32.ActiveCfg = Debug|Win32
-		{6CEE834A-8104-46A8-8902-64C81BD7928F}.Debug|Win32.Build.0 = Debug|Win32
-		{6CEE834A-8104-46A8-8902-64C81BD7928F}.Debug|x64.ActiveCfg = Debug|x64
-		{6CEE834A-8104-46A8-8902-64C81BD7928F}.Debug|x64.Build.0 = Debug|x64
-		{6CEE834A-8104-46A8-8902-64C81BD7928F}.Release|Mixed Platforms.ActiveCfg = Release|Win32
-		{6CEE834A-8104-46A8-8902-64C81BD7928F}.Release|Mixed Platforms.Build.0 = Release|Win32
-		{6CEE834A-8104-46A8-8902-64C81BD7928F}.Release|Win32.ActiveCfg = Release|Win32
-		{6CEE834A-8104-46A8-8902-64C81BD7928F}.Release|Win32.Build.0 = Release|Win32
-		{6CEE834A-8104-46A8-8902-64C81BD7928F}.Release|x64.ActiveCfg = Release|x64
-		{6CEE834A-8104-46A8-8902-64C81BD7928F}.Release|x64.Build.0 = Release|x64
-		{668BEED5-AC07-4F35-B3AE-EE65A7F9C976}.Debug|Mixed Platforms.ActiveCfg = Debug|Win32
-		{668BEED5-AC07-4F35-B3AE-EE65A7F9C976}.Debug|Mixed Platforms.Build.0 = Debug|Win32
-		{668BEED5-AC07-4F35-B3AE-EE65A7F9C976}.Debug|Win32.ActiveCfg = Debug|Win32
-		{668BEED5-AC07-4F35-B3AE-EE65A7F9C976}.Debug|Win32.Build.0 = Debug|Win32
-		{668BEED5-AC07-4F35-B3AE-EE65A7F9C976}.Debug|x64.ActiveCfg = Debug|x64
-		{668BEED5-AC07-4F35-B3AE-EE65A7F9C976}.Debug|x64.Build.0 = Debug|x64
-		{668BEED5-AC07-4F35-B3AE-EE65A7F9C976}.Release|Mixed Platforms.ActiveCfg = Release|Win32
-		{668BEED5-AC07-4F35-B3AE-EE65A7F9C976}.Release|Mixed Platforms.Build.0 = Release|Win32
-		{668BEED5-AC07-4F35-B3AE-EE65A7F9C976}.Release|Win32.ActiveCfg = Release|Win32
-		{668BEED5-AC07-4F35-B3AE-EE65A7F9C976}.Release|Win32.Build.0 = Release|Win32
-		{668BEED5-AC07-4F35-B3AE-EE65A7F9C976}.Release|x64.ActiveCfg = Release|x64
-		{668BEED5-AC07-4F35-B3AE-EE65A7F9C976}.Release|x64.Build.0 = Release|x64
-	EndGlobalSection
-	GlobalSection(SolutionProperties) = preSolution
-		HideSolutionNode = FALSE
-	EndGlobalSection
-EndGlobal
diff --git a/Math/Math.vssscc b/Math/Math.vssscc
deleted file mode 100644
index 6cb031bcf..000000000
--- a/Math/Math.vssscc
+++ /dev/null
@@ -1,10 +0,0 @@
-""
-{
-"FILE_VERSION" = "9237"
-"ENLISTMENT_CHOICE" = "NEVER"
-"PROJECT_FILE_RELATIVE_PATH" = ""
-"NUMBER_OF_EXCLUDED_FILES" = "0"
-"ORIGINAL_PROJECT_FILE_PATH" = ""
-"NUMBER_OF_NESTED_PROJECTS" = "0"
-"SOURCE_CONTROL_SETTINGS_PROVIDER" = "PROJECT"
-}
diff --git a/Math/Math/CNTKMathCUDA.vcxproj b/Math/Math/CNTKMathCUDA.vcxproj
index 7fe728c60..feb45bd70 100644
--- a/Math/Math/CNTKMathCUDA.vcxproj
+++ b/Math/Math/CNTKMathCUDA.vcxproj
@@ -54,13 +54,13 @@
     <LinkIncremental>true</LinkIncremental>
     <IncludePath>..\..\common\include;$(ACML_PATH)\include;$(CUDA_PATH)\include;$(IncludePath)</IncludePath>
     <LibraryPath>$(SolutionDir)$(Platform)\$(Configuration);$(ACML_PATH)\lib;$(CUDA_PATH)\lib\$(Platform);$(LibraryPath)</LibraryPath>
-    <IntDir>$(Platform)\$(Configuration)\CUDA\</IntDir>
+    <IntDir>$(Platform)\$(Configuration)\$(ProjectName)\</IntDir>
   </PropertyGroup>
   <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'">
     <LinkIncremental>false</LinkIncremental>
     <IncludePath>..\..\common\include;$(CUDA_PATH)\include;$(ACML_PATH)\include;$(VCInstallDir)include;$(VCInstallDir)atlmfc\include;$(WindowsSDK_IncludePath);</IncludePath>
     <LibraryPath>$(SolutionDir)$(Platform)\$(Configuration);$(ACML_PATH)\lib;$(CUDA_PATH)\lib\$(Platform);$(VCInstallDir)lib\amd64;$(VCInstallDir)atlmfc\lib\amd64;$(WindowsSDK_LibraryPath_x64);</LibraryPath>
-    <IntDir>$(Platform)\$(Configuration)\CUDA\</IntDir>
+    <IntDir>$(Platform)\$(Configuration)\$(ProjectName)\</IntDir>
   </PropertyGroup>
   <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'">
     <ClCompile>
diff --git a/Math/Math/Math.vcxproj b/Math/Math/Math.vcxproj
index d6813ecfb..660bb2cd4 100644
--- a/Math/Math/Math.vcxproj
+++ b/Math/Math/Math.vcxproj
@@ -54,11 +54,13 @@
     <LinkIncremental>true</LinkIncremental>
     <IncludePath>..\..\common\include;$(ACML_PATH)\include;$(CUDA_PATH)\include;$(IncludePath)</IncludePath>
     <LibraryPath>$(SolutionDir)$(Platform)\$(Configuration);$(ACML_PATH)\lib;$(CUDA_PATH)\lib\$(Platform);$(LibraryPath)</LibraryPath>
+    <IntDir>$(Platform)\$(Configuration)\$(ProjectName)\</IntDir>
   </PropertyGroup>
   <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'">
     <LinkIncremental>false</LinkIncremental>
     <IncludePath>..\..\common\include;$(CUDA_PATH)\include;$(ACML_PATH)\include;$(IncludePath)</IncludePath>
     <LibraryPath>$(SolutionDir)$(Platform)\$(Configuration);$(ACML_PATH)\lib;$(CUDA_PATH)\lib\$(Platform);$(LibraryPath)</LibraryPath>
+    <IntDir>$(Platform)\$(Configuration)\$(ProjectName)\</IntDir>
   </PropertyGroup>
   <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'">
     <ClCompile>
@@ -78,8 +80,7 @@
       <SubSystem>Windows</SubSystem>
       <GenerateDebugInformation>true</GenerateDebugInformation>
       <AdditionalDependencies>libacml_mp_dll.lib;%(AdditionalDependencies)</AdditionalDependencies>
-      <AdditionalLibraryDirectories>
-      </AdditionalLibraryDirectories>
+      <AdditionalLibraryDirectories>$(SolutionDir)$(Platform)\$(Configuration)\</AdditionalLibraryDirectories>
       <DelayLoadDLLs>cublas64_70.dll;cusparse64_70.dll;curand64_70.dll;cudart64_70.dll;libacml_dll.dll;libacml_mp_dll.dll;nvcuda.dll;%(DelayLoadDLLs)</DelayLoadDLLs>
       <Profile>true</Profile>
     </Link>
@@ -128,8 +129,7 @@
       <GenerateDebugInformation>true</GenerateDebugInformation>
       <EnableCOMDATFolding>true</EnableCOMDATFolding>
       <OptimizeReferences>true</OptimizeReferences>
-      <AdditionalLibraryDirectories>
-      </AdditionalLibraryDirectories>
+      <AdditionalLibraryDirectories>$(SolutionDir)$(Platform)\$(Configuration)\</AdditionalLibraryDirectories>
       <AdditionalDependencies>libacml_mp_dll.lib;%(AdditionalDependencies)</AdditionalDependencies>
       <Profile>true</Profile>
       <DelayLoadDLLs>cublas64_70.dll;cusparse64_70.dll;curand64_70.dll;cudart64_70.dll;libacml_dll.dll;libacml_mp_dll.dll;nvcuda.dll;%(DelayLoadDLLs)</DelayLoadDLLs>
diff --git a/Math/MathPerformanceTests/MathPerformanceTests.vcxproj b/Math/MathPerformanceTests/MathPerformanceTests.vcxproj
index dd54a2c80..a21a60247 100644
--- a/Math/MathPerformanceTests/MathPerformanceTests.vcxproj
+++ b/Math/MathPerformanceTests/MathPerformanceTests.vcxproj
@@ -1,18 +1,10 @@
 <?xml version="1.0" encoding="utf-8"?>
 <Project DefaultTargets="Build" ToolsVersion="12.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
   <ItemGroup Label="ProjectConfigurations">
-    <ProjectConfiguration Include="Debug|Win32">
-      <Configuration>Debug</Configuration>
-      <Platform>Win32</Platform>
-    </ProjectConfiguration>
     <ProjectConfiguration Include="Debug|x64">
       <Configuration>Debug</Configuration>
       <Platform>x64</Platform>
     </ProjectConfiguration>
-    <ProjectConfiguration Include="Release|Win32">
-      <Configuration>Release</Configuration>
-      <Platform>Win32</Platform>
-    </ProjectConfiguration>
     <ProjectConfiguration Include="Release|x64">
       <Configuration>Release</Configuration>
       <Platform>x64</Platform>
@@ -32,25 +24,12 @@
     <RootNamespace>MathPerformanceTests</RootNamespace>
   </PropertyGroup>
   <Import Project="$(VCTargetsPath)\Microsoft.Cpp.Default.props" />
-  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'" Label="Configuration">
-    <ConfigurationType>Application</ConfigurationType>
-    <UseDebugLibraries>true</UseDebugLibraries>
-    <PlatformToolset>v120</PlatformToolset>
-    <CharacterSet>Unicode</CharacterSet>
-  </PropertyGroup>
   <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'" Label="Configuration">
     <ConfigurationType>Application</ConfigurationType>
     <UseDebugLibraries>true</UseDebugLibraries>
     <PlatformToolset>v120</PlatformToolset>
     <CharacterSet>Unicode</CharacterSet>
   </PropertyGroup>
-  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'" Label="Configuration">
-    <ConfigurationType>Application</ConfigurationType>
-    <UseDebugLibraries>false</UseDebugLibraries>
-    <PlatformToolset>v120</PlatformToolset>
-    <WholeProgramOptimization>true</WholeProgramOptimization>
-    <CharacterSet>Unicode</CharacterSet>
-  </PropertyGroup>
   <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'" Label="Configuration">
     <ConfigurationType>Application</ConfigurationType>
     <UseDebugLibraries>false</UseDebugLibraries>
@@ -62,46 +41,22 @@
   <ImportGroup Label="ExtensionSettings">
     <Import Project="$(VCTargetsPath)\BuildCustomizations\CUDA 7.0.props" />
   </ImportGroup>
-  <ImportGroup Label="PropertySheets" Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">
-    <Import Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" />
-  </ImportGroup>
   <ImportGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'" Label="PropertySheets">
     <Import Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" />
   </ImportGroup>
-  <ImportGroup Label="PropertySheets" Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">
-    <Import Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" />
-  </ImportGroup>
   <ImportGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'" Label="PropertySheets">
     <Import Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" />
   </ImportGroup>
   <PropertyGroup Label="UserMacros" />
-  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">
-    <LinkIncremental>true</LinkIncremental>
-  </PropertyGroup>
   <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'">
     <LinkIncremental>true</LinkIncremental>
     <IncludePath>..\..\common\include\;$(VCInstallDir)include;$(VCInstallDir)atlmfc\include;$(WindowsSDK_IncludePath);</IncludePath>
-  </PropertyGroup>
-  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">
-    <LinkIncremental>false</LinkIncremental>
+    <IntDir>$(Platform)\$(Configuration)\$(ProjectName)\</IntDir>
   </PropertyGroup>
   <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'">
     <LinkIncremental>false</LinkIncremental>
+    <IntDir>$(Platform)\$(Configuration)\$(ProjectName)\</IntDir>
   </PropertyGroup>
-  <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">
-    <ClCompile>
-      <PrecompiledHeader>Use</PrecompiledHeader>
-      <WarningLevel>Level3</WarningLevel>
-      <Optimization>Disabled</Optimization>
-      <PreprocessorDefinitions>WIN32;_DEBUG;_CONSOLE;%(PreprocessorDefinitions)</PreprocessorDefinitions>
-      <SDLCheck>true</SDLCheck>
-    </ClCompile>
-    <Link>
-      <SubSystem>Console</SubSystem>
-      <GenerateDebugInformation>true</GenerateDebugInformation>
-      <AdditionalDependencies>winmm.lib;%(AdditionalDependencies)</AdditionalDependencies>
-    </Link>
-  </ItemDefinitionGroup>
   <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'">
     <ClCompile>
       <PrecompiledHeader>Use</PrecompiledHeader>
@@ -121,23 +76,6 @@
       <CodeGeneration>compute_20,sm_20;compute_30,sm_30;%(CodeGeneration)</CodeGeneration>
     </CudaCompile>
   </ItemDefinitionGroup>
-  <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">
-    <ClCompile>
-      <WarningLevel>Level3</WarningLevel>
-      <PrecompiledHeader>Use</PrecompiledHeader>
-      <Optimization>MaxSpeed</Optimization>
-      <FunctionLevelLinking>true</FunctionLevelLinking>
-      <IntrinsicFunctions>true</IntrinsicFunctions>
-      <PreprocessorDefinitions>WIN32;NDEBUG;_CONSOLE;%(PreprocessorDefinitions)</PreprocessorDefinitions>
-      <SDLCheck>true</SDLCheck>
-    </ClCompile>
-    <Link>
-      <SubSystem>Console</SubSystem>
-      <GenerateDebugInformation>true</GenerateDebugInformation>
-      <EnableCOMDATFolding>true</EnableCOMDATFolding>
-      <OptimizeReferences>true</OptimizeReferences>
-    </Link>
-  </ItemDefinitionGroup>
   <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'">
     <ClCompile>
       <WarningLevel>Level4</WarningLevel>
@@ -168,9 +106,7 @@
   <ItemGroup>
     <ClCompile Include="MathPerformanceTests.cpp" />
     <ClCompile Include="stdafx.cpp">
-      <PrecompiledHeader Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">Create</PrecompiledHeader>
       <PrecompiledHeader Condition="'$(Configuration)|$(Platform)'=='Debug|x64'">Create</PrecompiledHeader>
-      <PrecompiledHeader Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">Create</PrecompiledHeader>
       <PrecompiledHeader Condition="'$(Configuration)|$(Platform)'=='Release|x64'">Create</PrecompiledHeader>
     </ClCompile>
   </ItemGroup>
diff --git a/README b/README
index 335a6b36b..95f7002e1 100644
--- a/README
+++ b/README
@@ -25,6 +25,8 @@ You can modify the path CUDA_PATH in makefile.cpu to change your cuda path
 We use cuda-7.0 as default.
 Then add ${CUDA_PATH}/lib, ${CUDA_PATH}/lib64 to your ${LD_LIBRARY_PATH} to make sure the program links to the library correctly.
 
+... TODO: add documentation on nvml lib
+
 == Build ==
 To build the cpu version, run
 	make -f Makefile.cpu 

From 16a481ac775650aad032c9ae27f3f251f634373f Mon Sep 17 00:00:00 2001
From: Frank Seide <fseide@microsoft.com>
Date: Mon, 18 May 2015 19:02:34 -0700
Subject: [PATCH 27/49] fixed (removed) Win32 again

---
 CNTK.sln            | 435 +++++++++++++++++---------------------------
 Linux/Linux.vcxproj |  20 +-
 2 files changed, 178 insertions(+), 277 deletions(-)

diff --git a/CNTK.sln b/CNTK.sln
index 3cd282cb6..0d4780cd0 100644
--- a/CNTK.sln
+++ b/CNTK.sln
@@ -1,267 +1,168 @@
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-# Visual Studio 2013
-VisualStudioVersion = 12.0.21005.1
-MinimumVisualStudioVersion = 10.0.40219.1
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-	ProjectSection(ProjectDependencies) = postProject
-		{B3DD765E-694E-4494-BAD7-37BBF2942517} = {B3DD765E-694E-4494-BAD7-37BBF2942517}
-	EndProjectSection
-EndProject
-Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "CNTK", "MachineLearning\CNTK\CNTK.vcxproj", "{E6F26F9A-FF64-4F0A-B749-CD309EE357EE}"
-	ProjectSection(ProjectDependencies) = postProject
-		{33D2FD22-DEF2-4507-A58A-368F641AEBE5} = {33D2FD22-DEF2-4507-A58A-368F641AEBE5}
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-		{60BDB847-D0C4-4FD3-A947-0C15C08BCDB5} = {60BDB847-D0C4-4FD3-A947-0C15C08BCDB5}
-		{B3DD765E-694E-4494-BAD7-37BBF2942517} = {B3DD765E-694E-4494-BAD7-37BBF2942517}
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-	EndProjectSection
-EndProject
-Project("{2150E333-8FDC-42A3-9474-1A3956D46DE8}") = "Unit Tests", "Unit Tests", "{D45DF403-6781-444E-B654-A96868C5BE68}"
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-Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "CNTKMathTest", "Math\CNTKMathTest\CNTKMathTest.vcxproj", "{6CEE834A-8104-46A8-8902-64C81BD7928F}"
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-Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "MathPerformanceTests", "Math\MathPerformanceTests\MathPerformanceTests.vcxproj", "{668BEED5-AC07-4F35-B3AE-EE65A7F9C976}"
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-	ProjectSection(ProjectDependencies) = postProject
-		{60BDB847-D0C4-4FD3-A947-0C15C08BCDB5} = {60BDB847-D0C4-4FD3-A947-0C15C08BCDB5}
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-		{60BDB847-D0C4-4FD3-A947-0C15C08BCDB5} = {60BDB847-D0C4-4FD3-A947-0C15C08BCDB5}
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-Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "LUSequenceReader", "DataReader\LUSequenceReader\LUSequenceReader.vcxproj", "{62836DC1-DF77-4B98-BF2D-45C943B7DDC6}"
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-	ProjectSection(ProjectDependencies) = postProject
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+		{33D2FD22-DEF2-4507-A58A-368F641AEBE5}.Release|x64.ActiveCfg = Release|x64
+		{33D2FD22-DEF2-4507-A58A-368F641AEBE5}.Release|x64.Build.0 = Release|x64
+		{668BEED5-AC07-4F35-B3AE-EE65A7F9C976}.Debug|x64.ActiveCfg = Debug|x64
+		{668BEED5-AC07-4F35-B3AE-EE65A7F9C976}.Debug|x64.Build.0 = Debug|x64
+		{668BEED5-AC07-4F35-B3AE-EE65A7F9C976}.Release|x64.ActiveCfg = Release|x64
+		{E6646FFE-3588-4276-8A15-8D65C22711C1}.Debug|x64.ActiveCfg = Debug|x64
+		{E6646FFE-3588-4276-8A15-8D65C22711C1}.Debug|x64.Build.0 = Debug|x64
+		{E6646FFE-3588-4276-8A15-8D65C22711C1}.Release|x64.ActiveCfg = Release|x64
+		{E6646FFE-3588-4276-8A15-8D65C22711C1}.Release|x64.Build.0 = Release|x64
+		{1D5787D4-52E4-45DB-951B-82F220EE0C6A}.Debug|x64.ActiveCfg = Debug|x64
+		{1D5787D4-52E4-45DB-951B-82F220EE0C6A}.Debug|x64.Build.0 = Debug|x64
+		{1D5787D4-52E4-45DB-951B-82F220EE0C6A}.Release|x64.ActiveCfg = Release|x64
+		{1D5787D4-52E4-45DB-951B-82F220EE0C6A}.Release|x64.Build.0 = Release|x64
+		{62836DC1-DF77-4B98-BF2D-45C943B7DDC6}.Debug|x64.ActiveCfg = Debug|x64
+		{62836DC1-DF77-4B98-BF2D-45C943B7DDC6}.Debug|x64.Build.0 = Debug|x64
+		{62836DC1-DF77-4B98-BF2D-45C943B7DDC6}.Release|x64.ActiveCfg = Release|x64
+		{62836DC1-DF77-4B98-BF2D-45C943B7DDC6}.Release|x64.Build.0 = Release|x64
+		{482999D1-B7E2-466E-9F8D-2119F93EAFD9}.Debug|x64.ActiveCfg = Debug|x64
+		{482999D1-B7E2-466E-9F8D-2119F93EAFD9}.Debug|x64.Build.0 = Debug|x64
+		{482999D1-B7E2-466E-9F8D-2119F93EAFD9}.Release|x64.ActiveCfg = Release|x64
+		{482999D1-B7E2-466E-9F8D-2119F93EAFD9}.Release|x64.Build.0 = Release|x64
+		{0F30EBCF-09F3-4EED-BF54-4214BCE53FEC}.Debug|x64.ActiveCfg = Debug|x64
+		{0F30EBCF-09F3-4EED-BF54-4214BCE53FEC}.Debug|x64.Build.0 = Debug|x64
+		{0F30EBCF-09F3-4EED-BF54-4214BCE53FEC}.Release|x64.ActiveCfg = Release|x64
+		{B3DD765E-694E-4494-BAD7-37BBF2942517}.Debug|x64.ActiveCfg = Debug|x64
+		{B3DD765E-694E-4494-BAD7-37BBF2942517}.Debug|x64.Build.0 = Debug|x64
+		{B3DD765E-694E-4494-BAD7-37BBF2942517}.Release|x64.ActiveCfg = Release|x64
+		{B3DD765E-694E-4494-BAD7-37BBF2942517}.Release|x64.Build.0 = Release|x64
+		{9A2F2441-5972-4EA8-9215-4119FCE0FB68}.Debug|x64.ActiveCfg = Debug|x64
+		{9A2F2441-5972-4EA8-9215-4119FCE0FB68}.Debug|x64.Build.0 = Debug|x64
+		{9A2F2441-5972-4EA8-9215-4119FCE0FB68}.Release|x64.ActiveCfg = Release|x64
+		{9A2F2441-5972-4EA8-9215-4119FCE0FB68}.Release|x64.Build.0 = Release|x64
+		{014DA766-B37B-4581-BC26-963EA5507931}.Debug|x64.ActiveCfg = Debug|x64
+		{014DA766-B37B-4581-BC26-963EA5507931}.Debug|x64.Build.0 = Debug|x64
+		{014DA766-B37B-4581-BC26-963EA5507931}.Release|x64.ActiveCfg = Release|x64
+		{014DA766-B37B-4581-BC26-963EA5507931}.Release|x64.Build.0 = Release|x64
+		{D667AF32-028A-4A5D-BE19-F46776F0F6B2}.Debug|x64.ActiveCfg = Debug|x64
+		{D667AF32-028A-4A5D-BE19-F46776F0F6B2}.Debug|x64.Build.0 = Debug|x64
+		{D667AF32-028A-4A5D-BE19-F46776F0F6B2}.Release|x64.ActiveCfg = Release|x64
+		{D667AF32-028A-4A5D-BE19-F46776F0F6B2}.Release|x64.Build.0 = Release|x64
+		{9216C53F-46EB-4669-B781-FF8503F27157}.Debug|x64.ActiveCfg = Debug|x64
+		{9216C53F-46EB-4669-B781-FF8503F27157}.Debug|x64.Build.0 = Debug|x64
+		{9216C53F-46EB-4669-B781-FF8503F27157}.Release|x64.ActiveCfg = Release|x64
+		{9216C53F-46EB-4669-B781-FF8503F27157}.Release|x64.Build.0 = Release|x64
+		{E7AD9034-C010-4FC7-9768-E7EE4EE94FFF}.Debug|x64.ActiveCfg = Debug|x64
+		{E7AD9034-C010-4FC7-9768-E7EE4EE94FFF}.Debug|x64.Build.0 = Debug|x64
+		{E7AD9034-C010-4FC7-9768-E7EE4EE94FFF}.Release|x64.ActiveCfg = Release|x64
+		{E7AD9034-C010-4FC7-9768-E7EE4EE94FFF}.Release|x64.Build.0 = Release|x64
+	EndGlobalSection
+	GlobalSection(SolutionProperties) = preSolution
+		HideSolutionNode = FALSE
+	EndGlobalSection
+	GlobalSection(NestedProjects) = preSolution
+		{E6F26F9A-FF64-4F0A-B749-CD309EE357EE} = {DD043083-71A4-409A-AA91-F9C548DCF7EC}
+		{482999D1-B7E2-466E-9F8D-2119F93EAFD9} = {DD043083-71A4-409A-AA91-F9C548DCF7EC}
+		{60BDB847-D0C4-4FD3-A947-0C15C08BCDB5} = {DD043083-71A4-409A-AA91-F9C548DCF7EC}
+		{B3DD765E-694E-4494-BAD7-37BBF2942517} = {DD043083-71A4-409A-AA91-F9C548DCF7EC}
+		{E7AD9034-C010-4FC7-9768-E7EE4EE94FFF} = {DD043083-71A4-409A-AA91-F9C548DCF7EC}
+		{6CEE834A-8104-46A8-8902-64C81BD7928F} = {D45DF403-6781-444E-B654-A96868C5BE68}
+		{668BEED5-AC07-4F35-B3AE-EE65A7F9C976} = {D45DF403-6781-444E-B654-A96868C5BE68}
+		{0F30EBCF-09F3-4EED-BF54-4214BCE53FEC} = {D45DF403-6781-444E-B654-A96868C5BE68}
+		{E6646FFE-3588-4276-8A15-8D65C22711C1} = {33EBFE78-A1A8-4961-8938-92A271941F94}
+		{1D5787D4-52E4-45DB-951B-82F220EE0C6A} = {33EBFE78-A1A8-4961-8938-92A271941F94}
+		{62836DC1-DF77-4B98-BF2D-45C943B7DDC6} = {33EBFE78-A1A8-4961-8938-92A271941F94}
+		{33D2FD22-DEF2-4507-A58A-368F641AEBE5} = {33EBFE78-A1A8-4961-8938-92A271941F94}
+		{9A2F2441-5972-4EA8-9215-4119FCE0FB68} = {33EBFE78-A1A8-4961-8938-92A271941F94}
+		{014DA766-B37B-4581-BC26-963EA5507931} = {33EBFE78-A1A8-4961-8938-92A271941F94}
+		{D667AF32-028A-4A5D-BE19-F46776F0F6B2} = {33EBFE78-A1A8-4961-8938-92A271941F94}
+	EndGlobalSection
+EndGlobal
diff --git a/Linux/Linux.vcxproj b/Linux/Linux.vcxproj
index d33be25ef..18ef54e01 100644
--- a/Linux/Linux.vcxproj
+++ b/Linux/Linux.vcxproj
@@ -1,13 +1,13 @@
 <?xml version="1.0" encoding="utf-8"?>
 <Project DefaultTargets="Build" ToolsVersion="12.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
   <ItemGroup Label="ProjectConfigurations">
-    <ProjectConfiguration Include="Debug|Win32">
+    <ProjectConfiguration Include="Debug|x64">
       <Configuration>Debug</Configuration>
-      <Platform>Win32</Platform>
+      <Platform>x64</Platform>
     </ProjectConfiguration>
-    <ProjectConfiguration Include="Release|Win32">
+    <ProjectConfiguration Include="Release|x64">
       <Configuration>Release</Configuration>
-      <Platform>Win32</Platform>
+      <Platform>x64</Platform>
     </ProjectConfiguration>
   </ItemGroup>
   <PropertyGroup Label="Globals">
@@ -15,13 +15,13 @@
     <RootNamespace>Linux</RootNamespace>
   </PropertyGroup>
   <Import Project="$(VCTargetsPath)\Microsoft.Cpp.Default.props" />
-  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'" Label="Configuration">
+  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'" Label="Configuration">
     <ConfigurationType>Application</ConfigurationType>
     <UseDebugLibraries>true</UseDebugLibraries>
     <PlatformToolset>v120</PlatformToolset>
     <CharacterSet>MultiByte</CharacterSet>
   </PropertyGroup>
-  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'" Label="Configuration">
+  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'" Label="Configuration">
     <ConfigurationType>Application</ConfigurationType>
     <UseDebugLibraries>false</UseDebugLibraries>
     <PlatformToolset>v120</PlatformToolset>
@@ -31,15 +31,15 @@
   <Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
   <ImportGroup Label="ExtensionSettings">
   </ImportGroup>
-  <ImportGroup Label="PropertySheets" Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">
+  <ImportGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'" Label="PropertySheets">
     <Import Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" />
   </ImportGroup>
-  <ImportGroup Label="PropertySheets" Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">
+  <ImportGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'" Label="PropertySheets">
     <Import Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" />
   </ImportGroup>
   <PropertyGroup Label="UserMacros" />
   <PropertyGroup />
-  <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">
+  <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'">
     <ClCompile>
       <WarningLevel>Level3</WarningLevel>
       <Optimization>Disabled</Optimization>
@@ -49,7 +49,7 @@
       <GenerateDebugInformation>true</GenerateDebugInformation>
     </Link>
   </ItemDefinitionGroup>
-  <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">
+  <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'">
     <ClCompile>
       <WarningLevel>Level3</WarningLevel>
       <Optimization>MaxSpeed</Optimization>

From 08625d482d7b7c11ae460ba4a31c409bb1386e99 Mon Sep 17 00:00:00 2001
From: Frank Seide <fseide@microsoft.com>
Date: Mon, 18 May 2015 19:36:04 -0700
Subject: [PATCH 28/49] created a new header file Basics.h, to take on the
 whole of the legacy basetypes.h (which was to contain a very limited set of
 generally useful core functions, like UTF8 conversion)

---
 Common/DataReader.cpp                         |  2 +-
 Common/Eval.cpp                               |  2 +-
 Common/File.cpp                               |  2 +-
 Common/Include/Basics.h                       | 21 +++++++++++++++++++
 Common/Include/DataReader.h                   |  2 +-
 Common/Include/DataWriter.h                   |  2 +-
 Common/Include/Eval.h                         |  2 +-
 Common/Include/commandArgUtil.h               |  2 +-
 Common/fileutil.cpp                           |  2 +-
 DataReader/BinaryReader/BinaryWriter.cpp      |  2 +-
 .../DSSMReader/minibatchsourcehelpers.h       |  2 +-
 .../LMSequenceReader/SequenceParser.cpp       |  2 +-
 .../LMSequenceReader/minibatchsourcehelpers.h |  2 +-
 DataReader/LUSequenceReader/DataWriter.cpp    |  2 +-
 .../LUSequenceReader/LUSequenceWriter.cpp     |  2 +-
 .../LUSequenceReader/minibatchsourcehelpers.h |  2 +-
 .../minibatchsourcehelpers.h                  |  2 +-
 .../UCIFastReader/minibatchsourcehelpers.h    |  2 +-
 MachineLearning/CNTK/CNTK.vcxproj             |  1 +
 MachineLearning/CNTK/CNTK.vcxproj.filters     |  3 +++
 .../CNTK/ComputationNetworkHelper.h           |  2 +-
 MachineLearning/CNTK/ComputationNode.h        |  2 +-
 MachineLearning/CNTK/NDLNetworkBuilder.h      |  2 +-
 MachineLearning/CNTK/NDLUtil.h                |  2 +-
 MachineLearning/CNTK/SGD.h                    |  2 +-
 MachineLearning/CNTK/SimpleEvaluator.h        |  2 +-
 MachineLearning/CNTK/SimpleNetworkBuilder.h   |  2 +-
 MachineLearning/CNTK/SimpleOutputWriter.h     |  2 +-
 MachineLearning/CNTK/tests.cpp                |  2 +-
 Math/Math/CPUMatrix.cpp                       |  2 +-
 Math/Math/CPUMatrix.h                         |  2 +-
 Math/Math/CPUSparseMatrix.cpp                 |  2 +-
 Math/Math/Matrix.cpp                          |  2 +-
 33 files changed, 55 insertions(+), 30 deletions(-)
 create mode 100644 Common/Include/Basics.h

diff --git a/Common/DataReader.cpp b/Common/DataReader.cpp
index d41682a37..b7f5ad2de 100644
--- a/Common/DataReader.cpp
+++ b/Common/DataReader.cpp
@@ -8,7 +8,7 @@
 
 #include "stdafx.h"
 #define DATAREADER_LOCAL
-#include "basetypes.h"
+#include "Basics.h"
 #include "DataReader.h"
 
 namespace Microsoft { namespace MSR { namespace CNTK {
diff --git a/Common/Eval.cpp b/Common/Eval.cpp
index 18ecd2c5b..3704f27c2 100644
--- a/Common/Eval.cpp
+++ b/Common/Eval.cpp
@@ -9,7 +9,7 @@
 #define _CRT_SECURE_NO_WARNINGS // "secure" CRT not available on all platforms  --add this at the top of all CPP files that give "function or variable may be unsafe" warnings
 
 #include "stdafx.h"
-#include "basetypes.h"
+#include "Basics.h"
 #define EVAL_LOCAL
 #include "Eval.h"
 
diff --git a/Common/File.cpp b/Common/File.cpp
index 2ba0c1ef8..3ca67301d 100644
--- a/Common/File.cpp
+++ b/Common/File.cpp
@@ -8,7 +8,7 @@
 #define _CRT_SECURE_NO_WARNINGS // "secure" CRT not available on all platforms  --add this at the top of all CPP files that give "function or variable may be unsafe" warnings
 #endif
 
-#include "basetypes.h"
+#include "Basics.h"
 #define FORMAT_SPECIALIZE // to get the specialized version of the format routines
 #include "fileutil.h"
 #include "File.h"
diff --git a/Common/Include/Basics.h b/Common/Include/Basics.h
new file mode 100644
index 000000000..48695d669
--- /dev/null
+++ b/Common/Include/Basics.h
@@ -0,0 +1,21 @@
+// Basics.h -- some shared generally useful pieces of code used by CNTK
+//
+// We also include a simple "emulation" layer for some proprietary MSVC CRT functions.
+
+#pragma once
+
+#ifndef _BASICS_H_
+#define _BASICS_H_
+
+#include "basetypes.h"  // TODO: gradually move over here all that's needed of basetypes.h, then remove basetypes.h.
+
+
+// ===========================================================================
+// emulation of some MSVC proprietary CRT
+// ===========================================================================
+
+#ifndef _MSC_VER
+static inline int _wsystem(const wchar_t *command) { return system(msra::strfun::utf8(command).c_str()); }
+#endif
+
+#endif // _BASICS_H_
diff --git a/Common/Include/DataReader.h b/Common/Include/DataReader.h
index b90532671..a309b1fdb 100644
--- a/Common/Include/DataReader.h
+++ b/Common/Include/DataReader.h
@@ -25,7 +25,7 @@
 #include "Matrix.h"
 #include <map>
 #include <string>
-#include "basetypes.h"
+#include "Basics.h"
 #include "commandArgUtil.h"
 
 namespace Microsoft { namespace MSR { namespace CNTK {
diff --git a/Common/Include/DataWriter.h b/Common/Include/DataWriter.h
index 227d7861e..a5ce6fb7e 100644
--- a/Common/Include/DataWriter.h
+++ b/Common/Include/DataWriter.h
@@ -23,7 +23,7 @@
 #define DATAWRITER_API
 #endif
 
-#include "basetypes.h"
+#include "Basics.h"
 #include "Matrix.h"
 #include <map>
 #include <string>
diff --git a/Common/Include/Eval.h b/Common/Include/Eval.h
index c61975afe..a0dbfd6b1 100644
--- a/Common/Include/Eval.h
+++ b/Common/Include/Eval.h
@@ -23,7 +23,7 @@
 #define EVAL_API
 #endif
 
-#include "basetypes.h"
+#include "Basics.h"
 #include <map>
 #include <vector>
 #include <string>
diff --git a/Common/Include/commandArgUtil.h b/Common/Include/commandArgUtil.h
index 8fe56f82d..6c2094e9e 100644
--- a/Common/Include/commandArgUtil.h
+++ b/Common/Include/commandArgUtil.h
@@ -4,7 +4,7 @@
 // </copyright>
 //
 #pragma once
-#include "basetypes.h"
+#include "Basics.h"
 #include <vector>
 #include <string>
 #include <map>
diff --git a/Common/fileutil.cpp b/Common/fileutil.cpp
index f3e58160a..19e1caed7 100644
--- a/Common/fileutil.cpp
+++ b/Common/fileutil.cpp
@@ -18,7 +18,7 @@
 #endif
 #define _CRT_SECURE_CPP_OVERLOAD_STANDARD_NAMES 1
 #endif
-#include "basetypes.h"
+#include "Basics.h"
 #include "fileutil.h"
 #ifdef __unix__
 #include <sys/types.h>
diff --git a/DataReader/BinaryReader/BinaryWriter.cpp b/DataReader/BinaryReader/BinaryWriter.cpp
index 5655cdb4a..c30a22b32 100644
--- a/DataReader/BinaryReader/BinaryWriter.cpp
+++ b/DataReader/BinaryReader/BinaryWriter.cpp
@@ -7,7 +7,7 @@
 //
 
 #include "stdafx.h"
-#include "basetypes.h"
+#include "Basics.h"
 #define DATAWRITER_EXPORTS  // creating the exports here
 #include "DataWriter.h"
 #include "BinaryReader.h"
diff --git a/DataReader/DSSMReader/minibatchsourcehelpers.h b/DataReader/DSSMReader/minibatchsourcehelpers.h
index d1237a34f..f87c8bb94 100644
--- a/DataReader/DSSMReader/minibatchsourcehelpers.h
+++ b/DataReader/DSSMReader/minibatchsourcehelpers.h
@@ -8,7 +8,7 @@
 
 #pragma once
 
-#include "basetypes.h"
+#include "Basics.h"
 #include <stdio.h>
 #include <vector>
 #include <algorithm>
diff --git a/DataReader/LMSequenceReader/SequenceParser.cpp b/DataReader/LMSequenceReader/SequenceParser.cpp
index 945398a18..c04861560 100644
--- a/DataReader/LMSequenceReader/SequenceParser.cpp
+++ b/DataReader/LMSequenceReader/SequenceParser.cpp
@@ -7,7 +7,7 @@
 //
 
 #include "stdafx.h"
-#include "basetypes.h"
+#include "Basics.h"
 #include "SequenceParser.h"
 #include <stdexcept>
 #include <stdint.h>
diff --git a/DataReader/LMSequenceReader/minibatchsourcehelpers.h b/DataReader/LMSequenceReader/minibatchsourcehelpers.h
index 624752c4a..395522a37 100644
--- a/DataReader/LMSequenceReader/minibatchsourcehelpers.h
+++ b/DataReader/LMSequenceReader/minibatchsourcehelpers.h
@@ -8,7 +8,7 @@
 
 #pragma once
 
-#include "basetypes.h"
+#include "Basics.h"
 #include <stdio.h>
 #include <vector>
 #include <algorithm>
diff --git a/DataReader/LUSequenceReader/DataWriter.cpp b/DataReader/LUSequenceReader/DataWriter.cpp
index 34a041f57..41b8adfc0 100644
--- a/DataReader/LUSequenceReader/DataWriter.cpp
+++ b/DataReader/LUSequenceReader/DataWriter.cpp
@@ -7,7 +7,7 @@
 //
 
 #include "stdafx.h"
-#include "basetypes.h"
+#include "Basics.h"
 
 #define DATAWRITER_EXPORTS
 #include "DataWriter.h"
diff --git a/DataReader/LUSequenceReader/LUSequenceWriter.cpp b/DataReader/LUSequenceReader/LUSequenceWriter.cpp
index a8714cf45..dc1555502 100644
--- a/DataReader/LUSequenceReader/LUSequenceWriter.cpp
+++ b/DataReader/LUSequenceReader/LUSequenceWriter.cpp
@@ -8,7 +8,7 @@
 
 #include "stdafx.h"
 #include <objbase.h>
-#include "basetypes.h"
+#include "Basics.h"
 #include <fstream>
 #include <algorithm>
 
diff --git a/DataReader/LUSequenceReader/minibatchsourcehelpers.h b/DataReader/LUSequenceReader/minibatchsourcehelpers.h
index 8dd0ab9d8..26d6068c2 100644
--- a/DataReader/LUSequenceReader/minibatchsourcehelpers.h
+++ b/DataReader/LUSequenceReader/minibatchsourcehelpers.h
@@ -9,7 +9,7 @@
 
 #pragma once
 
-#include "basetypes.h"
+#include "Basics.h"
 #include <stdio.h>
 #include <vector>
 #include <algorithm>
diff --git a/DataReader/LibSVMBinaryReader/minibatchsourcehelpers.h b/DataReader/LibSVMBinaryReader/minibatchsourcehelpers.h
index d1237a34f..f87c8bb94 100644
--- a/DataReader/LibSVMBinaryReader/minibatchsourcehelpers.h
+++ b/DataReader/LibSVMBinaryReader/minibatchsourcehelpers.h
@@ -8,7 +8,7 @@
 
 #pragma once
 
-#include "basetypes.h"
+#include "Basics.h"
 #include <stdio.h>
 #include <vector>
 #include <algorithm>
diff --git a/DataReader/UCIFastReader/minibatchsourcehelpers.h b/DataReader/UCIFastReader/minibatchsourcehelpers.h
index 624752c4a..395522a37 100644
--- a/DataReader/UCIFastReader/minibatchsourcehelpers.h
+++ b/DataReader/UCIFastReader/minibatchsourcehelpers.h
@@ -8,7 +8,7 @@
 
 #pragma once
 
-#include "basetypes.h"
+#include "Basics.h"
 #include <stdio.h>
 #include <vector>
 #include <algorithm>
diff --git a/MachineLearning/CNTK/CNTK.vcxproj b/MachineLearning/CNTK/CNTK.vcxproj
index bc8774852..b72655823 100644
--- a/MachineLearning/CNTK/CNTK.vcxproj
+++ b/MachineLearning/CNTK/CNTK.vcxproj
@@ -153,6 +153,7 @@
   <ItemGroup>
     <ClInclude Include="..\..\Common\hostname.h" />
     <ClInclude Include="..\..\Common\Include\basetypes.h" />
+    <ClInclude Include="..\..\Common\Include\Basics.h" />
     <ClInclude Include="..\..\Common\Include\BestGpu.h" />
     <ClInclude Include="..\..\Common\Include\commandArgUtil.h" />
     <ClInclude Include="..\..\Common\Include\DataReader.h" />
diff --git a/MachineLearning/CNTK/CNTK.vcxproj.filters b/MachineLearning/CNTK/CNTK.vcxproj.filters
index 897a06e88..2af1d2fb5 100644
--- a/MachineLearning/CNTK/CNTK.vcxproj.filters
+++ b/MachineLearning/CNTK/CNTK.vcxproj.filters
@@ -133,6 +133,9 @@
     <ClInclude Include="..\..\Common\Include\TimerUtility.h">
       <Filter>Common\Include</Filter>
     </ClInclude>
+    <ClInclude Include="..\..\Common\Include\Basics.h">
+      <Filter>Common\Include</Filter>
+    </ClInclude>
   </ItemGroup>
   <ItemGroup>
     <Text Include="modelEditor.txt">
diff --git a/MachineLearning/CNTK/ComputationNetworkHelper.h b/MachineLearning/CNTK/ComputationNetworkHelper.h
index 642a95e7c..f0973cac4 100644
--- a/MachineLearning/CNTK/ComputationNetworkHelper.h
+++ b/MachineLearning/CNTK/ComputationNetworkHelper.h
@@ -10,7 +10,7 @@
 #include <vector>
 #include <string>
 #include <stdexcept>
-#include "basetypes.h"
+#include "Basics.h"
 #include "fileutil.h"
 #include "commandArgUtil.h"
 //#include <Windows.h>
diff --git a/MachineLearning/CNTK/ComputationNode.h b/MachineLearning/CNTK/ComputationNode.h
index 0c6e5f9e7..42c76f827 100644
--- a/MachineLearning/CNTK/ComputationNode.h
+++ b/MachineLearning/CNTK/ComputationNode.h
@@ -14,7 +14,7 @@
 #include <memory>
 #include <algorithm>
 #include <assert.h>
-#include "basetypes.h"
+#include "Basics.h"
 #include <atomic>
 #include <sstream>
 #include <Matrix.h>
diff --git a/MachineLearning/CNTK/NDLNetworkBuilder.h b/MachineLearning/CNTK/NDLNetworkBuilder.h
index 4f24f1343..70bd94ec8 100644
--- a/MachineLearning/CNTK/NDLNetworkBuilder.h
+++ b/MachineLearning/CNTK/NDLNetworkBuilder.h
@@ -8,7 +8,7 @@
 #include "ComputationNetwork.h"
 #include "IComputationNetBuilder.h"
 #include "IExecutionEngine.h"
-#include "basetypes.h"
+#include "Basics.h"
 #include <string>
 #include "commandArgUtil.h"
 #include "DataReader.h"
diff --git a/MachineLearning/CNTK/NDLUtil.h b/MachineLearning/CNTK/NDLUtil.h
index 97d9770a5..05f4a80e4 100644
--- a/MachineLearning/CNTK/NDLUtil.h
+++ b/MachineLearning/CNTK/NDLUtil.h
@@ -6,7 +6,7 @@
 
 #pragma once
 
-#include "basetypes.h"
+#include "Basics.h"
 #include "NetworkDescriptionLanguage.h"
 #include "ComputationNetwork.h"
 #include "SynchronousExecutionEngine.h"
diff --git a/MachineLearning/CNTK/SGD.h b/MachineLearning/CNTK/SGD.h
index 43af53faf..e48f83212 100644
--- a/MachineLearning/CNTK/SGD.h
+++ b/MachineLearning/CNTK/SGD.h
@@ -5,7 +5,7 @@
 //
 #pragma once
 
-#include "basetypes.h"
+#include "Basics.h"
 #include "ComputationNetwork.h"
 #include "ComputationNetworkHelper.h"
 #include "SimpleEvaluator.h"
diff --git a/MachineLearning/CNTK/SimpleEvaluator.h b/MachineLearning/CNTK/SimpleEvaluator.h
index f31801087..10efd000d 100644
--- a/MachineLearning/CNTK/SimpleEvaluator.h
+++ b/MachineLearning/CNTK/SimpleEvaluator.h
@@ -11,7 +11,7 @@
 #include <vector>
 #include <string>
 #include <stdexcept>
-#include "basetypes.h"
+#include "Basics.h"
 #include "fileutil.h"
 #include "commandArgUtil.h"
 #include <fstream>
diff --git a/MachineLearning/CNTK/SimpleNetworkBuilder.h b/MachineLearning/CNTK/SimpleNetworkBuilder.h
index 587fef540..c808fe8c5 100644
--- a/MachineLearning/CNTK/SimpleNetworkBuilder.h
+++ b/MachineLearning/CNTK/SimpleNetworkBuilder.h
@@ -5,7 +5,7 @@
 //
 #pragma once
 
-#include "basetypes.h"
+#include "Basics.h"
 #include "ComputationNetwork.h"
 #include "IComputationNetBuilder.h"
 #include <string>
diff --git a/MachineLearning/CNTK/SimpleOutputWriter.h b/MachineLearning/CNTK/SimpleOutputWriter.h
index 82de8fd05..961313d2d 100644
--- a/MachineLearning/CNTK/SimpleOutputWriter.h
+++ b/MachineLearning/CNTK/SimpleOutputWriter.h
@@ -11,7 +11,7 @@
 #include <vector>
 #include <string>
 #include <stdexcept>
-#include "basetypes.h"
+#include "Basics.h"
 #include "fileutil.h"
 #include "commandArgUtil.h"
 #include <fstream>
diff --git a/MachineLearning/CNTK/tests.cpp b/MachineLearning/CNTK/tests.cpp
index 406b9ae00..d1e61b2a4 100644
--- a/MachineLearning/CNTK/tests.cpp
+++ b/MachineLearning/CNTK/tests.cpp
@@ -7,7 +7,7 @@
 //
 
 #include "stdafx.h"
-#include "basetypes.h"
+#include "Basics.h"
 #include "ComputationNetwork.h"
 #include "ComputationNode.h"
 #include "DataReader.h"
diff --git a/Math/Math/CPUMatrix.cpp b/Math/Math/CPUMatrix.cpp
index 61f87f781..799c7c393 100644
--- a/Math/Math/CPUMatrix.cpp
+++ b/Math/Math/CPUMatrix.cpp
@@ -7,7 +7,7 @@
 //
 
 #include "stdafx.h"
-#include "basetypes.h"
+#include "Basics.h"
 #include "fileutil.h"
 
 #include <assert.h>
diff --git a/Math/Math/CPUMatrix.h b/Math/Math/CPUMatrix.h
index f6199aef0..457684a36 100644
--- a/Math/Math/CPUMatrix.h
+++ b/Math/Math/CPUMatrix.h
@@ -11,7 +11,7 @@
 #include "File.h"
 #include "Helpers.h"
 #include "CommonMatrix.h"
-#include "basetypes.h" // for RuntimeError()
+#include "Basics.h" // for RuntimeError()
 
 #ifdef    _WIN32
 #ifdef MATH_EXPORTS
diff --git a/Math/Math/CPUSparseMatrix.cpp b/Math/Math/CPUSparseMatrix.cpp
index 20c268e0c..3b9066899 100644
--- a/Math/Math/CPUSparseMatrix.cpp
+++ b/Math/Math/CPUSparseMatrix.cpp
@@ -22,7 +22,7 @@
 #include <vld.h>
 #endif
 
-#include "basetypes.h"
+#include "Basics.h"
 #include "fileutil.h"
 #include <iostream>
 #pragma warning (disable: 4127) // conditional expression is constant; "if (sizeof(ElemType)==sizeof(float))" triggers this
diff --git a/Math/Math/Matrix.cpp b/Math/Math/Matrix.cpp
index 6738867a3..4ca74f692 100644
--- a/Math/Math/Matrix.cpp
+++ b/Math/Math/Matrix.cpp
@@ -5,7 +5,7 @@
 // </copyright>
 //
 #include "stdafx.h"
-#include "basetypes.h"
+#include "Basics.h"
 #include "fileutil.h"
 #include "Matrix.h"
 #include <assert.h>

From 178555d0a4797bf79a3e0ae680ab6ddd7fa8dd2e Mon Sep 17 00:00:00 2001
From: Frank Seide <fseide@microsoft.com>
Date: Mon, 18 May 2015 20:32:39 -0700
Subject: [PATCH 29/49] Visual Studio Solution cleanup: moved
 minibatchsourcehelpers.h to Common/Include, as it is shared amongst readers
 (exception: the HTK reader, which has a different version); fixed some
 incorrect #include of basetypes.h; copying of DLLs now does not copy if the
 file already exists and is not out of date; prebuild.bat now only updates
 builddate.h if it has changed, to avoid CNTK.cpp to be recompiled each time;
 fixed a few build warnings in the CUDA kernels (uninitialized variables);
 removed unused PTasks references in Linux makefiles

---
 Common/FileTest/FileTest.cpp                  |    2 +-
 .../Include}/minibatchsourcehelpers.h         |    0
 .../LMSequenceReader/minibatchsourcehelpers.h |  117 -
 .../LUSequenceReader/minibatchsourcehelpers.h |  118 -
 .../minibatchsourcehelpers.h                  |  117 -
 .../UCIFastReader/minibatchsourcehelpers.h    |  117 -
 DataReader/UCIReader/minibatchsourcehelpers.h |  130 -
 MachineLearning/CNTK/CNTK.cpp                 |    2 +-
 MachineLearning/CNTK/CNTK.vcxproj             |    9 +-
 MachineLearning/CNTK/CNTK.vcxproj.filters     |   32 +-
 MachineLearning/CNTK/PTask.cpp                |    7 -
 MachineLearning/CNTK/PTask.h                  |   17 -
 .../CNTK/PTaskComputationNetwork.h            |   58 -
 MachineLearning/CNTK/PTaskExecutionEngine.h   |  209 --
 MachineLearning/CNTK/PTaskGraphBuilder.cpp    | 1179 ----------
 MachineLearning/CNTK/PTaskGraphBuilder.h      |  405 ----
 MachineLearning/CNTK/fileutil.cpp             | 2087 -----------------
 MachineLearning/CNTK/prebuild.bat             |   29 +-
 MachineLearning/CNTKEval/CNTKEval.vcxproj     |    5 +-
 .../CNTKEval/CNTKEval.vcxproj.filters         |    3 +
 MachineLearning/MachineLearning.sln           |   29 -
 MachineLearning/MachineLearning.vssscc        |   10 -
 Makefile.cpu                                  |    2 +-
 Makefile.gpu                                  |    2 +-
 Makefile_kaldi.cpu                            |    2 +-
 Makefile_kaldi.gpu                            |    2 +-
 Math/CNTKMathTest/MatrixFileWriteAndRead.cpp  |    6 +-
 Math/Math/CNTKMathCUDA.vcxproj                |    8 +-
 Math/Math/GPUMatrix.cu                        |    9 +-
 Math/Math/GPUMatrixCUDAKernels.cu             |    2 +-
 Math/Math/Math.vcxproj                        |    6 +-
 31 files changed, 71 insertions(+), 4650 deletions(-)
 rename {DataReader/DSSMReader => Common/Include}/minibatchsourcehelpers.h (100%)
 delete mode 100644 DataReader/LMSequenceReader/minibatchsourcehelpers.h
 delete mode 100644 DataReader/LUSequenceReader/minibatchsourcehelpers.h
 delete mode 100644 DataReader/LibSVMBinaryReader/minibatchsourcehelpers.h
 delete mode 100644 DataReader/UCIFastReader/minibatchsourcehelpers.h
 delete mode 100644 DataReader/UCIReader/minibatchsourcehelpers.h
 delete mode 100644 MachineLearning/CNTK/PTask.cpp
 delete mode 100644 MachineLearning/CNTK/PTask.h
 delete mode 100644 MachineLearning/CNTK/PTaskComputationNetwork.h
 delete mode 100644 MachineLearning/CNTK/PTaskExecutionEngine.h
 delete mode 100644 MachineLearning/CNTK/PTaskGraphBuilder.cpp
 delete mode 100644 MachineLearning/CNTK/PTaskGraphBuilder.h
 delete mode 100644 MachineLearning/CNTK/fileutil.cpp
 delete mode 100644 MachineLearning/MachineLearning.sln
 delete mode 100644 MachineLearning/MachineLearning.vssscc

diff --git a/Common/FileTest/FileTest.cpp b/Common/FileTest/FileTest.cpp
index a3ce98c18..ee752c40c 100644
--- a/Common/FileTest/FileTest.cpp
+++ b/Common/FileTest/FileTest.cpp
@@ -7,7 +7,7 @@
 //
 
 #include "stdafx.h"
-#include "basetypes.h"
+#include "Basics.h"
 #include "fileutil.h"
 #include "FileTest.h"
 #include "File.h"
diff --git a/DataReader/DSSMReader/minibatchsourcehelpers.h b/Common/Include/minibatchsourcehelpers.h
similarity index 100%
rename from DataReader/DSSMReader/minibatchsourcehelpers.h
rename to Common/Include/minibatchsourcehelpers.h
diff --git a/DataReader/LMSequenceReader/minibatchsourcehelpers.h b/DataReader/LMSequenceReader/minibatchsourcehelpers.h
deleted file mode 100644
index 395522a37..000000000
--- a/DataReader/LMSequenceReader/minibatchsourcehelpers.h
+++ /dev/null
@@ -1,117 +0,0 @@
-//
-// <copyright file="minibatchsourcehelpers.h" company="Microsoft">
-//     Copyright (c) Microsoft Corporation.  All rights reserved.
-// </copyright>
-//
-// minibatchsourcehelpers.h -- helper classes for minibatch sources
-//
-
-#pragma once
-
-#include "Basics.h"
-#include <stdio.h>
-#include <vector>
-#include <algorithm>
-
-namespace msra { namespace dbn {
-
-// ---------------------------------------------------------------------------
-// randomordering -- class to help manage randomization of input data
-// ---------------------------------------------------------------------------
-
-static inline size_t rand (const size_t begin, const size_t end)
-{
-    const size_t randno = ::rand() * RAND_MAX + ::rand();   // BUGBUG: still only covers 32-bit range
-    return begin + randno % (end - begin);
-}
-
-class randomordering                // note: NOT thread-safe at all
-{
-    // constants for randomization
-    const static size_t randomizeDisable=0;
-
-    typedef unsigned int INDEXTYPE; // don't use size_t, as this saves HUGE amounts of RAM
-    std::vector<INDEXTYPE> map;          // [t] -> t' indices in randomized order
-    size_t currentseed;             // seed for current sequence
-    size_t randomizationrange;      // t - randomizationrange/2 <= t' < t + randomizationrange/2 (we support this to enable swapping)
-                                    // special values (randomizeDisable)
-    void invalidate() { currentseed = (size_t) -1; }
-public:
-    randomordering() { invalidate(); randomizationrange = randomizeDisable;}
-
-    void resize (size_t len, size_t p_randomizationrange) { randomizationrange = p_randomizationrange; if (len > 0) map.resize (len); invalidate(); }
-
-    // return the randomized feature bounds for a time range
-    std::pair<size_t,size_t> bounds (size_t ts, size_t te) const
-    {
-        size_t tbegin = max (ts, randomizationrange/2) - randomizationrange/2;
-        size_t tend = min (te + randomizationrange/2, map.size());
-        return std::make_pair<size_t,size_t> (move(tbegin), move(tend));
-    }
-
-    // this returns the map directly (read-only) and will lazily initialize it for a given seed
-    const std::vector<INDEXTYPE> & operator() (size_t seed) //throw()
-    {
-        // if wrong seed then lazily recache the sequence
-        if (seed != currentseed && randomizationrange != randomizeDisable)
-        {
-            // test for numeric overflow
-            if (map.size()-1 != (INDEXTYPE) (map.size()-1))
-                throw std::runtime_error ("randomordering: INDEXTYPE has too few bits for this corpus");
-            // 0, 1, 2...
-            foreach_index (t, map) map[t] = (INDEXTYPE) t;
-
-            if (map.size() > RAND_MAX * (size_t) RAND_MAX)
-                throw std::runtime_error ("randomordering: too large training set: need to change to different random generator!");
-            srand ((unsigned int) seed);
-            size_t retries = 0;
-            foreach_index (t, map)
-            {
-                for (int tries = 0; tries < 5; tries++)
-                {
-                    // swap current pos with a random position
-                    // Random positions are limited to t+randomizationrange.
-                    // This ensures some locality suitable for paging with a sliding window.
-                    const size_t tbegin = max ((size_t) t, randomizationrange/2) - randomizationrange/2; // range of window  --TODO: use bounds() function above
-                    const size_t tend = min (t + randomizationrange/2, map.size());
-                    assert (tend >= tbegin);                    // (guard against potential numeric-wraparound bug)
-                    const size_t trand = rand (tbegin, tend);   // random number within windows
-                    assert ((size_t) t <= trand + randomizationrange/2 && trand < (size_t) t + randomizationrange/2);
-                    // if range condition is fulfilled then swap
-                    if (trand <= map[t] + randomizationrange/2 && map[t] < trand + randomizationrange/2
-                        && (size_t) t <= map[trand] + randomizationrange/2 && map[trand] < (size_t) t + randomizationrange/2)
-                    {
-                        ::swap (map[t], map[trand]);
-                        break;
-                    }
-                    // but don't multi-swap stuff out of its range (for swapping positions that have been swapped before)
-                    // instead, try again with a different random number
-                    retries++;
-                }
-            }
-            fprintf (stderr, "randomordering: %d retries for %d elements (%.1f%%) to ensure window condition\n", retries, map.size(), 100.0 * retries / map.size());
-            // ensure the window condition
-            foreach_index (t, map) assert ((size_t) t <= map[t] + randomizationrange/2 && map[t] < (size_t) t + randomizationrange/2);
-#if 0       // and a live check since I don't trust myself here yet
-            foreach_index (t, map) if (!((size_t) t <= map[t] + randomizationrange/2 && map[t] < (size_t) t + randomizationrange/2))
-            {
-                fprintf (stderr, "randomordering: windowing condition violated %d -> %d\n", t, map[t]);
-                throw std::logic_error ("randomordering: windowing condition violated");
-            }
-#endif
-#if 0       // test whether it is indeed a unique complete sequence
-            auto map2 = map;
-            ::sort (map2.begin(), map2.end());
-            foreach_index (t, map2) assert (map2[t] == (size_t) t);
-#endif
-            fprintf (stderr, "randomordering: recached sequence for seed %d: %d, %d, ...\n", (int) seed, (int) map[0], (int) map[1]);
-            currentseed = seed;
-        }
-        return map; // caller can now access it through operator[]
-    }
-    size_t CurrentSeed() {return currentseed;}
-};
-
-typedef unsigned short CLASSIDTYPE; // type to store state ids; don't use size_t --saves HUGE amounts of RAM
-
-};};
diff --git a/DataReader/LUSequenceReader/minibatchsourcehelpers.h b/DataReader/LUSequenceReader/minibatchsourcehelpers.h
deleted file mode 100644
index 26d6068c2..000000000
--- a/DataReader/LUSequenceReader/minibatchsourcehelpers.h
+++ /dev/null
@@ -1,118 +0,0 @@
-//
-// <copyright file="minibatchsourcehelpers.h" company="Microsoft">
-//     Copyright (c) Microsoft Corporation.  All rights reserved.
-// </copyright>
-//
-// minibatchsourcehelpers.h -- helper classes for minibatch sources
-//
-
-
-#pragma once
-
-#include "Basics.h"
-#include <stdio.h>
-#include <vector>
-#include <algorithm>
-
-namespace msra { namespace dbn {
-
-// ---------------------------------------------------------------------------
-// randomordering -- class to help manage randomization of input data
-// ---------------------------------------------------------------------------
-
-static inline size_t rand (const size_t begin, const size_t end)
-{
-    const size_t randno = ::rand() * RAND_MAX + ::rand();   // BUGBUG: still only covers 32-bit range
-    return begin + randno % (end - begin);
-}
-
-class randomordering                // note: NOT thread-safe at all
-{
-    // constants for randomization
-    const static size_t randomizeDisable=0;
-
-    typedef unsigned int INDEXTYPE; // don't use size_t, as this saves HUGE amounts of RAM
-    std::vector<INDEXTYPE> map;          // [t] -> t' indices in randomized order
-    size_t currentseed;             // seed for current sequence
-    size_t randomizationrange;      // t - randomizationrange/2 <= t' < t + randomizationrange/2 (we support this to enable swapping)
-                                    // special values (randomizeDisable)
-    void invalidate() { currentseed = (size_t) -1; }
-public:
-    randomordering() { invalidate(); randomizationrange = randomizeDisable;}
-
-    void resize (size_t len, size_t p_randomizationrange) { randomizationrange = p_randomizationrange; if (len > 0) map.resize (len); invalidate(); }
-
-    // return the randomized feature bounds for a time range
-    std::pair<size_t,size_t> bounds (size_t ts, size_t te) const
-    {
-        size_t tbegin = max (ts, randomizationrange/2) - randomizationrange/2;
-        size_t tend = min (te + randomizationrange/2, map.size());
-        return std::make_pair<size_t,size_t> (move(tbegin), move(tend));
-    }
-
-    // this returns the map directly (read-only) and will lazily initialize it for a given seed
-    const std::vector<INDEXTYPE> & operator() (size_t seed) //throw()
-    {
-        // if wrong seed then lazily recache the sequence
-        if (seed != currentseed && randomizationrange != randomizeDisable)
-        {
-            // test for numeric overflow
-            if (map.size()-1 != (INDEXTYPE) (map.size()-1))
-                throw std::runtime_error ("randomordering: INDEXTYPE has too few bits for this corpus");
-            // 0, 1, 2...
-            foreach_index (t, map) map[t] = (INDEXTYPE) t;
-
-            if (map.size() > RAND_MAX * (size_t) RAND_MAX)
-                throw std::runtime_error ("randomordering: too large training set: need to change to different random generator!");
-            srand ((unsigned int) seed);
-            size_t retries = 0;
-            foreach_index (t, map)
-            {
-                for (int tries = 0; tries < 5; tries++)
-                {
-                    // swap current pos with a random position
-                    // Random positions are limited to t+randomizationrange.
-                    // This ensures some locality suitable for paging with a sliding window.
-                    const size_t tbegin = max ((size_t) t, randomizationrange/2) - randomizationrange/2; // range of window  --TODO: use bounds() function above
-                    const size_t tend = min (t + randomizationrange/2, map.size());
-                    assert (tend >= tbegin);                    // (guard against potential numeric-wraparound bug)
-                    const size_t trand = rand (tbegin, tend);   // random number within windows
-                    assert ((size_t) t <= trand + randomizationrange/2 && trand < (size_t) t + randomizationrange/2);
-                    // if range condition is fulfilled then swap
-                    if (trand <= map[t] + randomizationrange/2 && map[t] < trand + randomizationrange/2
-                        && (size_t) t <= map[trand] + randomizationrange/2 && map[trand] < (size_t) t + randomizationrange/2)
-                    {
-                        ::swap (map[t], map[trand]);
-                        break;
-                    }
-                    // but don't multi-swap stuff out of its range (for swapping positions that have been swapped before)
-                    // instead, try again with a different random number
-                    retries++;
-                }
-            }
-            fprintf (stderr, "randomordering: %d retries for %d elements (%.1f%%) to ensure window condition\n", retries, map.size(), 100.0 * retries / map.size());
-            // ensure the window condition
-            foreach_index (t, map) assert ((size_t) t <= map[t] + randomizationrange/2 && map[t] < (size_t) t + randomizationrange/2);
-#if 0       // and a live check since I don't trust myself here yet
-            foreach_index (t, map) if (!((size_t) t <= map[t] + randomizationrange/2 && map[t] < (size_t) t + randomizationrange/2))
-            {
-                fprintf (stderr, "randomordering: windowing condition violated %d -> %d\n", t, map[t]);
-                throw std::logic_error ("randomordering: windowing condition violated");
-            }
-#endif
-#if 0       // test whether it is indeed a unique complete sequence
-            auto map2 = map;
-            ::sort (map2.begin(), map2.end());
-            foreach_index (t, map2) assert (map2[t] == (size_t) t);
-#endif
-            fprintf (stderr, "randomordering: recached sequence for seed %d: %d, %d, ...\n", (int) seed, (int) map[0], (int) map[1]);
-            currentseed = seed;
-        }
-        return map; // caller can now access it through operator[]
-    }
-    size_t CurrentSeed() {return currentseed;}
-};
-
-typedef unsigned short CLASSIDTYPE; // type to store state ids; don't use size_t --saves HUGE amounts of RAM
-
-};};
diff --git a/DataReader/LibSVMBinaryReader/minibatchsourcehelpers.h b/DataReader/LibSVMBinaryReader/minibatchsourcehelpers.h
deleted file mode 100644
index f87c8bb94..000000000
--- a/DataReader/LibSVMBinaryReader/minibatchsourcehelpers.h
+++ /dev/null
@@ -1,117 +0,0 @@
-//
-// <copyright file="minibatchsourcehelpers.h" company="Microsoft">
-//     Copyright (c) Microsoft Corporation.  All rights reserved.
-// </copyright>
-//
-// minibatchsourcehelpers.h -- helper classes for minibatch sources
-//
-
-#pragma once
-
-#include "Basics.h"
-#include <stdio.h>
-#include <vector>
-#include <algorithm>
-
-namespace msra { namespace dbn {
-
-// ---------------------------------------------------------------------------
-// randomordering -- class to help manage randomization of input data
-// ---------------------------------------------------------------------------
-
-static inline size_t rand (const size_t begin, const size_t end)
-{
-    const size_t randno = ::rand() * RAND_MAX + ::rand();   // BUGBUG: still only covers 32-bit range
-    return begin + randno % (end - begin);
-}
-
-class randomordering                // note: NOT thread-safe at all
-{
-    // constants for randomization
-    const static size_t randomizeDisable=0;
-
-    typedef unsigned int INDEXTYPE; // don't use size_t, as this saves HUGE amounts of RAM
-    std::vector<INDEXTYPE> map;          // [t] -> t' indices in randomized order
-    size_t currentseed;             // seed for current sequence
-    size_t randomizationrange;      // t - randomizationrange/2 <= t' < t + randomizationrange/2 (we support this to enable swapping)
-                                    // special values (randomizeDisable)
-    void invalidate() { currentseed = (size_t) -1; }
-public:
-    randomordering() { invalidate(); randomizationrange = randomizeDisable;}
-
-    void resize (size_t len, size_t p_randomizationrange) { randomizationrange = p_randomizationrange; if (len > 0) map.resize (len); invalidate(); }
-
-    // return the randomized feature bounds for a time range
-    std::pair<size_t,size_t> bounds (size_t ts, size_t te) const
-    {
-        size_t tbegin = max (ts, randomizationrange/2) - randomizationrange/2;
-        size_t tend = min (te + randomizationrange/2, map.size());
-        return std::make_pair<size_t,size_t> (move(tbegin), move(tend));
-    }
-
-    // this returns the map directly (read-only) and will lazily initialize it for a given seed
-    const std::vector<INDEXTYPE> & operator() (size_t seed) //throw()
-    {
-        // if wrong seed then lazily recache the sequence
-        if (seed != currentseed && randomizationrange != randomizeDisable)
-        {
-            // test for numeric overflow
-            if (map.size()-1 != (INDEXTYPE) (map.size()-1))
-                throw std::runtime_error ("randomordering: INDEXTYPE has too few bits for this corpus");
-            // 0, 1, 2...
-            foreach_index (t, map) map[t] = (INDEXTYPE) t;
-
-            if (map.size() > RAND_MAX * (size_t) RAND_MAX)
-                throw std::runtime_error ("randomordering: too large training set: need to change to different random generator!");
-            srand ((unsigned int) seed);
-            size_t retries = 0;
-            foreach_index (t, map)
-            {
-                for (int tries = 0; tries < 5; tries++)
-                {
-                    // swap current pos with a random position
-                    // Random positions are limited to t+randomizationrange.
-                    // This ensures some locality suitable for paging with a sliding window.
-                    const size_t tbegin = max ((size_t) t, randomizationrange/2) - randomizationrange/2; // range of window  --TODO: use bounds() function above
-                    const size_t tend = min (t + randomizationrange/2, map.size());
-                    assert (tend >= tbegin);                    // (guard against potential numeric-wraparound bug)
-                    const size_t trand = rand (tbegin, tend);   // random number within windows
-                    assert ((size_t) t <= trand + randomizationrange/2 && trand < (size_t) t + randomizationrange/2);
-                    // if range condition is fulfilled then swap
-                    if (trand <= map[t] + randomizationrange/2 && map[t] < trand + randomizationrange/2
-                        && (size_t) t <= map[trand] + randomizationrange/2 && map[trand] < (size_t) t + randomizationrange/2)
-                    {
-                        ::swap (map[t], map[trand]);
-                        break;
-                    }
-                    // but don't multi-swap stuff out of its range (for swapping positions that have been swapped before)
-                    // instead, try again with a different random number
-                    retries++;
-                }
-            }
-            fprintf (stderr, "randomordering: %d retries for %d elements (%.1f%%) to ensure window condition\n", retries, map.size(), 100.0 * retries / map.size());
-            // ensure the window condition
-            foreach_index (t, map) assert ((size_t) t <= map[t] + randomizationrange/2 && map[t] < (size_t) t + randomizationrange/2);
-#if 0       // and a live check since I don't trust myself here yet
-            foreach_index (t, map) if (!((size_t) t <= map[t] + randomizationrange/2 && map[t] < (size_t) t + randomizationrange/2))
-            {
-                fprintf (stderr, "randomordering: windowing condition violated %d -> %d\n", t, map[t]);
-                throw std::logic_error ("randomordering: windowing condition violated");
-            }
-#endif
-#if 0       // test whether it is indeed a unique complete sequence
-            auto map2 = map;
-            ::sort (map2.begin(), map2.end());
-            foreach_index (t, map2) assert (map2[t] == (size_t) t);
-#endif
-            fprintf (stderr, "randomordering: recached sequence for seed %d: %d, %d, ...\n", (int) seed, (int) map[0], (int) map[1]);
-            currentseed = seed;
-        }
-        return map; // caller can now access it through operator[]
-    }
-    size_t CurrentSeed() {return currentseed;}
-};
-
-typedef unsigned short CLASSIDTYPE; // type to store state ids; don't use size_t --saves HUGE amounts of RAM
-
-};};
diff --git a/DataReader/UCIFastReader/minibatchsourcehelpers.h b/DataReader/UCIFastReader/minibatchsourcehelpers.h
deleted file mode 100644
index 395522a37..000000000
--- a/DataReader/UCIFastReader/minibatchsourcehelpers.h
+++ /dev/null
@@ -1,117 +0,0 @@
-//
-// <copyright file="minibatchsourcehelpers.h" company="Microsoft">
-//     Copyright (c) Microsoft Corporation.  All rights reserved.
-// </copyright>
-//
-// minibatchsourcehelpers.h -- helper classes for minibatch sources
-//
-
-#pragma once
-
-#include "Basics.h"
-#include <stdio.h>
-#include <vector>
-#include <algorithm>
-
-namespace msra { namespace dbn {
-
-// ---------------------------------------------------------------------------
-// randomordering -- class to help manage randomization of input data
-// ---------------------------------------------------------------------------
-
-static inline size_t rand (const size_t begin, const size_t end)
-{
-    const size_t randno = ::rand() * RAND_MAX + ::rand();   // BUGBUG: still only covers 32-bit range
-    return begin + randno % (end - begin);
-}
-
-class randomordering                // note: NOT thread-safe at all
-{
-    // constants for randomization
-    const static size_t randomizeDisable=0;
-
-    typedef unsigned int INDEXTYPE; // don't use size_t, as this saves HUGE amounts of RAM
-    std::vector<INDEXTYPE> map;          // [t] -> t' indices in randomized order
-    size_t currentseed;             // seed for current sequence
-    size_t randomizationrange;      // t - randomizationrange/2 <= t' < t + randomizationrange/2 (we support this to enable swapping)
-                                    // special values (randomizeDisable)
-    void invalidate() { currentseed = (size_t) -1; }
-public:
-    randomordering() { invalidate(); randomizationrange = randomizeDisable;}
-
-    void resize (size_t len, size_t p_randomizationrange) { randomizationrange = p_randomizationrange; if (len > 0) map.resize (len); invalidate(); }
-
-    // return the randomized feature bounds for a time range
-    std::pair<size_t,size_t> bounds (size_t ts, size_t te) const
-    {
-        size_t tbegin = max (ts, randomizationrange/2) - randomizationrange/2;
-        size_t tend = min (te + randomizationrange/2, map.size());
-        return std::make_pair<size_t,size_t> (move(tbegin), move(tend));
-    }
-
-    // this returns the map directly (read-only) and will lazily initialize it for a given seed
-    const std::vector<INDEXTYPE> & operator() (size_t seed) //throw()
-    {
-        // if wrong seed then lazily recache the sequence
-        if (seed != currentseed && randomizationrange != randomizeDisable)
-        {
-            // test for numeric overflow
-            if (map.size()-1 != (INDEXTYPE) (map.size()-1))
-                throw std::runtime_error ("randomordering: INDEXTYPE has too few bits for this corpus");
-            // 0, 1, 2...
-            foreach_index (t, map) map[t] = (INDEXTYPE) t;
-
-            if (map.size() > RAND_MAX * (size_t) RAND_MAX)
-                throw std::runtime_error ("randomordering: too large training set: need to change to different random generator!");
-            srand ((unsigned int) seed);
-            size_t retries = 0;
-            foreach_index (t, map)
-            {
-                for (int tries = 0; tries < 5; tries++)
-                {
-                    // swap current pos with a random position
-                    // Random positions are limited to t+randomizationrange.
-                    // This ensures some locality suitable for paging with a sliding window.
-                    const size_t tbegin = max ((size_t) t, randomizationrange/2) - randomizationrange/2; // range of window  --TODO: use bounds() function above
-                    const size_t tend = min (t + randomizationrange/2, map.size());
-                    assert (tend >= tbegin);                    // (guard against potential numeric-wraparound bug)
-                    const size_t trand = rand (tbegin, tend);   // random number within windows
-                    assert ((size_t) t <= trand + randomizationrange/2 && trand < (size_t) t + randomizationrange/2);
-                    // if range condition is fulfilled then swap
-                    if (trand <= map[t] + randomizationrange/2 && map[t] < trand + randomizationrange/2
-                        && (size_t) t <= map[trand] + randomizationrange/2 && map[trand] < (size_t) t + randomizationrange/2)
-                    {
-                        ::swap (map[t], map[trand]);
-                        break;
-                    }
-                    // but don't multi-swap stuff out of its range (for swapping positions that have been swapped before)
-                    // instead, try again with a different random number
-                    retries++;
-                }
-            }
-            fprintf (stderr, "randomordering: %d retries for %d elements (%.1f%%) to ensure window condition\n", retries, map.size(), 100.0 * retries / map.size());
-            // ensure the window condition
-            foreach_index (t, map) assert ((size_t) t <= map[t] + randomizationrange/2 && map[t] < (size_t) t + randomizationrange/2);
-#if 0       // and a live check since I don't trust myself here yet
-            foreach_index (t, map) if (!((size_t) t <= map[t] + randomizationrange/2 && map[t] < (size_t) t + randomizationrange/2))
-            {
-                fprintf (stderr, "randomordering: windowing condition violated %d -> %d\n", t, map[t]);
-                throw std::logic_error ("randomordering: windowing condition violated");
-            }
-#endif
-#if 0       // test whether it is indeed a unique complete sequence
-            auto map2 = map;
-            ::sort (map2.begin(), map2.end());
-            foreach_index (t, map2) assert (map2[t] == (size_t) t);
-#endif
-            fprintf (stderr, "randomordering: recached sequence for seed %d: %d, %d, ...\n", (int) seed, (int) map[0], (int) map[1]);
-            currentseed = seed;
-        }
-        return map; // caller can now access it through operator[]
-    }
-    size_t CurrentSeed() {return currentseed;}
-};
-
-typedef unsigned short CLASSIDTYPE; // type to store state ids; don't use size_t --saves HUGE amounts of RAM
-
-};};
diff --git a/DataReader/UCIReader/minibatchsourcehelpers.h b/DataReader/UCIReader/minibatchsourcehelpers.h
deleted file mode 100644
index 940b3b0e2..000000000
--- a/DataReader/UCIReader/minibatchsourcehelpers.h
+++ /dev/null
@@ -1,130 +0,0 @@
-//
-// <copyright file="minibatchsourcehelpers.h" company="Microsoft">
-//     Copyright (c) Microsoft Corporation.  All rights reserved.
-// </copyright>
-//
-// minibatchsourcehelpers.h -- helper classes for minibatch sources
-//
-// F. Seide, Oct 2012
-//
-// $Log: /Speech_To_Speech_Translation/dbn/dbn/minibatchsourcehelpers.h $
-// 
-// 3     10/09/12 7:23p Fseide
-// moved class minibatchiterator to minibatchiterator.h, and dealt with
-// the fallout
-// 
-// 2     10/09/12 7:12p Fseide
-// moved all minibatch sources to respective new source files
-// 
-// 1     10/09/12 6:45p Fseide
-// began to move the minibatch sources to separate source files
-
-#pragma once
-
-#include "basetypes.h"
-#include <stdio.h>
-#include <vector>
-#include <algorithm>
-
-namespace msra { namespace dbn {
-
-// ---------------------------------------------------------------------------
-// randomordering -- class to help manage randomization of input data
-// ---------------------------------------------------------------------------
-
-static inline size_t rand (const size_t begin, const size_t end)
-{
-    const size_t randno = ::rand() * RAND_MAX + ::rand();   // BUGBUG: still only covers 32-bit range
-    return begin + randno % (end - begin);
-}
-
-class randomordering                // note: NOT thread-safe at all
-{
-    // constants for randomization
-    const static size_t randomizeDisable=0;
-
-    typedef unsigned int INDEXTYPE; // don't use size_t, as this saves HUGE amounts of RAM
-    std::vector<INDEXTYPE> map;          // [t] -> t' indices in randomized order
-    size_t currentseed;             // seed for current sequence
-    size_t randomizationrange;      // t - randomizationrange/2 <= t' < t + randomizationrange/2 (we support this to enable swapping)
-                                    // special values (randomizeDisable)
-    void invalidate() { currentseed = (size_t) -1; }
-public:
-    randomordering() { invalidate(); randomizationrange = randomizeDisable;}
-
-    void resize (size_t len, size_t p_randomizationrange) { randomizationrange = p_randomizationrange; if (len > 0) map.resize (len); invalidate(); }
-
-    // return the randomized feature bounds for a time range
-    std::pair<size_t,size_t> bounds (size_t ts, size_t te) const
-    {
-        size_t tbegin = max (ts, randomizationrange/2) - randomizationrange/2;
-        size_t tend = min (te + randomizationrange/2, map.size());
-        return std::make_pair<size_t,size_t> (move(tbegin), move(tend));
-    }
-
-    // this returns the map directly (read-only) and will lazily initialize it for a given seed
-    const std::vector<INDEXTYPE> & operator() (size_t seed) //throw()
-    {
-        // if wrong seed then lazily recache the sequence
-        if (seed != currentseed && randomizationrange != randomizeDisable)
-        {
-            // test for numeric overflow
-            if (map.size()-1 != (INDEXTYPE) (map.size()-1))
-                throw std::runtime_error ("randomordering: INDEXTYPE has too few bits for this corpus");
-            // 0, 1, 2...
-            foreach_index (t, map) map[t] = (INDEXTYPE) t;
-
-            if (map.size() > RAND_MAX * (size_t) RAND_MAX)
-                throw std::runtime_error ("randomordering: too large training set: need to change to different random generator!");
-            srand ((unsigned int) seed);
-            size_t retries = 0;
-            foreach_index (t, map)
-            {
-                for (int tries = 0; tries < 5; tries++)
-                {
-                    // swap current pos with a random position
-                    // Random positions are limited to t+randomizationrange.
-                    // This ensures some locality suitable for paging with a sliding window.
-                    const size_t tbegin = max ((size_t) t, randomizationrange/2) - randomizationrange/2; // range of window  --TODO: use bounds() function above
-                    const size_t tend = min (t + randomizationrange/2, map.size());
-                    assert (tend >= tbegin);                    // (guard against potential numeric-wraparound bug)
-                    const size_t trand = rand (tbegin, tend);   // random number within windows
-                    assert ((size_t) t <= trand + randomizationrange/2 && trand < (size_t) t + randomizationrange/2);
-                    // if range condition is fulfilled then swap
-                    if (trand <= map[t] + randomizationrange/2 && map[t] < trand + randomizationrange/2
-                        && (size_t) t <= map[trand] + randomizationrange/2 && map[trand] < (size_t) t + randomizationrange/2)
-                    {
-                        ::swap (map[t], map[trand]);
-                        break;
-                    }
-                    // but don't multi-swap stuff out of its range (for swapping positions that have been swapped before)
-                    // instead, try again with a different random number
-                    retries++;
-                }
-            }
-            fprintf (stderr, "randomordering: %d retries for %d elements (%.1f%%) to ensure window condition\n", retries, map.size(), 100.0 * retries / map.size());
-            // ensure the window condition
-            foreach_index (t, map) assert ((size_t) t <= map[t] + randomizationrange/2 && map[t] < (size_t) t + randomizationrange/2);
-#if 0       // and a live check since I don't trust myself here yet
-            foreach_index (t, map) if (!((size_t) t <= map[t] + randomizationrange/2 && map[t] < (size_t) t + randomizationrange/2))
-            {
-                fprintf (stderr, "randomordering: windowing condition violated %d -> %d\n", t, map[t]);
-                throw std::logic_error ("randomordering: windowing condition violated");
-            }
-#endif
-#if 0       // test whether it is indeed a unique complete sequence
-            auto map2 = map;
-            ::sort (map2.begin(), map2.end());
-            foreach_index (t, map2) assert (map2[t] == (size_t) t);
-#endif
-            fprintf (stderr, "randomordering: recached sequence for seed %d: %d, %d, ...\n", (int) seed, (int) map[0], (int) map[1]);
-            currentseed = seed;
-        }
-        return map; // caller can now access it through operator[]
-    }
-    size_t CurrentSeed() {return currentseed;}
-};
-
-typedef unsigned short CLASSIDTYPE; // type to store state ids; don't use size_t --saves HUGE amounts of RAM
-
-};};
diff --git a/MachineLearning/CNTK/CNTK.cpp b/MachineLearning/CNTK/CNTK.cpp
index ce5f05b25..8c6de8339 100644
--- a/MachineLearning/CNTK/CNTK.cpp
+++ b/MachineLearning/CNTK/CNTK.cpp
@@ -19,7 +19,7 @@
 #include "ModelEditLanguage.h"
 #include "SGD.h"
 #include <string>
-#include <basetypes.h>
+#include "Basics.h"
 #include "commandArgUtil.h"
 #include "SimpleEvaluator.h"
 #include "SimpleOutputWriter.h"
diff --git a/MachineLearning/CNTK/CNTK.vcxproj b/MachineLearning/CNTK/CNTK.vcxproj
index b72655823..7f7ca8291 100644
--- a/MachineLearning/CNTK/CNTK.vcxproj
+++ b/MachineLearning/CNTK/CNTK.vcxproj
@@ -83,7 +83,7 @@
       <DelayLoadDLLs>CNTKMath.dll; nvml.dll; cudart64_70.dll</DelayLoadDLLs>
     </Link>
     <PostBuildEvent>
-      <Command>XCOPY /I /Y "%ProgramW6432%\NVIDIA Corporation\NVSMI\nvml*.dll" $(TargetDir)</Command>
+      <Command>xcopy /I /D /Y "%ProgramW6432%\NVIDIA Corporation\NVSMI\nvml*.dll" $(TargetDir)</Command>
       <Message>Copying NVidia GDK extension DLL to target folder</Message>
     </PostBuildEvent>
     <CustomBuildStep>
@@ -125,7 +125,7 @@
       <AdditionalLibraryDirectories>"c:\Program Files\NVIDIA Corporation\GDK\gdk_win7_amd64_release\nvml\lib"</AdditionalLibraryDirectories>
     </Link>
     <PostBuildEvent>
-      <Command>XCOPY /I /Y "%ProgramW6432%\NVIDIA Corporation\NVSMI\nvml*.dll" $(TargetDir)</Command>
+      <Command>xcopy /I /D /Y "%ProgramW6432%\NVIDIA Corporation\NVSMI\nvml*.dll" $(TargetDir)</Command>
       <Message>Copying NVidia GDK extension DLL to target folder</Message>
     </PostBuildEvent>
     <CustomBuildStep>
@@ -151,7 +151,6 @@
     <Text Include="modelEditorFromScratch.txt" />
   </ItemGroup>
   <ItemGroup>
-    <ClInclude Include="..\..\Common\hostname.h" />
     <ClInclude Include="..\..\Common\Include\basetypes.h" />
     <ClInclude Include="..\..\Common\Include\Basics.h" />
     <ClInclude Include="..\..\Common\Include\BestGpu.h" />
@@ -161,6 +160,7 @@
     <ClInclude Include="..\..\Common\Include\File.h" />
     <ClInclude Include="..\..\Common\Include\fileutil.h" />
     <ClInclude Include="..\..\Common\Include\hostname.h" />
+    <ClInclude Include="..\..\Common\Include\minibatchsourcehelpers.h" />
     <ClInclude Include="..\..\Common\Include\nvml.h" />
     <ClInclude Include="..\..\Common\Include\TimerUtility.h" />
     <ClInclude Include="CompositeComputationNode.h" />
@@ -203,6 +203,9 @@
     <ClCompile Include="stdafx.cpp" />
     <ClCompile Include="tests.cpp" />
   </ItemGroup>
+  <ItemGroup>
+    <None Include="prebuild.bat" />
+  </ItemGroup>
   <Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
   <ImportGroup Label="ExtensionTargets" />
 </Project>
\ No newline at end of file
diff --git a/MachineLearning/CNTK/CNTK.vcxproj.filters b/MachineLearning/CNTK/CNTK.vcxproj.filters
index 2af1d2fb5..b0bce29ee 100644
--- a/MachineLearning/CNTK/CNTK.vcxproj.filters
+++ b/MachineLearning/CNTK/CNTK.vcxproj.filters
@@ -1,9 +1,6 @@
 <?xml version="1.0" encoding="utf-8"?>
 <Project ToolsVersion="4.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
   <ItemGroup>
-    <ClCompile Include="..\..\Common\BestGpu.cpp">
-      <Filter>Common</Filter>
-    </ClCompile>
     <ClCompile Include="..\..\Common\ConfigFile.cpp">
       <Filter>Common</Filter>
     </ClCompile>
@@ -41,17 +38,14 @@
       <Filter>Common</Filter>
     </ClCompile>
     <ClCompile Include="CNTK.cpp" />
+    <ClCompile Include="..\..\Common\BestGpu.cpp">
+      <Filter>GPU Interfacing</Filter>
+    </ClCompile>
   </ItemGroup>
   <ItemGroup>
     <ClInclude Include="..\..\Common\Include\basetypes.h">
       <Filter>Common\Include</Filter>
     </ClInclude>
-    <ClInclude Include="..\..\Common\Include\BestGpu.h">
-      <Filter>Common\Include</Filter>
-    </ClInclude>
-    <ClInclude Include="..\..\Common\hostname.h">
-      <Filter>Common</Filter>
-    </ClInclude>
     <ClInclude Include="..\..\Common\Include\commandArgUtil.h">
       <Filter>Common\Include</Filter>
     </ClInclude>
@@ -61,9 +55,6 @@
     <ClInclude Include="..\..\Common\Include\File.h">
       <Filter>Common\Include</Filter>
     </ClInclude>
-    <ClInclude Include="..\..\Common\Include\nvml.h">
-      <Filter>Common\Include</Filter>
-    </ClInclude>
     <ClInclude Include="..\..\Common\Include\DataReader.h">
       <Filter>Common\Include</Filter>
     </ClInclude>
@@ -136,6 +127,15 @@
     <ClInclude Include="..\..\Common\Include\Basics.h">
       <Filter>Common\Include</Filter>
     </ClInclude>
+    <ClInclude Include="..\..\Common\Include\nvml.h">
+      <Filter>GPU Interfacing</Filter>
+    </ClInclude>
+    <ClInclude Include="..\..\Common\Include\minibatchsourcehelpers.h">
+      <Filter>Common\Include</Filter>
+    </ClInclude>
+    <ClInclude Include="..\..\Common\Include\BestGpu.h">
+      <Filter>Common\Include</Filter>
+    </ClInclude>
   </ItemGroup>
   <ItemGroup>
     <Text Include="modelEditor.txt">
@@ -170,5 +170,13 @@
     <Filter Include="Misc">
       <UniqueIdentifier>{3c119a92-ffb2-4850-adae-01778324974d}</UniqueIdentifier>
     </Filter>
+    <Filter Include="GPU Interfacing">
+      <UniqueIdentifier>{8d99b2cc-5209-40e4-8b4b-a7616973ae3b}</UniqueIdentifier>
+    </Filter>
+  </ItemGroup>
+  <ItemGroup>
+    <None Include="prebuild.bat">
+      <Filter>Misc</Filter>
+    </None>
   </ItemGroup>
 </Project>
\ No newline at end of file
diff --git a/MachineLearning/CNTK/PTask.cpp b/MachineLearning/CNTK/PTask.cpp
deleted file mode 100644
index 99cc2d31e..000000000
--- a/MachineLearning/CNTK/PTask.cpp
+++ /dev/null
@@ -1,7 +0,0 @@
-#include "stdafx.h"
-#include "ComputationNetwork.h"
-#include "PTaskGraphBuilder.h"
-
-namespace Microsoft { namespace MSR { namespace CNTK {
-
-}}}
\ No newline at end of file
diff --git a/MachineLearning/CNTK/PTask.h b/MachineLearning/CNTK/PTask.h
deleted file mode 100644
index bb20d6b5a..000000000
--- a/MachineLearning/CNTK/PTask.h
+++ /dev/null
@@ -1,17 +0,0 @@
-//
-// <copyright file="PTask.h" company="Microsoft">
-//     Copyright (c) Microsoft Corporation.  All rights reserved.
-// </copyright>
-//
-#pragma once
-
-// A single include file to collect together all includes for PTask.
-#define CUDA_SUPPORT
-#include "PTaskAPI.h"
-#include "primitive_types.h"
-#include "HostTask.h"
-
-using namespace PTask;
-
-// TODO: Base the path on the properties specified in config.txt. 
-#define PTASK_GRAPH_VIZ_FILE "C:\\temp\\PTaskGraph.dot"
diff --git a/MachineLearning/CNTK/PTaskComputationNetwork.h b/MachineLearning/CNTK/PTaskComputationNetwork.h
deleted file mode 100644
index 4cfdde919..000000000
--- a/MachineLearning/CNTK/PTaskComputationNetwork.h
+++ /dev/null
@@ -1,58 +0,0 @@
-//
-// <copyright file="PTaskComputationNetwork.h" company="Microsoft">
-//     Copyright (c) Microsoft Corporation.  All rights reserved.
-// </copyright>
-//
-#pragma once
-
-#include <string>
-#include "ComputationNetwork.h"
-
-#include "PTask.h"
-#include "PTaskGraphBuilder.h"
-
-namespace Microsoft { namespace MSR { namespace CNTK {
-
-    template<class ElemType>
-    class PTaskComputationNetwork : public ComputationNetwork<ElemType>
-    {
-    public:
-        PTaskComputationNetwork(short deviceId=AUTOPLACEMATRIX) 
-            : ComputationNetwork<ElemType>(deviceId)
-        {
-            m_PTaskGraphBuilder = new PTaskGraphBuilder<ElemType>();
-        }
-
-        virtual ~PTaskComputationNetwork() { }
-
-        virtual void LoadFromFile(const std::wstring& fileName, FileOptions fileFormat = FileOptions::fileOptionsBinary) override
-        {
-            // Let the base class implementation deserialize all the state
-            // and construct its regular CN ...
-            this->ComputationNetwork<ElemType>::LoadFromFile(fileName, fileFormat);
-
-            // ... then use that state to create the corresponding PTask graph.
-            m_PTaskGraphBuilder->BuildFromComputationNetwork(this);
-        }
-
-        virtual void ComputeGradient(ComputationNodePtr rootNode) override
-        {
-            //printf("PTaskComputationNetwork::ComputeGradient called.\n");
-            this->ComputationNetwork<ElemType>::ComputeGradient(rootNode);
-        }
-
-    private:
-        // Copy constructor, should never be called.
-        PTaskComputationNetwork(const PTaskComputationNetwork<ElemType>& deepCopyFrom) {};
-
-        // Assignment operator, should never be called.
-        PTaskComputationNetwork<ElemType>& operator=(const PTaskComputationNetwork<ElemType>& deepCopyFrom) 
-        {
-            assert(false);
-            return const_cast<PTaskComputationNetwork<ElemType>&>(deepCopyFrom); // return a value to avoid compile errors
-        };
-
-        PTaskGraphBuilder<ElemType>*    m_PTaskGraphBuilder;
-    };
-
-}}}
diff --git a/MachineLearning/CNTK/PTaskExecutionEngine.h b/MachineLearning/CNTK/PTaskExecutionEngine.h
deleted file mode 100644
index 23cb6ba18..000000000
--- a/MachineLearning/CNTK/PTaskExecutionEngine.h
+++ /dev/null
@@ -1,209 +0,0 @@
-//
-// <copyright file="PTaskExecutionEngine.h" company="Microsoft">
-//     Copyright (c) Microsoft Corporation.  All rights reserved.
-// </copyright>
-//
-#pragma once
-
-#include "PTaskComputationNetwork.h"
-
-namespace Microsoft { namespace MSR { namespace CNTK {
-
-// PTaskNodeEvaluator
-// Process the Network Description Language into a Computation Network useable
-// by PTaskExecutionEngine.
-template <typename ElemType>
-class PTaskNodeEvaluator : public NDLNodeEvaluator<ElemType>
-{
-public:
-    // Constructor - create evaluator
-    PTaskNodeEvaluator(PTaskComputationNetwork<ElemType>& cn)
-        : m_net(cn)
-    { }
-
-    // Evaluate - evaluate a node and translate into underlying 
-    // node - node we are evaluating
-    // baseName - base name for all symbols at this level
-    virtual void Evaluate(NDLNode<ElemType>* node, const wstring& baseName, const int pass)
-    {
-        // constants don't need to be evaluated, they just translate into numbers...
-        if (node->GetType() == ndlTypeConstant 
-            || node->GetType() == ndlTypeArray) // currently arrays only used for node lists, in the future may be used for other things
-            return;
-
-        // get the parameters
-        std::vector<NDLNode<ElemType>*> parameter = node->GetParameters();
-        if (parameter.size() < 1)
-        {
-            Error("Node with no parameters, %s\n", node->GetName().c_str());
-        }
-
-        // get the name for the symbol to be used by CN nodes
-        std::wstring name = msra::strfun::utf16(node->GetName());
-        if (!baseName.empty())
-        {
-            name = baseName + L"." + name;
-        }
-
-        if (node->GetValue() == "InputValue")
-        {
-            if (pass > 0)
-                return;
-
-            // get dimensions of input
-            size_t rows = parameter[0]->GetScalar();
-
-            // check for second dimension, otherwise default to 1
-            size_t cols = 1;
-            if (parameter.size() > 1)
-            {
-                cols = parameter[1]->GetScalar();
-            }
-
-            ComputationNodePtr input = m_net.CreateInputNode(name, rows, cols);
-            node->SetEvalValue(input);
-        }
-        else if (node->GetValue() == "LearnableParameter")
-        {
-            // get dimensions of input
-            size_t rows = parameter[0]->GetScalar();
-
-            // check for second dimension, otherwise default to 1
-            size_t cols = 1;
-            if (parameter.size() > 1)
-            {
-                cols = parameter[1]->GetScalar();
-            }
-
-            if (pass == 0)
-            {
-
-                bool needGradient = true;
-                ComputationNodePtr nodePtr = m_net.CreateLearnableParameter(name, rows, cols);
-                node->SetEvalValue(nodePtr);
-
-                nodePtr->NeedGradient() = needGradient;
-            }
-            else
-            {
-                static int randomSeed = 1;
-                ComputationNodePtr nodePtr = (ComputationNodePtr)m_net.GetNodeFromName(name);
-
-                bool init = true;
-                bool uniformInit=true;
-                if (init)
-                {
-                    InitLearnableParameters(nodePtr, cols, randomSeed++, uniformInit);
-                }
-            }
-        }
-        else if (node->GetValue() == "ConstantScalarParameter")
-        {
-            if (pass > 0)
-                return;
-
-            size_t rows = 1;
-            size_t cols = 1;
-            bool needGradient = false;
-            bool init = false;
-            ElemType val = parameter[0]->GetScalar();
-            ComputationNodePtr nodePtr = m_net.CreateLearnableParameter(name, rows, cols);
-            node->SetEvalValue(nodePtr);
-
-            nodePtr->NeedGradient() = needGradient;
-            nodePtr->FunctionValues().SetValue(val);
-        }
-        else
-        {
-            ComputationNodePtr nodePtr = NULL;
-            if (pass == 0)
-            {
-                nodePtr = m_net.CreateComputationNode(node->GetValue(), name);
-                node->SetEvalValue(nodePtr);
-            }
-
-            std::vector<void*> inputs = EvaluateParameters(node, baseName, pass);
-
-            if (pass == 0)
-            {
-                switch (inputs.size())
-                {
-                case 1:
-                    nodePtr->AttachInputs(ComputationNodePtr(inputs[0]));
-                    break;
-                case 2:
-                    nodePtr->AttachInputs(ComputationNodePtr(inputs[0]), ComputationNodePtr(inputs[1]));
-                    break;
-                case 3:
-                    nodePtr->AttachInputs(ComputationNodePtr(inputs[0]), ComputationNodePtr(inputs[1]), ComputationNodePtr(inputs[2]));
-                    break;
-                default:
-                    Error("Invalid number of parameters name = '%s' call = '%s'\n", node->GetName().c_str(), node->GetValue().c_str());
-                }
-            }
-        }
-
-    }
-
-    virtual ~PTaskNodeEvaluator()
-    {
-
-    }
-
-private:
-    PTaskComputationNetwork<ElemType>& m_net;
-    typedef ComputationNode<ElemType>* ComputationNodePtr;
-
-    void InitLearnableParameters(ComputationNodePtr node, const size_t inputSize, ULONG randomSeed, bool uniformInit)
-    {
-        ElemType initValueScale = (ElemType)1.0;
-        if (uniformInit)
-        {
-            ElemType randRange = (ElemType)0.05; //initValueScale/sqrt(inputSize);
-            node->FunctionValues().SetUniformRandomValue(-randRange, randRange, randomSeed);
-        }
-        else
-        {
-            ElemType randInitstd = (ElemType)0.2 * initValueScale/sqrt((ElemType)inputSize);
-            node->FunctionValues().SetGaussianRandomValue(0,randInitstd,randomSeed);
-        }
-    }
-};
-
-    template class PTaskComputationNetwork<float>; 
-    template class PTaskComputationNetwork<double>;
-
-// PTaskExecutionEngine
-template <typename ElemType>
-class PTaskExecutionEngine : public IExecutionEngine<ElemType>
-{
-public:
-    PTaskExecutionEngine()
-    {
-        m_nodeEvaluator = new PTaskNodeEvaluator<ElemType>(m_computationNetwork);
-    }
-
-    virtual ~PTaskExecutionEngine()
-    {
-
-    }
-
-    ComputationNetwork<ElemType>& GetComputationNetwork()
-    {
-        return m_computationNetwork;
-    }
-
-    NDLNodeEvaluator<ElemType>& GetNodeEvaluator()
-    {
-        return *m_nodeEvaluator;
-    }
-
-private:
-    PTaskComputationNetwork<ElemType> m_computationNetwork;
-    PTaskNodeEvaluator<ElemType>* m_nodeEvaluator;
-
-};
-    template class PTaskExecutionEngine<float>; 
-    template class PTaskExecutionEngine<double>;
-
-}}}
\ No newline at end of file
diff --git a/MachineLearning/CNTK/PTaskGraphBuilder.cpp b/MachineLearning/CNTK/PTaskGraphBuilder.cpp
deleted file mode 100644
index d6a7ae934..000000000
--- a/MachineLearning/CNTK/PTaskGraphBuilder.cpp
+++ /dev/null
@@ -1,1179 +0,0 @@
-//
-// <copyright file="PTaskGraphBuilder.h" company="Microsoft">
-//     Copyright (c) Microsoft Corporation.  All rights reserved.
-// </copyright>
-//
-
-#define _CRT_SECURE_NO_WARNINGS // "secure" CRT not available on all platforms  --add this at the top of all CPP files that give "function or variable may be unsafe" warnings
-
-#ifdef USE_PTASK
-#include "PTask.h"
-#endif
-
-#include <string>
-//#include <cuda_runtime.h>
-#include "ComputationNetwork.h"
-#include "ComputationNode.h"
-#include "PTaskGraphBuilder.h"
-
-
-namespace Microsoft { namespace MSR { namespace CNTK {
-
-template<class ElemType>
-TaskDescriptor<ElemType>::TaskDescriptor(
-    const ComputationNode<ElemType>* node,
-    TaskType taskType,
-    size_t input
-    ) 
-    : m_node(const_cast<ComputationNodePtr>(node)), m_taskType(taskType)
-{
-    std::string taskName;
-
-    switch(taskType)
-    {
-    case taskUpdate: // Update task
-        {
-        m_taskName = "Update_" + msra::strfun::utf8(node->NodeName());
-        break;
-        }
-    case taskEvaluate: // EvaluateThisNode() task
-        {
-        m_taskName = msra::strfun::utf8(node->NodeName());
-        m_taskName = "Forward_" + m_taskName;
-        break;
-        }
-    case taskComputeInputPartial: // ComputeInputPartial() task
-        m_taskName = msra::strfun::utf8(node->NodeName());
-        char number[2];
-        sprintf(number, "%lu", input);
-        m_taskName = "Backprop" + std::string(number) + "_" + m_taskName;
-        break;
-    case taskEvaluateRecurrent: // EvaluateThisNode() Recurrent task
-    case taskComputeInputPartialRecurrent: // ComputeInputPartial() Recurrent task
-        throw runtime_error("Recurrent not yet implemented");
-        break;
-    }
-    m_task = nullptr;
-}
-
-template<class ElemType>
-TaskDescriptor<ElemType>::~TaskDescriptor()
-{
-}
-
-// GradientParam - Get a Gradient Param
-// index - index of input, or -1 for current node gradient
-// options - param options
-template<class ElemType>
-ParamData<ElemType>* TaskDescriptor<ElemType>::GradientParam(int index, UINT options, ElemType initValue)
-{
-    ComputationNodePtr inputNode = index<0?m_node:m_node->Inputs(index);
-    std::string valueName = msra::strfun::utf8(inputNode->NodeName()) + "_GradientValues";
-    ParamData<ElemType>* pd = new ParamData<ElemType>(paramTypeMatrix, valueName, &inputNode->GradientValues(), options);
-    if (!(options&paramOptionsNoPush))
-        m_paramData.push_back(pd);
-    if (options&paramOptionsInitialize)
-        pd->SetInitialize(initValue);
-    return pd;
-}
-
-// FunctionParam - Insert a Function Param into the parameter list
-// index - index of input, or -1 for current node gradient
-// options - param options
-template<class ElemType>
-ParamData<ElemType>* TaskDescriptor<ElemType>::FunctionParam(int index, UINT options)
-{
-    ComputationNodePtr inputNode = index<0?m_node:m_node->Inputs(index);
-    std::string valueName = msra::strfun::utf8(inputNode->NodeName()) + "_FunctionValues";
-    ParamData<ElemType>* pd = new ParamData<ElemType>(paramTypeMatrix, valueName, &inputNode->FunctionValues(), options);
-    if (!(options&paramOptionsNoPush))
-        m_paramData.push_back(pd);
-    return pd;
-}
-
-// MatrixParam - Insert a Matrix Param into the parameter list
-// matrix - matrix we are using as a parameter
-// name - name to be used for this parameter, will have node name prepended
-// options - param options
-template<class ElemType>
-ParamData<ElemType>* TaskDescriptor<ElemType>::MatrixParam(const Matrix<ElemType>& matrix, const std::string& name, UINT options)
-{
-    std::string valueName = msra::strfun::utf8(m_node->NodeName()) + "_" + name;
-    ParamData<ElemType>* pd = new ParamData<ElemType>(paramTypeMatrix, valueName, (void *)&matrix, options);
-    if (!(options&paramOptionsNoPush))
-        m_paramData.push_back(pd);
-    return pd;
-}
-
-// Param - Insert a Param into the parameter list
-// paramType - parameter type for this parameter
-// name - name to be used for this parameter, will have node name prepended
-// options - param options
-template<class ElemType>
-ParamData<ElemType>* TaskDescriptor<ElemType>::Param(ParamType paramType, const std::string& name, UINT options, void* data)
-{
-    std::string valueName = msra::strfun::utf8(m_node->NodeName()) + "_" + name;
-    ParamData<ElemType>* pd = new ParamData<ElemType>(paramType, valueName, data, options);
-    if (!(options&paramOptionsNoPush))
-        m_paramData.push_back(pd);
-    return pd;
-}
-
-// if PTask is not being used, comment it all out
-#ifndef USE_PTASK
-template<class ElemType>
-void PTaskGraphBuilder<ElemType>::PushActualMBSize(const std::list<ComputationNodePtr>& /*learnableNodes*/, size_t /*actualMBSize*/, CONTROLSIGNAL /*signal=DBCTLC_NONE*/)
-{}
-template<class ElemType>
-void PTaskGraphBuilder<ElemType>::PushData(std::map<std::wstring, Matrix<ElemType>*>& /*data*/, CONTROLSIGNAL /*signal=DBCTLC_NONE*/)
-{}
-template<class ElemType>
-ElemType PTaskGraphBuilder<ElemType>::GetValue(ComputationNode<ElemType>*)
-{ return ElemType(1);}
-template<class ElemType>
-void PTaskGraphBuilder<ElemType>::GetValue(ComputationNode<ElemType>* /*node*/, Matrix<ElemType>& /*matTo*/)
-{}
-template<class ElemType>
-PTaskGraphBuilder<ElemType>::PTaskGraphBuilder() 
-{}
-template<class ElemType>
-PTaskGraphBuilder<ElemType>::~PTaskGraphBuilder() 
-{}
-template<class ElemType>
-void PTaskGraphBuilder<ElemType>::BuildFromComputationNetwork(ComputationNetwork<ElemType>*)
-{}
-template<class ElemType>
-void PTaskGraphBuilder<ElemType>::StartPTaskGraph()
-{}
-template<class ElemType>
-void PTaskGraphBuilder<ElemType>::UpdateParameters(void* /*sgd*/, const ElemType /*learnRatePerSample*/, const size_t /*expectedMBSize*/)
-{}
-template<class ElemType>
-void PTaskGraphBuilder<ElemType>::PushMatrix(const Matrix<ElemType>& /*matrix*/, Channel* /*channel*/, CONTROLSIGNAL signal)
-{
-    signal;
-}
-
-#else //defined(USE_PTASK)
-#pragma comment(lib, "ptask.lib")
-
-DatablockTemplate* TaskDescriptor<float>::s_descriptorTemplate = NULL;
-DatablockTemplate* TaskDescriptor<double>::s_descriptorTemplate = NULL;
-
-template<class ElemType>
-void TaskDescriptor<ElemType>::ConfigureInputsAndOutputs(UINT& uidCounter, std::map<const std::string, Port*>& valueNameToProducerPortMap)
-{
-    // get the counts of ports
-    m_numInputPorts = 0;
-    m_numOutputPorts = 0;
-    for (ParamData<ElemType>* param : m_paramData)
-    {
-        if (param->options & paramOptionsInput)
-            m_numInputPorts++;
-        if (param->options & paramOptionsOutput)
-            m_numOutputPorts++;
-    }
-    m_numInputPorts++; // add an extra one for the TaskDescriptor pointer (always first parameter)
-    m_inputPorts = new PTask::Port*[m_numInputPorts];
-    m_outputPorts = new PTask::Port*[m_numOutputPorts];
-    int paramCount[PTask::PORTTYPE::OUTPUT_PORT+1] = {0};
-
-    // Add the TaskDescriptor parameter that all methods will have
-    if (s_descriptorTemplate == NULL)
-    {
-        BUFFERDIMENSIONS dims(sizeof(TaskDescriptor<ElemType>*));
-        s_descriptorTemplate = Runtime::GetDatablockTemplate("TaskDescriptorTemplate", &dims, 1, FALSE, TRUE); // TODO which override? flag values?
-    }
-    Port* port = CreatePortForTemplate(s_descriptorTemplate, PTask::PORTTYPE::STICKY_PORT, std::string("TaskDescriptor"), 0, -1, false/*gpuBuffer*/, uidCounter, valueNameToProducerPortMap);
-    m_inputPorts[paramCount[PTask::PORTTYPE::INPUT_PORT]++] = port;
-    void* pv = this;
-    Datablock* pblock = PTask::Runtime::AllocateDatablock(s_descriptorTemplate, (void *)&pv, sizeof(this), NULL);
-    port->SetPermanentBlock(pblock);
-    pblock->Release();
-
-    // create the ports for the other parameters
-    int paramNum = 0;
-    for (ParamData<ElemType>* param : m_paramData)
-    {
-        Port* port = NULL;
-
-        // loop for support of in/out ports
-        for (UINT portLoop = PTask::PORTTYPE::INPUT_PORT;
-            portLoop <= PTask::PORTTYPE::OUTPUT_PORT;
-            portLoop = (PTask::PORTTYPE)((UINT)portLoop++))
-        {
-            UINT portType = portLoop;
-            int outputPort = -1;
-            if (portType == PTask::PORTTYPE::INPUT_PORT)
-            {
-                // is it some input type?
-                if (!(param->options & (paramOptionsInput|paramOptionsInitialize|paramOptionsConstant|paramOptionsTemporary)))
-                    continue;
-                // for now treat a temporary as a initializer port that takes zero as it's initalizer value, may change later to a pool or something else
-                if (param->options & (paramOptionsInitialize|paramOptionsTemporary))
-                    portType = PTask::PORTTYPE::INITIALIZER_PORT;
-
-                // Do this to setup an in/out port
-                if (param->options & paramOptionsOutput)
-                    outputPort = paramCount[PTask::PORTTYPE::OUTPUT_PORT];
-            }
-            // check for output port
-            else if (!(param->options & paramOptionsOutput))
-            {
-                continue;
-            }
-
-            // get the dimensions to use for the data template
-            BUFFERDIMENSIONS dims;
-
-            // determine name for port
-            char buf[10];
-            _itoa_s(paramNum, buf, 10);
-            std::string name = m_taskName + "." + buf;
-            bool gpuBuffer = false;
-
-            // get size and suffix for name based on type
-            switch(param->type)
-            {
-            case paramTypeChar:
-                dims.Initialize(sizeof(char));
-                name += ".char";
-                break;
-            case paramTypeShort:
-                dims.Initialize(sizeof(short));
-                name += ".short";
-                break;
-            case paramTypeLong:
-                dims.Initialize(sizeof(long));
-                name += ".long";
-                break;
-            case paramTypeLongLong:
-                dims.Initialize(sizeof(long));
-                name += ".longlong";
-                break;
-            case paramTypePointer:
-            case paramTypeNode: // same as constant pointer
-                dims.Initialize(sizeof(void*));
-                name += ".pointer";
-                break;
-            case paramTypeSingle:
-                dims.Initialize(sizeof(float));
-                name += ".float";
-                break;
-            case paramTypeDouble:
-                dims.Initialize(sizeof(double));
-                name += ".double";
-                break;
-            case paramTypeMatrix:
-                {
-                Matrix<ElemType>* matrix = (Matrix<ElemType>*)param->assocData;
-                dims.Initialize((UINT)matrix->GetNumRows(), (UINT)matrix->GetNumCols(), 1, sizeof(ElemType), (UINT)(sizeof(ElemType)*matrix->GetNumRows() /* ADim.colstride */ ));
-                name += ".matrix";
-                gpuBuffer = true;
-                break;
-                }
-            default:
-                assert(false);
-                break;
-            }
-
-            // TODO: Any benefit to caching/reusing templates across different tasks? DBN doesn't bother; 
-            // PTask doesn't use unique identity, it seems - at least at present. Do it anyway, in case this changes in the future?
-            DatablockTemplate* dt = Runtime::GetDatablockTemplate((char *)name.c_str(), &dims, 1, FALSE, TRUE); // TODO which override? flag values?
-
-            // if this is a matrix type we want to add an application context
-            if (param->type == paramTypeMatrix)
-            {
-                dt->SetApplicationContextCallback((LPFNAPPLICATIONCONTEXTCALLBACK)PTaskGraphBuilder<ElemType>::ApplicationContextCallback);
-            }
-
-            // create the port, we add 1 to the paramNum because we always have the taskDescriptor as the first parameter to the task, but it's not in the parameter collection
-            port = CreatePortForTemplate(dt, portType, param->name, paramNum+1, outputPort, gpuBuffer, uidCounter, valueNameToProducerPortMap);
-
-            // constant params are handled by setting their port as sticky.
-            // (Confusingly, they have PORTTYPE::INPUT and not PORTTYPE::STICKY_PORT - the latter are reserved for 
-            // immutable constant values that can be passed by value. Rename them to PORTTYPE::CONSTBYVALUE_PORT?)
-            if (param->options & paramOptionsConstant)
-                port->SetSticky(TRUE);
-
-            // now populate the input/output array we need to use for creating the task
-            if (portLoop == PTask::PORTTYPE::OUTPUT_PORT)
-                m_outputPorts[paramCount[portLoop]] = port;
-            else
-                m_inputPorts[paramCount[portLoop]] = port;
-            paramCount[portLoop]++;
-
-            // update the parameter values with the port. If it's an in/out port the 'in' side will be saved
-            if (param->port == NULL)
-                param->port = port;
-            if (portLoop == PTask::PORTTYPE::OUTPUT_PORT)
-                param->portOut = port;
-
-            // if we are initializing a buffer, do it now, temporaries will init to zero since that is the default init value
-            if (param->options & (paramOptionsInitialize|paramOptionsTemporary))
-            {
-                dt->SetInitialValue(&param->initValue, sizeof(param->initValue), dt->GetDatablockByteCount()/sizeof(param->initValue));
-            }
-        }
-        paramNum++;
-    }
-}
-
-template<class ElemType>
-void TaskDescriptor<ElemType>::CreateTask(Graph* graph)
-{
-    CompiledKernel * kernel = PTask::Runtime::GetHostFunctionCompiledKernel(
-        const_cast<char*>(m_taskName.c_str()), // cast away the const, really a PTask prototype error
-        (FARPROC)HostTaskDriver<ElemType>);
-    if(kernel == NULL)
-    {
-        throw exception("Failed to get PTask kernel");
-    }
-
-    m_task = graph->AddTask(
-        kernel, 
-        m_numInputPorts,
-        m_inputPorts,
-        m_numOutputPorts,
-        m_outputPorts,
-        (char*)m_taskName.c_str());
-
-    // This is a host task that will launch CUDA kernels on a dependent CUDA-capable accelerator.
-    m_task->BindDependentAcceleratorClass(ACCELERATOR_CLASS_CUDA, 1, TRUE);
-}
-
-template<class ElemType>
-void TaskDescriptor<ElemType>::CreateChannelsForInputs(
-    Graph* graph, 
-    std::map<const std::string, Port*>& valueNameToProducerPortMap, 
-    std::map<const std::string, std::vector<PTask::GraphInputChannel*>*>& inputNameToChannelsMap,
-    int verbosity)
-{
-    int iparam = 0; 
-    // start at 1 because we want to skip the TaskDescriptor parameter, which is always 0
-    for (UINT i=1; i<m_numInputPorts; i++)
-    {
-        // find the associated parameter data
-        ParamData<ElemType>* param;
-        // for (param = m_paramData[iparam]; 
-        //     !(param->options & (paramOptionsInput|paramOptionsConstant|paramOptionsInitialize))
-        //     && iparam < m_paramData.size();
-        //      param = m_paramData[++iparam])
-        //         ; 
-        for (param = m_paramData[iparam++];
-            !(param->options & (paramOptionsInput|paramOptionsConstant|paramOptionsInitialize))
-            && iparam < m_paramData.size();
-            param = m_paramData[iparam++])
-                ;
-
-        Port* destinationPort = m_inputPorts[i];
-        std::string valueName = m_inputNames.at(i);
-        assert(destinationPort == param->port);
-
-        if (valueName == "TaskDescriptor")
-        {
-            // nothing to do here
-        }
-        // if it's an initializer port and doesn't need to retain it's value, we are done
-        else if (destinationPort->GetPortType() == PORTTYPE::INITIALIZER_PORT && !(param->options & paramOptionsMaintainValue))
-        {
-            fprintf(stderr, " %s Initializer port doesn't need a source; port %d of %s\n", 
-                valueName.c_str(), i, this->TaskName().c_str());
-        }
-        else if (valueNameToProducerPortMap.find(valueName) != valueNameToProducerPortMap.end())
-        {
-            // If the input name has an entry in the value name to port map, create an internal channel
-            // from the associated port.
-            Port* sourcePort = valueNameToProducerPortMap[valueName];
-            std::string channelName = valueName;
-            channelName += " -> " + this->TaskName();
-            InternalChannel* channel = graph->AddInternalChannel(sourcePort, destinationPort, (char*)channelName.c_str());
-            if (verbosity >= 1) fprintf(stderr, 
-                "  Internal channel: %s connected to input port %d of %s\n", 
-                channelName.c_str(), i, this->TaskName().c_str());
-        }
-        else if (inputNameToChannelsMap.find(valueName) != inputNameToChannelsMap.end())
-        {
-            // If it has an entry in the input name to channels map, create a graph input channel
-            // for the associated port.
-            // TODO Should we be using a multichannel? Consequences of not?
-            std::vector<PTask::GraphInputChannel*>* channels = inputNameToChannelsMap[valueName];
-
-            std::string channelName = "InputChannel " + valueName + " -> " + this->TaskName();
-            GraphInputChannel* channel = graph->AddInputChannel(destinationPort, (char*)channelName.c_str());
-            if (verbosity >= 1) fprintf(stderr, 
-                "  Input channel: %s connected to input port %d of %s\n", 
-                channelName.c_str(), i, this->TaskName().c_str());
-            channels->push_back(channel);
-        }
-        // constants need to have an input channel too
-        else if (param->options & paramOptionsConstant)
-        {
-            // consider: do we need to save these in a map, if so should we unify this and the input branch of the if?
-            std::string channelName = "ConstantValue: " + valueName + " -> " + this->TaskName();
-            graph->AddInputChannel(destinationPort, (char*)channelName.c_str());
-            if (verbosity >= 1) fprintf(stderr, 
-                "  Input channel: %s connected to input port %d of %s\n", 
-                channelName.c_str(), i, this->TaskName().c_str());
-        }
-        else
-        {
-            bool finalCriteriaNode = false;
-            // check to see if this is the "FinalCriteria" task, if so it needs to have a 1x1 matrix with the value 1.0 pushed into it
-            if (m_taskType == taskComputeInputPartial && param->type == paramTypeMatrix)
-            {
-                DatablockTemplate* dataTemplate = param->port->GetTemplate();
-                BUFFERDIMENSIONS dim = dataTemplate->GetBufferDimensions();
-                if (dim.uiXElements == dim.uiYElements && dim.uiXElements == 0) // empty matrix
-                {
-                    dim.uiXElements = dim.uiYElements = dim.uiZElements = 1; // 1x1 matrix
-                    dim.cbElementStride = dim.cbPitch = sizeof(ElemType);
-                    dataTemplate->SetBufferDimensions(dim);
-                    param->port->SetSticky(true);
-                    ElemType val = (ElemType)1.0;
-                    Datablock* pblock = PTask::Runtime::AllocateDatablock(dataTemplate, (void *)&val, sizeof(ElemType), NULL);
-                    param->port->SetPermanentBlock(pblock);
-                    pblock->Lock();
-                    Matrix<ElemType>* matrix = new Matrix<ElemType>(1, 1, (ElemType*)pblock->GetDataPointer(false), matrixFlagDontOwnBuffer, MANAGEDEXTERN);
-                    pblock->SetApplicationContext(matrix);
-                    pblock->Unlock();
-                    pblock->Release();
-                    finalCriteriaNode = true;
-                    if (verbosity >= 1) fprintf(stderr, 
-                        "  BackPropogation source input %s set to value 1.0 on input port %d of %s\n", 
-                        valueName.c_str(), i, this->TaskName().c_str());
-
-                }
-            }
-
-            if (!finalCriteriaNode && verbosity >= 1) fprintf(stderr, 
-                "  ** No source for input %s to connect to input port %d of %s\n", 
-                valueName.c_str(), i, this->TaskName().c_str());
-        }
-    }
-}
-
-//CreateInitializerChannel - Create the initialization channel for a port
-// graph - graph to add channel to
-// port - port we are adding the initialization channel to
-// matrix - initial value to use
-// name - name of the init channel
-template<class ElemType>
-void TaskDescriptor<ElemType>::CreateInitializerChannel(
-    Graph* graph,
-    Port* port,
-    Matrix<ElemType>& matrix,
-    const std::string& name
-    )
-{
-    port->GetTemplate()->SetInitialValue(&matrix(0,0), (UINT)(matrix.GetNumElements()*sizeof(ElemType)), 1);
-    // if we already have another main channel defined (likely) move it over to the control channel
-    if (port->GetChannelCount() > 0)
-    {
-        Channel* mainChannel = port->GetChannel(0);
-        port->UnbindChannel(0);
-        port->BindControlChannel(mainChannel);
-    }
-    Channel* pInitChannel = graph->AddInitializerChannel(port, (char*)name.c_str());
-    pInitChannel->SetPredicationType(CE_DST, CGATEFN_OPEN_ON_BOF);
-    pInitChannel->SetInitialPropagatedControlSignal(DBCTLC_BOF);
-}
-
-// FindEmptyOutPorts - find unconnected output ports and hook up "bit buckets"
-// this is necessary because some values are produced in a forward pass that may not be consumed by the back pass, and need to be "capped"
-template<class ElemType>
-void TaskDescriptor<ElemType>::FindEmptyOutPorts(Graph* graph)
-{
-    Task* pTask = this->m_task;
-    std::map<UINT, Port*>* oPorts = pTask->GetOutputPortMap();
-    for(std::map<UINT, Port*>::iterator pi=oPorts->begin(); pi!=oPorts->end(); pi++) 
-    {
-        OutputPort * pOPort = reinterpret_cast<OutputPort*>(pi->second);
-        if(pOPort->GetChannelCount() == 0 && 
-           pOPort->GetControlChannelCount() == 0) 
-        {
-            // unbound output channel! plug it up
-            std::string name = pTask->GetTaskName();
-            name += "-unused";
-            GraphOutputChannel* pOutChannel = graph->AddOutputChannel(pOPort, (char*)name.c_str());
-            pOutChannel->SetPredicationType(CE_SRC, CGATEFN_DEVNULL);
-        }
-    }
-}
-
-// CreateBackAndInitChannel - Create back channels and initialization channels 
-// graph - graph to add the elements to
-// outputNameToChannelsMap - map from name to output channel
-template<class ElemType>
-void TaskDescriptor<ElemType>::CreateBackAndInitChannel(Graph* graph, std::map<const std::string, PTask::GraphOutputChannel*>& outputNameToChannelsMap)
-{
-    const vector<ParamData<ElemType>*>& params = this->GetParameters();
-    for (const ParamData<ElemType>* param : params)
-    {
-        // initialize the values at the beginning, copy from source matrix
-        if ((param->options & (paramOptionsInitOnBOF | paramOptionsMaintainValue | paramOptionsInitalValuesOnDestinations)) && param->assocData != NULL)
-        {
-            Matrix<ElemType>* matrix = (Matrix<ElemType>*)param->assocData;
-            if (matrix != NULL)
-            {
-                for (int i=0; i < param->portOut->GetChannelCount();i++)
-                {
-                    Channel* channel = param->portOut->GetChannel(i);
-                    Port* portDest = channel->GetBoundPort(CE_DST);
-
-                    // if we aren't putting initalizers on all destination ports, only MaintainValue on in/out parameters
-                    if (!(param->options & paramOptionsInitalValuesOnDestinations)
-                        && !portDest->IsInOutParameter())
-                        continue;
-
-                    // initialize all ports that get data from this port
-                    std::string name(channel->GetName());
-                    name.append("-Init");
-                    CreateInitializerChannel(graph, portDest, *matrix, name.c_str());
-                }
-            }
-        }
-
-        // check for if we need to save a value on output
-        if (param->options & paramOptionsSaveOnEOF)
-        {
-            std::string nameOutChannel = param->name;
-            GraphOutputChannel* outChannel = graph->AddOutputChannel(param->portOut, (char*)nameOutChannel.c_str());
-            outChannel->SetPredicationType(CE_SRC, CGATEFN_OPEN_ON_EOF);
-            outputNameToChannelsMap[nameOutChannel] = outChannel;
-        }
-    }
-}
-
-// PushActualMBSize - push ActualMBSize into the graph
-// learnableNodes - List of learnable nodes that need ActualMBSize
-// actualMBSize - actual Minibatch Size
-// signal - the PTask DataBlock signal to attach to this data
-template<class ElemType>
-void PTaskGraphBuilder<ElemType>::PushActualMBSize(const std::list<ComputationNodePtr>& learnableNodes, size_t actualMBSize, PTask::CONTROLSIGNAL signal/*=DBCTLC_NONE*/)
-{
-    for (ComputationNodePtr node : learnableNodes)
-    {
-        std::string inputName = msra::strfun::utf8(node->NodeName())+"_actualMBSize";
-        auto iter = m_inputNameToChannelsMap.find(inputName);
-        if (iter == m_inputNameToChannelsMap.end())
-            throw std::runtime_error("input channel not created for actualMBSize");
-        std::vector<PTask::GraphInputChannel*>* channels = iter->second;
-        for (PTask::GraphInputChannel* channel : *channels)
-        {
-            Datablock* pblock = PTask::Runtime::AllocateDatablock(channel->GetTemplate(), (void *)&actualMBSize, sizeof(size_t), channel, PT_ACCESS_DEFAULT, signal);
-            channel->Push(pblock);
-            pblock->Release();
-        }
-    }
-}
-
-// PushData - push data into the graph
-// data - the name->matrix map<> returned from datareaders
-// signal - the PTask DataBlock signal to attach to this data
-template<class ElemType>
-void PTaskGraphBuilder<ElemType>::PushData(std::map<std::wstring, Matrix<ElemType>*>& data, PTask::CONTROLSIGNAL signal/*=DBCTLC_NONE*/)
-{
-    for (std::pair<std::wstring, Matrix<ElemType>*> pair : data)
-    {
-        std::string inputName = msra::strfun::utf8(pair.first)+"_FunctionValues";
-        auto iter = m_inputNameToChannelsMap.find(inputName);
-        if (iter == m_inputNameToChannelsMap.end())
-            throw std::runtime_error("input channel not created for data matrix");
-        std::vector<PTask::GraphInputChannel*>* channels = iter->second;
-        for (PTask::GraphInputChannel* channel : *channels)
-        {
-            Matrix<ElemType>* matrix = pair.second;
-            PushMatrix(*matrix, channel, signal);
-        }
-    }
-}
-
-// PushMatrix - push matrix into the graph
-// matrix - the matrix to push into the graph
-// channel - channel we are pushing into
-// signal - the PTask DataBlock signal to attach to this data
-template<class ElemType>
-void PTaskGraphBuilder<ElemType>::PushMatrix(const Matrix<ElemType>& matrix, Channel* channel, PTask::CONTROLSIGNAL signal/*=DBCTLC_NONE*/)
-{
-    void* matrixData = (void*)matrix.BufferPointer();
-    size_t sizeData = matrix.BufferSize();
-    Datablock* pblock = PTask::Runtime::AllocateDatablock(channel->GetTemplate(), (void *)matrixData, (UINT)sizeData, channel, PT_ACCESS_DEFAULT, signal);
-    pblock->Lock();
-    Matrix<ElemType>* header = new Matrix<ElemType>(matrix.GetNumRows(), matrix.GetNumCols(), (ElemType*)pblock->GetDataPointer(false), matrixFlagDontOwnBuffer, MANAGEDEXTERN, matrix.NzCount());
-    pblock->SetApplicationContext(header);
-    pblock->Unlock();
-    channel->Push(pblock);
-    pblock->Release();
-}
-
-// GetValue - Get a single value out of the graph
-// node - node (used to get the name) we want to retieve the value from
-// returns - single value from the channel named the same as the node
-template<class ElemType>
-ElemType PTaskGraphBuilder<ElemType>::GetValue(ComputationNode<ElemType>* node)
-{
-    std::string nameOutChannel = msra::strfun::utf8(node->NodeName());
-    GraphOutputChannel* outChannel = m_outputNameToChannelsMap[nameOutChannel];
-    Datablock* dataBlock = outChannel->Pull();
-    dataBlock->Lock();
-    void* data = dataBlock->GetDataPointer(false);
-    assert(dataBlock->GetDataBufferLogicalSizeBytes() >= sizeof(ElemType));
-
-    // if we have the matrix header make sure it's a 1x1 matrix
-    if (dataBlock->GetApplicationContext() != NULL)
-    {
-        Matrix<ElemType>* mat = (Matrix<ElemType>*)dataBlock->GetApplicationContext();
-        assert(mat->GetNumCols() == mat->GetNumRows());
-        assert(mat->GetNumRows() == 1);
-    }
-    // return the value
-    ElemType elem = *(ElemType*)data;
-    dataBlock->Unlock();
-    return elem;
-}
-
-// GetValue - Get a single value out of the graph
-// node - node (used to get the name) we want to retieve the value from
-// returns - single value from the channel named the same as the node
-template<class ElemType>
-void PTaskGraphBuilder<ElemType>::GetValue(ComputationNode<ElemType>* node, Matrix<ElemType>& matTo)
-{
-    std::string nameOutChannel = msra::strfun::utf8(node->NodeName()) + "_FunctionValues";
-    if (m_outputNameToChannelsMap.find(nameOutChannel) == m_outputNameToChannelsMap.end())
-        throw std::logic_error("GetValue: name not found in output channel map");
-    GraphOutputChannel* outChannel = m_outputNameToChannelsMap[nameOutChannel];
-    Datablock* dataBlock = outChannel->Pull();
-    dataBlock->Lock();
-    void* data = dataBlock->GetDataPointer(false);
-
-    // if we have the matrix header make sure it is sane and copy it over
-    if (dataBlock->GetApplicationContext() != NULL)
-    {
-        Matrix<ElemType>* mat = (Matrix<ElemType>*)dataBlock->GetApplicationContext();
-        assert (dataBlock->GetDataBufferLogicalSizeBytes() >= mat->BufferSize());
-        matTo = *mat;
-    }
-    dataBlock->Unlock();
-}
-
-
-// CreateOutputChannels - Create the output channels for the graph
-template<class ElemType>
-void PTaskGraphBuilder<ElemType>::CreateOutputChannels(const vector<ComputationNodePtr>& nodes)
-{
-    for (ComputationNode<ElemType>* node : nodes)
-    {
-        std::string nameOutChannel = msra::strfun::utf8(node->NodeName());
-        std::string name = nameOutChannel+"_FunctionValues";
-        Port* port = m_valueNameToProducerPortMap[name];
-        GraphOutputChannel* outChannel = m_PTaskGraph->AddOutputChannel(port, (char*)nameOutChannel.c_str());
-        m_outputNameToChannelsMap[nameOutChannel] = outChannel;
-    }
-}
-
-// CreatePropogationPath - Create the path for the control signals to follow in the graph
-template<class ElemType>
-void PTaskGraphBuilder<ElemType>::CreatePropogationPath()
-{
-    Graph* graph = m_PTaskGraph;
-    if (m_verbosity >= 1) fprintf(stderr, "\nCreating Propogation Path through graph...\n");
-
-    // use the VERY COOL auto propogation path creator
-    m_PTaskGraph->SynthesizeControlPropagationPaths(DBCTLC_EOF);
-}
-
-template<class ElemType>
-Port* TaskDescriptor<ElemType>::CreatePortForTemplate(DatablockTemplate* dt,
-    UINT portType, 
-    std::string& valueName, 
-    UINT portIndex, UINT inoutPort, bool gpuBuffer, 
-    UINT& uidCounter,
-    std::map<const std::string, Port*>& valueNameToProducerPortMap
-    )
-{
-    // TODO Either get variable bindings for each ComputationNode sub-type, or standardize on a fixed set?
-    // std::string variableBinding = ???
-    // TODO For now, using the value name as the variable binding, as useful for debugging.
-    Port* port = PTask::Runtime::CreatePort(
-        (PTask::PORTTYPE)portType, dt, uidCounter++, (char*)valueName.c_str(), portIndex, inoutPort); // TODO InOutParamPortIndex should be -1? Other params?
-
-    // Set this port to be dependent on CUDA, which means all the buffers will stay on the CUDA side.
-    // Note that the index here is _not_ the accelerator number and must always be 0. Affinity is configured elsewhere.
-    // TODO: needs to change for host-side processes if we support them
-    if (gpuBuffer)
-    {
-        port->BindDependentAccelerator(ACCELERATOR_CLASS_CUDA, 0);
-    }
-
-    // Store the port, and also the name of the value it corresponds to.
-    switch(portType)
-    {
-    case PTask::PORTTYPE::OUTPUT_PORT:
-        m_outputNames.push_back(valueName);
-
-        // In the case of output ports, this port is the producer of this value.
-        // Store the name-port association globally, so that consumers can connect to it.
-        if (valueNameToProducerPortMap.find(valueName) != valueNameToProducerPortMap.end())
-        {
-            throw exception("Each value name may only be produced by one task/port");
-        }
-        valueNameToProducerPortMap[valueName] = port;
-        break;
-    case PTask::PORTTYPE::STICKY_PORT:
-    case PTask::PORTTYPE::INPUT_PORT:
-    case PTask::PORTTYPE::INITIALIZER_PORT:
-        m_inputNames.push_back(valueName);
-        break;
-    default:
-    case PTask::PORTTYPE::META_PORT:
-        throw exception("Unsupported port type");
-        break;
-    }
-    return port;
-}
-
-template<class ElemType>
-PTaskGraphBuilder<ElemType>::PTaskGraphBuilder() 
-{
-    // Level of console logging, useful for development/debugging.
-    // 0 = silent; 1 = summary; 2 = debug. 
-    // m_verbosity = 1;
-    m_verbosity = 2;
-
-    m_portUIDCounter = 0;
-    PTask::Runtime::SetUseOpenCL(FALSE);
-    PTask::Runtime::SetUseDirectX(FALSE);
-    PTask::Runtime::SetUseCUDA(TRUE);
-
-    // set the watchdog, so we can tell where a graph is hanging, if it does
-    PTask::Runtime::SetUseGraphMonitorWatchdog(TRUE);
-    PTask::Runtime::SetDispatchWatchdogThreshold(45000); // inital read of data can take a little time
-
-    //PTask::Runtime::SetDispatchLoggingEnabled(TRUE);
-
-    // CJR: 6/19: PTask tries to keep a default cuda context current on 
-    // threads that are likely to make CUDA API calls to limit common case 
-    // overheads for device context push/pop/attach/detach. This gets messed up
-    // when the application makes it's own context either explicitly or implicitly 
-    // (like CNTK) through calls to cuda runtime APIS. Inform PTask that CNTK does this:
-    PTask::Runtime::SetApplicationThreadsManagePrimaryContext(TRUE);
-       
-    // now limit PTask to only use the Accelerators we want it to
-    LimitAccelerators();
-
-    // time to initalize the runtime
-    PTask::Runtime::Initialize();
-
-    m_PTaskGraph = PTask::Runtime::CreateGraph(); // TODO Add graph name?
-    m_cn = NULL;
-}
-
-// destructor: stops and teardown the graph
-template<class ElemType>
-PTaskGraphBuilder<ElemType>::~PTaskGraphBuilder() 
-{
-    if (m_PTaskGraph == nullptr)
-        return;
-    if (m_PTaskGraph->IsRunning())
-        m_PTaskGraph->Stop();
-    m_PTaskGraph->Teardown();
-}
-
-template<class ElemType>
-void PTaskGraphBuilder<ElemType>::CreateTaskDescriptorForNode(ComputationNode<ElemType>* node, TaskType taskFlag)
-{
-    switch(taskFlag)
-    {
-    case taskEvaluate: // EvaluateThisNode() task
-        {
-        TaskDescriptorPtr taskDescriptor = node->GetPTaskDescriptor(taskFlag);
-        m_taskNameToTaskDescriptorMap[taskDescriptor->TaskName()] = taskDescriptor;
-        break;
-        }
-    case taskComputeInputPartial: // ComputeInputPartial() task
-        for (int i=0; i < node->ChildrenSize(); i++)
-        {
-            // if it's an input, we don't need to do a gradient
-            if (!node->Inputs(i)->NeedGradient())
-                continue;
-            TaskDescriptorPtr taskDescriptor = node->GetPTaskDescriptor(taskFlag, i);
-            std::string name = taskDescriptor->TaskName();
-            if (m_taskNameToTaskDescriptorMap.find(name) != m_taskNameToTaskDescriptorMap.end())
-                throw logic_error("Add support for multiple Partial derivatives to PTask");
-            m_taskNameToTaskDescriptorMap[name] = taskDescriptor;
-        }
-        break;
-    case taskUpdate:
-        {
-        TaskDescriptorPtr taskDescriptor = node->GetPTaskDescriptor(taskFlag);
-        m_taskNameToTaskDescriptorMap[taskDescriptor->TaskName()] = taskDescriptor;
-        break;
-        }
-    case taskEvaluateRecurrent: // EvaluateThisNode() Recurrent task
-    case taskComputeInputPartialRecurrent: // ComputeInputPartial() Recurrent task
-        throw runtime_error("Recurrent not yet implemented");
-        break;
-    }
-}
-
-
-// CreateInputName - create a entry in the input name to channels map
-// inputName - name for the entry
-template<class ElemType>
-void PTaskGraphBuilder<ElemType>::CreateInputName(std::string inputName)
-{
-    // But do create an (empty) entry for it in input name to channels map.
-    // Will populate later with graph input channels.
-    if (m_inputNameToChannelsMap.find(inputName) != m_inputNameToChannelsMap.end())
-    {
-        throw exception("Input names must be unique");
-    }
-    std::vector<PTask::GraphInputChannel*>* channels = new std::vector<PTask::GraphInputChannel*>();
-    m_inputNameToChannelsMap[inputName] = channels;
-}
-
-// Create descriptors to model PTask tasks that ComputationNodes will be mapped to.
-template<class ElemType>
-void PTaskGraphBuilder<ElemType>::CreateTaskDescriptorsForComputationNodes()
-{
-    if (m_verbosity >= 1) fprintf(stderr, "\nCreating PTask tasks for ComputationNodes ...\n");
-    for (auto nodeIter=m_computationNodes.begin(); nodeIter != m_computationNodes.end(); nodeIter++)
-    {
-        ComputationNodePtr node = *nodeIter;
-        std::wstring opName = node->OperationName();
-
-        if (m_verbosity >= 1) fprintf(stderr, "  %ls(%ls): ",
-            opName.c_str(), node->NodeName().c_str());
-
-        // Learnable parameter node types.
-        if (opName == LearnableParameter<ElemType>::TypeName())
-        {
-            // if we are computing the gradient
-            if (node->NeedGradient())
-            {
-                if (m_verbosity >= 1) fprintf(stderr, "Creating LearnableParameter Tasks\n");
-                CreateTaskDescriptorForNode(node, taskUpdate);
-                std::string inputName = msra::strfun::utf8(node->NodeName())+"_actualMBSize";
-                CreateInputName(inputName);
-            }
-        }
-        // Input node types
-        else if (opName == InputValue<ElemType>::TypeName() || node->RequirePreCompute())
-        {
-            // Don't create any tasks for an input node ...
-            if (m_verbosity >= 1) fprintf(stderr, "Input/Precompute node requires no tasks\n");
-            std::string inputName = msra::strfun::utf8(node->NodeName())+"_FunctionValues";
-            CreateInputName(inputName);
-        }
-        // Forward only node types.
-        else if (
-            opName == PerDimMeanVarNormalizationNode<ElemType>::TypeName() ||
-            opName == PerDimMeanVarDeNormalizationNode<ElemType>::TypeName() ||
-            opName == ErrorPredictionNode<ElemType>::TypeName())
-        {
-            if (m_verbosity >= 1) fprintf(stderr, "Creating forward task only\n");
-            CreateTaskDescriptorForNode(node, taskEvaluate);
-        }
-        // Regular computation node types.
-        else if (
-            opName == CrossEntropyWithSoftmaxNode<ElemType>::TypeName() ||
-            opName == MatrixL1RegNode<ElemType>::TypeName() ||
-            opName == MatrixL2RegNode<ElemType>::TypeName() ||
-            opName == SquareErrorNode<ElemType>::TypeName() ||
-            opName == ConvolutionNode<ElemType>::TypeName() ||
-            opName == MaxPoolingNode<ElemType>::TypeName() ||
-            opName == CosDistanceNode<ElemType>::TypeName() ||
-            opName == ElementTimesNode<ElemType>::TypeName() ||
-            opName == DiagTimesNode<ElemType>::TypeName() ||
-            opName == DropoutNode<ElemType>::TypeName() ||
-            opName == ExpNode<ElemType>::TypeName() ||
-            opName == LogNode<ElemType>::TypeName() ||
-            opName == CosineNode<ElemType>::TypeName() ||
-            opName == MinusNode<ElemType>::TypeName() ||
-            opName == NegateNode<ElemType>::TypeName() ||
-            opName == PlusNode<ElemType>::TypeName() ||
-            opName == RectifiedLinearNode<ElemType>::TypeName() ||
-            opName == ScaleNode<ElemType>::TypeName() ||
-            opName == SigmoidNode<ElemType>::TypeName() ||
-            opName == SoftmaxNode<ElemType>::TypeName() ||
-            opName == SumElementsNode<ElemType>::TypeName() ||
-            opName == TanhNode<ElemType>::TypeName() ||
-            opName == TimesNode<ElemType>::TypeName())
-        {
-            if (m_verbosity >= 1) fprintf(stderr, "Creating forward and back tasks\n");
-            CreateTaskDescriptorForNode(node, taskEvaluate);
-            CreateTaskDescriptorForNode(node, taskComputeInputPartial);
-        }
-        else
-        {
-            fprintf(stderr, "PTaskGraphBuilder does not (yet) support ComputationNode type %ls.\n",
-                opName.c_str());
-            throw exception("Unsupported computation node type");
-        }
-    }
-}
-
-// UpdateParameters - Update the parameters that may change by epoch
-// sgd - SGD pointer (to access constants in the class)
-// learnRatePerSample - learning rate per sample for this epoch
-// expectedMBSize - minibatch size for this epoch
-template<class ElemType>
-void PTaskGraphBuilder<ElemType>::UpdateParameters(void* sgd, const ElemType learnRatePerSample, const size_t expectedMBSize)
-{
-    std::list<ComputationNodePtr> precompNodes = m_cn->GetNodesRequirePreComputation(nullptr, false);
-    for (ComputationNodePtr node : precompNodes)
-    {
-        std::string name = msra::strfun::utf8(node->NodeName()) + "_FunctionValues";
-        std::map<const std::string, std::vector<PTask::GraphInputChannel*>*>::iterator iter 
-            = m_inputNameToChannelsMap.find(name);
-        if (!(iter == m_inputNameToChannelsMap.end()))
-        {
-            // make sure the matrix is in CPU memory before we add to the graph
-            Matrix<ElemType>& mat = node->FunctionValues();
-            mat.SetPreferredDeviceId(CPUDEVICE);
-            mat.TransferFromDeviceToDevice(mat.GetDeviceId(), CPUDEVICE, true);
-
-            vector<GraphInputChannel*>* inChannels = iter->second;
-            for (GraphInputChannel* input : *inChannels)
-            {
-                PushMatrix(node->FunctionValues(), input);
-            }
-        }
-    }
-
-    for (std::pair<const std::string, TaskDescriptorPtr> pair : m_taskNameToTaskDescriptorMap)
-    {
-        const TaskDescriptorPtr taskDescriptor = pair.second;
-        const std::vector<ParamData<ElemType>*>& params = taskDescriptor->GetParameters();
-        ComputationNodePtr node = taskDescriptor->GetNode();
-
-        // update needs the learning Rate and MBSizes, etc. Set them here
-        if (taskDescriptor->GetTaskType() == taskUpdate)
-        {
-            //static void UpdateWeightsS(const SGD* sgd, Matrix<ElemType>& functionValues, Matrix<ElemType>& gradientValues, Matrix<ElemType>& smoothedGradient, 
-            //    const ElemType learnRatePerSample, const size_t actualMBSize, const size_t expectedMBSize)
-            params[0]->SetConstant((void*)&sgd, sizeof(sgd));
-            params[4]->SetConstant((void*)&learnRatePerSample, sizeof(learnRatePerSample));
-            assert(sizeof(void*) == sizeof(expectedMBSize));
-            params[6]->SetConstant((void*)&expectedMBSize, sizeof(expectedMBSize));
-        }
-    }
-}
-
-// the Host Task driver
-template <class ElemType>
-static void __stdcall
-HostTaskDriver(LPDEPENDENTCONTEXT depContext)
-{
-    assert(depContext->nArguments > 1); // should always have more than one parameter (the context parameter)
-    assert(depContext->ppArguments != NULL);
-                
-    // look for a dependent binding
-    bool hasDependentBinding = false;
-    for (int i=1; i < depContext->nArguments; i++)
-    {
-        if (depContext->pbIsDependentBinding[i])
-        {
-            hasDependentBinding = true;
-            break;
-        }
-    }
-    
-    // if we have a dependent binding, need to launch GPU methods
-    if (hasDependentBinding) {
-        void * pvStream = depContext->pStreams[0];
-        cudaStream_t hStream = reinterpret_cast<cudaStream_t>(pvStream);
-        size_t device = reinterpret_cast<size_t>(depContext->pDependentDevices[0]);
-        onstream override(hStream);
-        Datablock** datablocks = depContext->ppDatablocks;
-
-        TaskDescriptor<ElemType>* taskDescriptor = *((TaskDescriptor<ElemType>**) depContext->ppArguments[0]);
-        const std::vector<ParamData<ElemType>*>& parameters = taskDescriptor->GetParameters();
-        void* newParam[10]; // array to hold parameters
-        assert(parameters.size() <= 10);
-        assert(depContext->nArguments == parameters.size()+1);
-        int argument=1; // first argument will always be the TaskDescriptor, then start regular arguments
-        for (int i = 0; i < parameters.size(); i++, argument++)
-        {
-            const ParamData<ElemType>*  paramData = parameters[i];
-            //JC Datablock* datablock = datablocks[i];
-            Datablock* datablock = datablocks[argument];
-            switch(paramData->type)
-            {
-            case paramTypeNode: // this parameter is a node pointer, just get it from the taskDescriptor
-                // NOTE: this can ONLY be used for accessing constant values in the node, not allowed to change anything.
-                newParam[i] = (void*)taskDescriptor->GetNode();
-                break;
-            case paramTypeMatrix: // the actual datapointer will be a GPU side buffer for the matrix
-                {
-                Matrix<ElemType>* matrix = (Matrix<ElemType>*)datablock->GetApplicationContext();
-                // determine the device for this argument
-                if (depContext->pbIsDependentBinding[argument])
-                    device = reinterpret_cast<size_t>(depContext->pvDeviceBindings[argument]);
-                else
-                    device = CPUDEVICE;
-                // if there is no matrix associated with the datablock yet, associate one
-                if (matrix == NULL || (paramData->options & paramOptionsOutput))
-                {
-                    Matrix<ElemType> *hostMatrix = (Matrix<ElemType> *)paramData->assocData; // reference the node based matrix
-                    bool sparse = hostMatrix->GetMatrixType() == SPARSE;
-                    matrix = new Matrix<ElemType>(hostMatrix->GetNumRows(), hostMatrix->GetNumCols(), (ElemType *)depContext->ppArguments[argument], 
-                        matrixFlagDontOwnBuffer | (sparse?matrixFormatSparse:matrixFormatDense), device);
-                    datablock->SetApplicationContext(matrix);
-                }
-                else
-                {
-                    // update the datapointer in case it changed
-                    assert(matrix->GetCurrentMatrixLocation() == GPU || matrix->GetCurrentMatrixLocation() == BOTH);
-                    matrix->SetValue(matrix->GetNumRows(), matrix->GetNumCols(), (ElemType*)depContext->ppArguments[argument], matrixFlagDontOwnBuffer, device);
-                }
-                newParam[i] = matrix;
-                break;
-                }
-                // everything else fits into a void* space
-            default:
-                newParam[i] = *((void**)depContext->ppArguments[argument]);
-                break;
-            }
-        }
-
-#if DUMPOUTPUT
-        fprintf(stderr, "%s\n", taskDescriptor->TaskName().c_str());
-#endif
-        // call the actual function now, must take all pointers/references or integral types that fit into sizeof(void*) bytes to work
-        FARPROC function = taskDescriptor->GetFunction();
-        typedef void (*func1)(void*);
-        typedef void (*func2)(void*, void*);
-        typedef void (*func3)(void*, void*, void*);
-        typedef void (*func4)(void*, void*, void*, void*);
-        typedef void (*func5)(void*, void*, void*, void*, void*);
-        typedef void (*func6)(void*, void*, void*, void*, void*, void*);
-        typedef void (*func7)(void*, void*, void*, void*, void*, void*, void*);
-        typedef void (*func8)(void*, void*, void*, void*, void*, void*, void*, void*);
-        typedef void (*func9)(void*, void*, void*, void*, void*, void*, void*, void*, void*);
-        switch (parameters.size())
-        {
-        case 1:
-            (*(func1)function)(newParam[0]);
-            break;
-        case 2:
-            (*(func2)function)(newParam[0], newParam[1]);
-            break;
-        case 3:
-            (*(func3)function)(newParam[0], newParam[1], newParam[2]);
-            break;
-        case 4:
-            (*(func4)function)(newParam[0], newParam[1], newParam[2], newParam[3]);
-            break;
-        case 5:
-            (*(func5)function)(newParam[0], newParam[1], newParam[2], newParam[3], newParam[4]);
-            break;
-        case 6:
-            (*(func6)function)(newParam[0], newParam[1], newParam[2], newParam[3], newParam[4], newParam[5]);
-            break;
-        case 7:
-            (*(func7)function)(newParam[0], newParam[1], newParam[2], newParam[3], newParam[4], newParam[5], newParam[6]);
-            break;
-        case 8:
-            (*(func8)function)(newParam[0], newParam[1], newParam[2], newParam[3], newParam[4], newParam[5], newParam[6], newParam[7]);
-            break;
-        case 9:
-            (*(func9)function)(newParam[0], newParam[1], newParam[2], newParam[3], newParam[4], newParam[5], newParam[6], newParam[7], newParam[8]);
-            break;
-
-        }
-
-        //TODO: we need to free up all the memory
-    } else {
-        // in this case the depContext->ppArguments[*]  are host pointers                 
-        // call host version if it exists
-        assert(false);  // no native version
-    }
-}
-
-template<class ElemType>
-void PTaskGraphBuilder<ElemType>::BuildFromComputationNetwork(ComputationNetwork<ElemType>* cn)
-{
-    m_cn = cn;
-    m_computationNodes = cn->GetAllNodes();
-
-    // set all the input nodes to have the biggest minibatch size we will see in this run
-    ComputationNodePtr criteriaNode = cn->FinalCriterionNodes()[0];
-    int actualMBSize = cn->GetMaxMBSize();
-    for (ComputationNodePtr node : cn->InputNodes(criteriaNode))
-    {
-        Matrix<ElemType>& matrix = node->FunctionValues();
-        matrix.Resize(matrix.GetNumRows(), actualMBSize);
-    }
-    // validate the network to make sure all the matrices get resized to match the inputs
-    cn->ValidateNetwork(criteriaNode);
-
-    // clear the Gradients for all nodes, because this will resize all the gradients to be the proper size
-    cn->ClearGradientForAllNodes(criteriaNode);
-
-    this->CreateTaskDescriptorsForComputationNodes();
-    this->ConfigureTaskInputsAndOutputs();
-    this->CreateTasksFromDescriptors();
-    this->CreateChannels();
-    this->CreateBackAndInitChannels();
-    CreateOutputChannels(cn->FinalCriterionNodes());
-    CreateOutputChannels(cn->EvaluationNodes());
-    //CreateOutputChannels(cn->OutputNodes());
-    this->FindEmptyOutPorts();
-    this->CreatePropogationPath();
-}
-
-template<class ElemType>
-void PTaskGraphBuilder<ElemType>::StartPTaskGraph()
-{
-    if (!IsRunning())
-        StartGraph();
-}
-
-// ApplicationContextCallback - Callback to manage the application context
-// eCallbackPoint - [in] The point in the datablock's lifecycle at which the callback was called. 
-// pDatablock -[in] The datablock being created, cloned or destroyed. 
-// ppApplicationContext - [in/out] The application context to be managed. 
-// Note: you must register the callback with the datablock template using the following call:
-//   pDataTemplate->SetApplicationContextCallback(PTaskGraphBuilder<ElemType>::ApplicationContextCallback);
-template<class ElemType>
-void __stdcall PTaskGraphBuilder<ElemType>::ApplicationContextCallback(
-    APPLICATIONCONTEXTCALLBACKPOINT eCallbackPoint,
-    const Datablock * pDatablock,
-    void ** ppApplicationContext
-    )
-{
-    switch (eCallbackPoint)
-    {
-    case CALLBACKPOINT_CREATE:
-        // currently we don't have enough information here to create anything
-        // so ignore
-        break;
-    case CALLBACKPOINT_CLONE:
-        // the block was cloned, so we need to clone the header also, 
-        // for now we will create the header the next time a NULL appcontext comes in
-        break;
-    case CALLBACKPOINT_DESTROY:
-        // this block is being destroyed, delete the matrix header
-        Matrix<ElemType>* pmat = (Matrix<ElemType>*)*ppApplicationContext;
-        if (pmat != nullptr) // if we have a matrix pointer, free it
-            delete pmat;
-        *ppApplicationContext = nullptr;
-        break;
-    }
-}
-
-#endif // USE_PTASK
-
-// instantiate classes
-template class PTaskGraphBuilder<float>;
-template class PTaskGraphBuilder<double>;
-
-template class TaskDescriptor<float>;
-template class TaskDescriptor<double>;
-
-template ParamData<float>* TaskDescriptor<float>::GradientParam(int, UINT,float);
-template ParamData<double>* TaskDescriptor<double>::GradientParam(int,UINT,double);
-
-}}}
diff --git a/MachineLearning/CNTK/PTaskGraphBuilder.h b/MachineLearning/CNTK/PTaskGraphBuilder.h
deleted file mode 100644
index 7a9f19a59..000000000
--- a/MachineLearning/CNTK/PTaskGraphBuilder.h
+++ /dev/null
@@ -1,405 +0,0 @@
-//
-// <copyright file="PTaskGraphBuilder.h" company="Microsoft">
-//     Copyright (c) Microsoft Corporation.  All rights reserved.
-// </copyright>
-//
-#pragma once
-
-#ifdef USE_PTASK
-#include "PTask.h"
-#else
-typedef void Port;
-typedef void Graph;
-typedef void Task;
-typedef void Channel;
-typedef int CONTROLSIGNAL;
-#define DBCTLC_BOF 1
-#define DBCTLC_EOF 2
-#define DBCTLC_NONE 3
-#endif
-
-#ifndef _WIN32          // BUGBUG: fix this once we need it
-typedef unsigned int UINT;
-typedef long long (*FARPROC)();
-#endif
-
-#include <string>
-//#include <cuda_runtime.h>
-
-namespace Microsoft { namespace MSR { namespace CNTK {
-#if 0   // TODO: where is this used? It creates the dependency on cuda_runtime.h, which we prefer to not have
-    extern __declspec(thread) cudaStream_t t_stream;
-
-    // class for stream overrides for PTask
-    // auto-class to set stream override inside a function
-    // usage at each function that calls CUDA:
-    //  onstream override(stream);
-    class onstream
-    {
-        cudaStream_t prevStream;
-    public:
-        onstream (cudaStream_t stream) { prevStream = GetStream(); SetStream(stream);}
-        ~onstream() { SetStream(prevStream); }
-    };
-#endif
-
-    // any  pointer/reference and all scalar types that fit into 8 bytes can be parameters
-    enum ParamType
-    {
-        paramTypeNone,
-        paramTypeMatrix,
-        paramTypePointer,
-        paramTypeReference = paramTypePointer, // both the same in memory
-        paramTypeShort,
-        paramTypeInteger,
-        paramTypeLong = paramTypeInteger,
-        paramTypeSizet,
-        paramTypeLongLong = paramTypeSizet,
-        paramTypeSingle,
-        paramTypeDouble,
-        paramTypeChar,
-        paramTypeBool,
-        paramTypeNode, // pass the node as first parameter, to be used ONLY for CONSTANT values
-    };
-
-    enum ParamOptions
-    {
-        paramOptionsNull = 0, // invalid value
-        paramOptionsInput = 1, // and input value for a task
-        paramOptionsOutput = 2, // an output value from a task
-        paramOptionsTemporary = 4, // for variables only used within one task (and then thrown away)
-        paramOptionsInitialize = 8, // initialize buffer with value
-        paramOptionsRecurrantIterator = 16, // iterator for recurrancy
-        paramOptionsConstant = 32, // constant value
-        paramOptionsMaintainValue = 64, // maintain value for in/out parameters, if not specified in/out means pass-through variable
-        paramOptionsNoPush = 128, // flag for parameter routines to not push the values
-        paramOptionsInitOnBOF = 256, // Initialize the buffer on BOF signal
-        paramOptionsSaveOnEOF = 512, // Save on EOF
-        paramOptionsInitalValuesOnDestinations = 1024, // Initial values need to be set on all destination ports, needed for Update
-    };
-
-    enum TaskType
-    {
-        taskNull,   // invalid value
-        taskEvaluate, // EvaluateThisNode() task
-        taskComputeInputPartial, // ComputeInputPartial() task
-        taskEvaluateRecurrent, // EvaluateThisNode() Recurrent task
-        taskComputeInputPartialRecurrent, // ComputeInputPartial() Recurrent task
-        taskUpdate, // update weight matricies
-        taskOutput, // output node, copy back to ComputationNode structure
-    };
-
-
-    // ParamData - parameter data, explains the parameter type
-    template<class ElemType>
-    class ParamData
-    {
-    public:
-        ParamType type; // data type of the parameter
-        void *assocData; // associated data (i.e. for Matrix, the matrix is the node this corresponds to)
-        Port* port;  // PTask port that is created for this parameter
-        Port* portOut; // output port for in/out parameters
-        UINT options; // parameter options (see ParamOptions above)
-        ElemType initValue; // initialization data for "paramOptionsInitialize"
-        std::string name; // name of the parameter
-
-        // constructors
-        ParamData(ParamType type, const std::string& name, UINT options) : type(type), name(name), assocData(NULL), port(NULL), portOut(NULL), options(options), initValue(0)
-        {}
-        ParamData(ParamType type, const std::string& name, void* data, UINT options) : type(type), name(name), assocData(data), port(NULL), portOut(NULL), options(options), initValue(0)
-        {}
-
-        // Initialize a parameter with an inital value
-        // initValue - value to initialize the port with
-        void SetInitialize(ElemType initVal)
-        { 
-            initValue = initVal;
-            options |= paramOptionsInitialize;
-        }
-
-        // SetConstant - Set a constant value to a port
-        // data - pointer to the data
-        // sizeData - size in bytes of the data
-        void SetConstant(void* data, int sizeData)
-        {
-#ifdef USE_PTASK
-            GraphInputChannel* channel = (GraphInputChannel*)port->GetChannel(0);
-            Datablock* pblock = PTask::Runtime::AllocateDatablock(port->GetTemplate(), (void *)data, sizeData, NULL);
-            channel->Push(pblock);
-            pblock->Release();
-#endif
-        }
-    };
-
-    // predeclaration
-    template<class ElemType>
-    class ComputationNetwork;
-
-    template<class ElemType>
-    class ComputationNode;
-
-    // Describes a PTask task.
-    // One instance is created for each actual task that will be added to the PTask graph.
-    // The descriptors are created first, to support phased assembly of the information 
-    // about the tasks and their relationships.
-    template<class ElemType>
-    class TaskDescriptor
-    {
-    protected:
-        typedef ComputationNode<ElemType>* ComputationNodePtr;
-
-    public:
-        TaskDescriptor(
-            const ComputationNode<ElemType>* node,
-            TaskType taskType,
-            size_t input=0
-            );
-
-        virtual ~TaskDescriptor();
-
-        const std::string& TaskName() const { return m_taskName; }
-        std::string& TaskName() { return m_taskName; }
-        bool IsForwardTask() const { return m_taskType == taskEvaluate || m_taskType == taskEvaluateRecurrent; }
-        TaskType GetTaskType() const { return m_taskType;}
-        const ComputationNodePtr GetNode() const {return m_node;}
-        const Task* GetTask() const {return m_task;}
-
-        ParamData<ElemType>* GradientParam(int index=-1, UINT options=paramOptionsInput, ElemType initValue=ElemType(0.0));
-        ParamData<ElemType>* FunctionParam(int index=-1, UINT options=paramOptionsOutput);
-        ParamData<ElemType>* MatrixParam(const Matrix<ElemType>& matrix, const std::string& name, UINT options=paramOptionsInput);
-        ParamData<ElemType>* Param(ParamType paramType, const std::string& name, UINT options=paramOptionsInput, void* data=nullptr);
-
-        void SetFunction(FARPROC function) {m_function = function;}
-#ifdef USE_PTASK
-        FARPROC GetFunction() {return m_function;}
-        void ConfigureInputsAndOutputs(UINT& uidCounter, std::map<const std::string, Port*>& valueNameToProducerPortMap);
-        void CreateTask(Graph* graph);
-
-        void CreateChannelsForInputs(
-            Graph* graph,
-            std::map<const std::string, Port*>& valueNameToProducerPortMap,
-            std::map<const std::string, std::vector<PTask::GraphInputChannel*>*>& inputNameToChannelsMap,
-            int verbosity);
-
-        void CreateInitializerChannel(
-            Graph* graph,
-            Port* port,
-            Matrix<ElemType>& matrix,
-            const std::string& name
-            );
-
-        void CreateBackAndInitChannel(Graph* graph, std::map<const std::string, PTask::GraphOutputChannel*>& outputNameToChannelsMap);
-        void FindEmptyOutPorts(Graph* graph);
-
-        // GetParamData - return the parameter data in parameter order
-        const std::vector<ParamData<ElemType>*>& GetParameters() const {return m_paramData;}
-    private:
-
-        Port* TaskDescriptor<ElemType>::CreatePortForTemplate(DatablockTemplate* dt,
-            UINT portType, 
-            std::string& valueName, 
-            UINT portIndex, UINT inoutPort, bool gpuBuffer, 
-            UINT& uidCounter,
-            std::map<const std::string, Port*>& valueNameToProducerPortMap
-            );
-
-
-        std::vector<const std::string>    m_inputNames;
-        std::vector<const std::string>    m_outputNames;
-
-        UINT                            m_numInputPorts;
-        Port**                          m_inputPorts;
-        UINT                            m_numOutputPorts;
-        Port**                          m_outputPorts;
-
-        static DatablockTemplate*       s_descriptorTemplate;
-#endif
-    private:
-        std::vector<ParamData<ElemType>*> m_paramData; // parameter data for CNTK task
-
-        ComputationNodePtr              m_node;
-        TaskType                        m_taskType;
-        std::string                     m_taskName;
-
-        Task*                           m_task;
-        FARPROC                         m_function;
-    }; 
-
-    template<class ElemType>
-    class PTaskGraphBuilder
-    {
-    private:
-        typedef ComputationNode<ElemType>* ComputationNodePtr;
-        typedef TaskDescriptor<ElemType>* TaskDescriptorPtr;
-    public:
-        PTaskGraphBuilder();
-        virtual ~PTaskGraphBuilder(); 
-
-        virtual void BuildFromComputationNetwork(ComputationNetwork<ElemType>* cn);
-        void StartPTaskGraph();
-        void UpdateParameters(void* sgd, const ElemType learnRatePerSample, const size_t expectedMBSize);
-
-        void PushActualMBSize(const std::list<ComputationNodePtr>& learnableNodes, size_t actualMBSize, CONTROLSIGNAL signal=DBCTLC_NONE);
-        void PushData(std::map<std::wstring, Matrix<ElemType>*>& data, CONTROLSIGNAL signal=DBCTLC_NONE);
-        void PushMatrix(const Matrix<ElemType>& matrix, Channel* channel, CONTROLSIGNAL signal=DBCTLC_NONE);
-
-        ElemType GetValue(ComputationNodePtr node);
-        void GetValue(ComputationNode<ElemType>* node, Matrix<ElemType>& matTo);
-#ifdef USE_PTASK
-
-        //static void WINAPI OutputParameter(const ComputationalNode<ElemType>* node, Matrix<ElemType> &functionValues);
-        static void __stdcall ApplicationContextCallback(
-            APPLICATIONCONTEXTCALLBACKPOINT eCallbackPoint,
-            const Datablock * pDatablock,
-            void ** ppApplicationContext
-            );
-
-
-    private:
-        // Copy constructor, should never be called.
-        PTaskGraphBuilder(const PTaskGraphBuilder<ElemType>& deepCopyFrom) {};
-
-        // Assignment operator, should never be called.
-        PTaskGraphBuilder<ElemType>& operator=(const PTaskGraphBuilder<ElemType>& deepCopyFrom) {assert(false); return *this; /* NOTE: just doing this to appease the compiler*/};
-
-        // Create descriptors to model PTask tasks that ComputationNodes will be mapped to.
-        void CreateTaskDescriptorsForComputationNodes();
-
-        void CreateTaskDescriptorForNode(ComputationNodePtr node, TaskType taskFlag);
-
-        void CreateInputName(std::string inputName);
-
-        // Configure task inputs and outputs.
-        void ConfigureTaskInputsAndOutputs()
-        {
-            if (m_verbosity >= 1) fprintf(stderr, "\nConfiguring task inputs and outputs ...\n");
-            for (auto taskIter=m_taskNameToTaskDescriptorMap.begin(); taskIter != m_taskNameToTaskDescriptorMap.end(); taskIter++)
-            {                
-                if (m_verbosity >= 2) fprintf(stderr, "  Task %s\n", taskIter->first.c_str());
-                TaskDescriptorPtr taskDescriptor = taskIter->second;
-                taskDescriptor->ConfigureInputsAndOutputs(m_portUIDCounter, m_valueNameToProducerPortMap);
-            }
-        }
-
-        // Create actual PTask tasks from task descriptors.
-        void CreateTasksFromDescriptors()
-        {
-            if (m_verbosity >= 1) fprintf(stderr, "\nCreating tasks from descriptors ...\n");
-            for (auto taskIter=m_taskNameToTaskDescriptorMap.begin(); taskIter != m_taskNameToTaskDescriptorMap.end(); taskIter++)
-            {                
-                if (m_verbosity >= 2) fprintf(stderr, "  Task %s\n", taskIter->first.c_str());
-                TaskDescriptorPtr taskDescriptor = taskIter->second;
-                taskDescriptor->CreateTask(m_PTaskGraph);
-            }
-        }
-
-        // Create PTask channels.
-        void CreateChannels()
-        {
-            if (m_verbosity >= 1) fprintf(stderr, "\nCreating PTask channels ...\n");
-            for (auto taskIter=m_taskNameToTaskDescriptorMap.begin(); taskIter != m_taskNameToTaskDescriptorMap.end(); taskIter++)
-            {                
-                if (m_verbosity >= 2) fprintf(stderr, "  Task %s\n", taskIter->first.c_str());
-                TaskDescriptorPtr taskDescriptor = taskIter->second;
-                taskDescriptor->CreateChannelsForInputs(m_PTaskGraph, m_valueNameToProducerPortMap, m_inputNameToChannelsMap, m_verbosity);
-            }
-        }
-
-        void CreateBackAndInitChannels()
-        {
-            if (m_verbosity >= 1) fprintf(stderr, "\nCreating LearnableParameter extra channels...\n");
-            for (auto taskIter=m_taskNameToTaskDescriptorMap.begin(); taskIter != m_taskNameToTaskDescriptorMap.end(); taskIter++)
-            {                
-                if (m_verbosity >= 2) fprintf(stderr, "  Task %s\n", taskIter->first.c_str());
-                TaskDescriptorPtr taskDescriptor = taskIter->second;
-                taskDescriptor->CreateBackAndInitChannel(m_PTaskGraph, m_outputNameToChannelsMap);
-            }
-        }
-
-        void FindEmptyOutPorts()
-        {
-            if (m_verbosity >= 1) fprintf(stderr, "\nFinding empty ports to plug...\n");
-            for (auto taskIter=m_taskNameToTaskDescriptorMap.begin(); taskIter != m_taskNameToTaskDescriptorMap.end(); taskIter++)
-            {                
-                TaskDescriptorPtr taskDescriptor = taskIter->second;
-                taskDescriptor->FindEmptyOutPorts(m_PTaskGraph);
-            }
-        }
-
-
-        void CreatePropogationPath();
-        void CreateOutputChannels(const vector<ComputationNodePtr>& nodes);
-
-        // LimitAccelerators - Limit the Accelerators to the ones chosen by the user (or decided by the "bestGPU" algorithm)
-        void LimitAccelerators()
-        {
-            UINT uiIndex = 0;
-
-            // get the devices from here
-            std::vector<int>::iterator vi;
-            std::vector<int> devices = g_bestGpu->GetDevices(BestGpu::RequeryDevices, bestGpuRequery);
-            for(vi=devices.begin(); vi!=devices.end(); vi++)
-            {
-                if (m_verbosity >= 1)
-                    printf("-- CUDA accelerator with CUDA id %d ENABLED for PTask\n", *vi);
-                PTask::Runtime::EnableAccelerator(ACCELERATOR_CLASS_CUDA, *vi);
-            }
-        }
-
-
-        // Start the PTask graph executing.
-        void StartGraph()
-        {
-            // Output the graph in Graphviz 'dot' format.
-            // Obtain Graphviz from http://www.graphviz.org/Download_windows.php
-            // Currently using version 2.34. Add C:\Program Files (x86)\Graphviz2.34\bin to PATH.
-            // Use:
-            //   dot -Tpng C:\temp\PTaskGraph.dot -o PTaskGraph.png 
-            // to render as PNG image.
-            if (m_verbosity >= 1)
-            {
-                fprintf(stderr, "Outputting graph to %s in Graphviz 'dot' format ...\n", PTASK_GRAPH_VIZ_FILE);
-                fprintf(stderr, "  Convert to .png with: dot -Tpng C:\\temp\\PTaskGraph.dot -o PTaskGraph.png\n");
-                fprintf(stderr, "  See PTaskGraphBuilder::StartGraph() for details.\n");
-            }
-            m_PTaskGraph->WriteDOTFile(PTASK_GRAPH_VIZ_FILE);
-
-            if (m_verbosity >= 1) fprintf(stderr, "Checking graph semantics ...\n");
-            Runtime::CheckGraphSemantics(m_PTaskGraph, TRUE, TRUE);
-
-            if (m_verbosity >= 1) fprintf(stderr, "Starting graph ...\n");
-            m_PTaskGraph->Run(TRUE); // single threaded for debugging
-        }
-
-        bool IsRunning()
-        {
-            return m_PTaskGraph->IsRunning();
-        }
-        
-        TaskDescriptor<ElemType>* PTaskGraphBuilder<ElemType>::GetPTaskDescriptorOutput(ComputationNodePtr node) const;
-
-        std::vector<ComputationNodePtr>                 m_computationNodes;
-        std::map<const std::string, TaskDescriptorPtr>  m_taskNameToTaskDescriptorMap;
-        std::map<const std::string, Port*>              m_valueNameToProducerPortMap;
-        std::map<const std::string, 
-            std::vector<PTask::GraphInputChannel*>*>    m_inputNameToChannelsMap;
-        std::map<const std::string, 
-            PTask::GraphOutputChannel*>                 m_outputNameToChannelsMap;
-        UINT                                            m_portUIDCounter;
-        Graph*                                          m_PTaskGraph;
-
-        int                                             m_verbosity;
-
-        // state for PTask nodes
-        ComputationNetwork<ElemType>*                   m_cn;
-#endif
-    };
-
-#ifdef USE_PTASK
-    // the Host Task driver
-    template <class ElemType>
-    static void __stdcall
-    HostTaskDriver(LPDEPENDENTCONTEXT depContext);
-#endif
-
-}}}
diff --git a/MachineLearning/CNTK/fileutil.cpp b/MachineLearning/CNTK/fileutil.cpp
deleted file mode 100644
index 432c1f354..000000000
--- a/MachineLearning/CNTK/fileutil.cpp
+++ /dev/null
@@ -1,2087 +0,0 @@
-//
-// fileutil.cpp - file I/O with error checking
-//
-//     Copyright (c) Microsoft Corporation.  All rights reserved.
-//
-// $Log: /Speech_To_Speech_Translation/dbn/dbn/fileutil.cpp $
-// 
-// 125   1/03/13 8:53p Kaisheny
-// Asynchronous SGD using data pipe.
-// 
-// 124   9/30/12 10:46a Fseide
-// new optional parameter to fuptodate()--caller can now choose whether a
-// missing input file, with target file present, will cause a failure or
-// considers the target up-to-date
-// 
-// 123   8/20/12 12:29p V-hansu
-// fixed a major bug in freadOrDie() for chunks > 15M units (breaking into
-// chunks was broken)
-// 
-// 122   4/01/12 12:02p Fseide
-// (expanded an error message)
-// 
-// 121   11/09/11 10:01 Fseide
-// added a new overload for fgetfilelines() that returns an array of char*
-// instead of strings, to avoid mem alloc
-// 
-// 120   10/27/11 18:52 Fseide
-// updated freadOrDie() to smaller chunk size
-// 
-// 119   10/27/11 13:40 Fseide
-// freadOrDie() now explicitly breaks up large reads because CRT fread()
-// does not handle them (due to a Windows bug)
-// 
-// 118   6/10/11 9:49 Fseide
-// new function fgetfilelines() for reading text files
-// 
-// 117   3/07/11 12:13 Fseide
-// actually implemented unlinkOrDie() (was a dummy)
-// 
-// 116   12/07/10 10:03 Fseide
-// (corrected the buffer size in fsetpos() fro 65336 to 65536)
-// 
-// 115   12/03/10 10:53 Fseide
-// fsetpos() optimization when seeking forward within the current read
-// buffer
-// 
-// 114   11/18/10 4:32p Kit
-// added missing header for errno
-// 
-// 113   11/18/10 9:20 Fseide
-// a basic optimization in fsetpos() to avoid rereading the buffer if
-// fsetpos() does not actually move the file pointer
-// 
-// 112   11/17/10 15:00 Fseide
-// new function fuptodate();
-// make_intermediate_dirs() moved to namespace msra::files (all new
-// functions should be put in there)
-// 
-// 111   11/12/10 16:43 Fseide
-// bug in getfiletime(), totally broken
-// 
-// 110   11/09/10 8:56 Fseide
-// some cleanup of make_intermediate_dirs()
-// 
-// 109   11/08/10 17:07 Fseide
-// new function make_intermediate_dirs()
-// 
-// 108   11/30/09 1:32p Kit
-// 
-// 107   2/05/09 19:05 Fseide
-// fgetline() now returns a non-const pointer, because user may want to
-// post-process the line, and the returned value is a user-specified
-// buffer anyway
-// 
-// 106   1/16/09 8:59 Fseide
-// exported fskipspace()
-// 
-// 105   1/16/09 8:47 Fseide
-// (a comment added)
-// 
-// 104   1/15/09 7:38 Fseide
-// some magic to unify fgetstring() for char and wchar_t to a single
-// template function
-// 
-// 103   1/14/09 19:27 Fseide
-// new functions fsetpos() and fgetpos();
-// added missing read-error checks to fget(w)string()
-// 
-// 102   1/14/09 12:38 Fseide
-// bug fix in fgetline(): missed an error check
-// 
-// 101   1/09/09 7:40 Fseide
-// (fixed a warning)
-// 
-// 100   1/08/09 16:38 Fseide
-// fopenOrDie() now supports "-" as the pathname, referring to stdin or
-// stdout
-// 
-// 99    1/08/09 15:32 Fseide
-// new funtion expand_wildcards()
-// 
-// 98    1/05/09 8:44 Fseide
-// (added comments)
-// 
-// 97    12/24/08 14:44 Fseide
-// added an overflow check to fputwfx()
-// 
-// 96    12/12/08 10:11a Qiluo
-// (change marker of banned APIs)
-// 
-// 95    12/11/08 7:40p Qiluo
-// (change marker of banned APIs)
-// 
-// 94    12/09/08 6:59p Qiluo
-// reverted stringerror => strerror
-// 
-// 93    12/09/08 6:37p Qiluo
-// fixed a few compilation bugs
-// 
-// 92    12/09/08 6:28p Qiluo
-// strerror => stringerror
-// 
-// 91    12/01/08 2:43p Qiluo
-// add markers for banned APIs, and refine the api fixing
-// 
-// 90    11/11/08 7:34p Qiluo
-// fix bug in strnlen
-// 
-// 89    11/11/08 18:27 Fseide
-// no longer disables C4996
-// 
-// 88    11/11/08 6:04p Qiluo
-// recover the old fputstring functions
-// 
-// 87    11/10/08 2:34p Qiluo
-// remove the dependency of header "StringUtil.h"
-// 
-// 86    10/31/08 5:08p Qiluo
-// remove banned APIs
-// 
-// 85    6/24/08 19:03 Fseide
-// added fgetwstring() and fputstring() for wstrings
-// 
-// 84    6/02/08 14:11 Fseide
-// fgetwfx() and wputwfx() now a bit more tolerant
-// 
-// 83    08-05-29 18:18 Llu
-// fix the interface of fputwav
-// 
-// 82    08-05-29 14:53 Llu
-// 
-// 81    08-05-29 13:53 Llu
-// add fputwav revise fgetwav using stl instead of short *
-// 
-// 80    3/19/08 16:13 Fseide
-// (better solution to prev. problem)
-// 
-// 79    3/19/08 16:07 Fseide
-// (#ifdef'ed out fprintfOrDie() in _MANAGED builds)
-// 
-// 78    10/30/07 16:46 Fseide
-// 
-// 77    3/27/07 13:54 Fseide
-// added 'using namespace std;' (was removed from message.h as it does not
-// belong there)
-// 
-// 76    1/30/07 1:59p Kit
-// Undid updates to fgetline error handling
-// 
-// 70    12/20/06 10:48a Kit
-// increased size of line buffer for fgetline because we seem to be
-// getting large strings in some rss feeds
-// 
-// 69    06-12-04 18:30 Llu
-// (fixed an unnecessary "deprecated string function" warning under VS
-// 2005)
-// 
-// 68    11/27/06 11:40 Fseide
-// new methods fgetwfx() and fputwfx() for direct access to simple PCM WAV
-// files
-// 
-// 67    10/14/06 18:31 Fseide
-// added char* version of fexists()
-// 
-// 66    5/14/06 19:58 Fseide
-// new function fsetmode()
-// 
-// 65    3/29/06 16:10 Fseide
-// increased buffer size in fgetfile() to 64k
-// 
-// 64    3/29/06 15:36 Fseide
-// changed to reading entire file instead of line-by-line, not changing
-// newlines anymore
-// 
-// 63    3/24/06 4:40p Rogeryu
-// workaround a VC 2003 header bug (va_start macro for references) in
-// MESSAGE/ERROR functions
-// 
-// 62    3/22/06 3:31p Rogeryu
-// (comments changed)
-// 
-// 61    3/21/06 5:21p Rogeryu
-// review and fix level2_security OACR warnings
-// 
-// 60    3/21/06 9:26a Rogeryu
-// review and fix OACR warnings
-// 
-// 59    06-03-15 15:41 Yushli
-// Suppress C4996 Warning per function
-// 
-// 58    06-03-14 12:11 Yushli
-// Suppress C4996 Warning on strerror per function
-// 
-// 57    06-03-14 10:33 Yushli
-// Suppress C4996 Warning per function.
-// 
-// 56    2/28/06 1:49p Kjchen
-// suppress oacr warning
-// 
-// 55    2/24/06 8:03p Kjchen
-// depress oacr warnings
-// 
-// 54    2/21/06 11:32a Kit
-// aadded filesize64 to support large files
-// 
-// 53    1/10/06 8:23p Rogeryu
-// fix a warning
-// 
-// 52    1/09/06 7:12p Rogeryu
-// wide version of fgetline
-// 
-// 51    12/20/05 21:15 Fseide
-// changed CreateFile() to CreateFileW()
-// 
-// 50    12/19/05 22:50 Fseide
-// setfiletime() fixed, now actually works
-// 
-// 49    12/19/05 21:52 Fseide
-// fputfile() added in 8-bit string version
-// 
-// 48    12/18/05 17:01 Fseide
-// fixed file-handle leaks in error conditions
-// 
-// 47    12/15/05 20:25 Fseide
-// added getfiletime(), setfiletime(), and fputfile() for strings
-// 
-// 46    9/27/05 12:22 Fseide
-// added wstring version of renameOrDie()
-// 
-// 45    9/22/05 12:26 Fseide
-// new method fexists()
-// 
-// 44    9/15/05 11:33 Fseide
-// new version of fgetline() that avoids buffer allocations, since this
-// seems very expensive esp. when reading a file line by line with
-// fgetline()
-// 
-// 43    9/05/05 4:57p F-xyzhao
-// renameOrDie(): changed string to std::string
-// 
-// 42    9/05/05 11:00 Fseide
-// new method renameOrDie()
-// 
-// 41    8/19/05 18:19 Fseide
-// bugfixes in WAVEHEADER::write and prepare
-// 
-// 40    8/19/05 18:02 Fseide
-// WAVEHEADER::write() now flushes
-// 
-// 39    8/19/05 17:56 Fseide
-// extended WAVEHEADER with write() and update()
-// 
-// 38    8/14/05 16:56 Fseide
-// fopenOrDie() now sets large buffer if 'S' option
-// 
-// 37    8/13/05 15:37 Fseide
-// added new version of fgetline that takes a buffer
-// 
-// 36    7/28/05 18:04 Fseide
-// bug fix in fgetin24 and fputint24
-// 
-// 35    7/26/05 18:54 Fseide
-// new functions fgetint24() and fputint24()
-// 
-// 34    5/10/05 14:12 Fseide
-// (level-4 warning fixed)
-// 
-// 33    5/10/05 11:57 Fseide
-// (level-4 warnings removed)
-// 
-// 32    5/09/05 12:07 Fseide
-// fixed for-loop conformance issues
-// 
-// 31    2/27/05 17:41 Fseide
-// recovered v29 that somehow got overwritten
-// 
-// 29    2/12/05 15:21 Fseide
-// fgetdouble() and fputdouble() added
-// 
-// 28    2/05/05 12:38 Fseide
-// new methods fputfile(), fgetfile();
-// new overload for filesize()
-// 
-// 27    2/03/05 22:34 Fseide
-// added new version of fgetline() that returns an STL string
-// 
-// 26    5/31/04 10:06 Fseide
-// new methods fseekOrDie(), ftellOrDie(), unlinkOrDie(), renameOrDie()
-// 
-// 25    3/19/04 4:01p Fseide
-// fwriteOrDie(): first argument changed to const
-// 
-// 24    2/21/04 10:26 Fseide
-// (compiler warnings eliminated)
-// 
-// 23    2/19/04 9:46p V-xlshi
-// 
-// 22    2/19/04 3:44p V-xlshi
-// fgetwavraw and fgetraw function is added, fgetwav is changed but its
-// functionality is the same with the old one.
-// 
-// 21    2/03/04 8:17p V-xlshi
-// 
-// 20    9/08/03 22:55 Fseide
-// fgetwav() can now read stereo PCM files
-// 
-// 19    8/15/03 15:40 Fseide
-// new method filesize()
-// 
-// 18    8/13/03 21:06 Fseide
-// new function fputbyte()
-// 
-// 17    8/13/03 15:37 Fseide
-// an error msg corrected
-// 
-// 16    8/07/03 22:04 Fseide
-// fprintfOrDie() now really dies in case of error
-// 
-// 15    7/30/03 5:09p Fseide
-// (eliminated a compiler warning)
-// 
-// 14    03-07-30 14:17 I-rogery
-// 
-// 13    7/25/03 6:07p Fseide
-// new functions fgetbyte() and fgetwav()
-// 
-// 12    6/03/03 5:23p Fseide
-// (some compiler warnings related to size_t eliminated)
-// 
-// 11    3/27/03 3:42p Fseide
-// fwriteOrDie() rewritten to break huge blocks into chunks of 16 MB
-// because Windows std C lib can't handle fwrite() with e.g. 100 MB in one
-// call
-// 
-// 10    7/23/02 9:00p Jlzhou
-// 
-// 9     7/03/02 9:25p Fseide
-// fcompareTag() now uses STRING type for both of its arguments (before,
-// it used const char * for one of them)
-// 
-// 8     6/10/02 3:14p Fseide
-// new functions fgettoken(), fgetfloat_ascii(), fskipNewline()
-// 
-// 7     6/07/02 7:26p Fseide
-// new functions fcheckTag_ascii() and fgetint_ascii()
-// 
-// 6     6/03/02 10:58a Jlzhou
-// 
-// 5     4/15/02 1:12p Fseide
-// void fputstring (FILE * f, const TSTRING & str) and fpad() added
-// 
-// 4     4/03/02 3:56p Fseide
-// VSS keyword and copyright added
-//
-// F. Seide 5 Mar 2002
-//
-
-#ifndef UNDER_CE    // fixed-buffer overloads not available for wince
-#ifdef _CRT_SECURE_CPP_OVERLOAD_STANDARD_NAMES  // fixed-buffer overloads for strcpy() etc.
-#undef _CRT_SECURE_CPP_OVERLOAD_STANDARD_NAMES
-#endif
-#define _CRT_SECURE_CPP_OVERLOAD_STANDARD_NAMES 1
-#endif
-
-#include "basetypes.h"
-#include "fileutil.h"
-#include "message.h"
-#include <stdio.h>
-#include <string.h>
-#include <ctype.h>
-#include "windows.h"    // for FILETIME
-#include <algorithm>    // for std::find
-
-#ifndef UNDER_CE  // some headers don't exist under winCE - the appropriate definitions seem to be in stdlib.h
-#include <fcntl.h>      // for _O_BINARY/TEXT - not needed for wince
-#include <io.h>         // for _setmode()
-#endif
-
-#include <errno.h>
-
-using namespace std;
-
-// ----------------------------------------------------------------------------
-// fopenOrDie(): like fopen() but terminate with err msg in case of error.
-// A pathname of "-" returns stdout or stdin, depending on mode, and it will
-// change the binary mode if 'b' or 't' are given. If you use this, make sure
-// not to fclose() such a handle.
-// ----------------------------------------------------------------------------
-
-static const wchar_t * strchr (const wchar_t * s, wchar_t v) { return wcschr (s, v); }
-
-// pathname is "-" -- open stdin or stdout. Changes bin mode if 'b' or 't' given.
-template<class _T> FILE * fopenStdHandle (const _T * mode)
-{
-    FILE * f = strchr (mode, 'r') ? stdin : stdout;
-    if (strchr (mode, 'b') || strchr (mode, 't'))   // change binary mode
-    {
-        // switch to binary mode if not yet (in case it is stdin)
-        int rc = _setmode (_fileno (f), strchr (mode, 'b') ? _O_BINARY : _O_TEXT);
-        if (rc == -1)
-            ERROR ("error switching stream to binary mode: %s", strerror (errno));
-    }
-    return f;
-}
-
-FILE * fopenOrDie (const STRING & pathname, const char * mode)
-{
-    FILE * f = (pathname[0] == '-') ? fopenStdHandle (mode) : fopen (pathname.c_str(), mode);
-    if (f == NULL)
-    {
-    ERROR ("error opening file '%s': %s", pathname.c_str(), strerror (errno));
-        return NULL;    // keep OACR happy
-    }
-    if (strchr (mode, 'S'))
-    {   // if optimized for sequential access then use large buffer
-    setvbuf (f, NULL, _IOFBF, 10000000);    // OK if it fails
-    }
-    return f;
-}
-
-FILE * fopenOrDie (const WSTRING & pathname, const wchar_t * mode)
-{
-    FILE * f = (pathname[0] == '-') ? fopenStdHandle (mode) : _wfopen (pathname.c_str(), mode);
-    if (f == NULL)
-    {
-        ERROR ("error opening file '%S': %s", pathname.c_str(), strerror (errno));
-        return NULL;    // keep OACR happy
-    }
-    if (strchr (mode, 'S'))
-    {   // if optimized for sequential access then use large buffer
-        setvbuf (f, NULL, _IOFBF, 10000000);    // OK if it fails
-    }
-    return f;
-}
-
-// ----------------------------------------------------------------------------
-// set mode to binary or text (pass 'b' or 't')
-// ----------------------------------------------------------------------------
-
-void fsetmode (FILE * f, char type)
-{
-    if (type != 'b' && type != 't')
-    {
-        ERROR ("fsetmode: invalid type '%c'");
-    }
-#ifdef UNDER_CE // winCE and win32 have different return types for _fileno
-    FILE *fd = _fileno (f);   // note: no error check possible
-#else
-    int fd = _fileno (f);   // note: no error check possible
-#endif
-    int mode = type == 'b' ? _O_BINARY : _O_TEXT;
-    int rc = _setmode (fd, mode);
-    if (rc == -1)
-    {
-    ERROR ("error changing file mode: %s", strerror (errno));
-    }
-}
-
-// ----------------------------------------------------------------------------
-// freadOrDie(): like fread() but terminate with err msg in case of error
-// ----------------------------------------------------------------------------
-
-void freadOrDie (void * ptr, size_t size, size_t count, FILE * f)
-{
-    // \\XXX\C$ reads are limited, with some randomness (e.g. 48 MB), on Windows 7 32 bit, so we break this into chunks of some MB. Meh.
-    while (count > 0)
-    {
-        size_t chunkn = min (count, 15*1024*1024);  // BUGBUG: I surely meant this limit to be bytes, not units of 'size'...
-        size_t n = fread (ptr, size, chunkn, f);
-        if (n != chunkn)
-            ERROR ("error reading from file: %s", strerror (errno));
-        count -= n;
-        ptr = n * size + (char*) ptr;
-    }
-}
-
-void freadOrDie (void * ptr, size_t size, size_t count, const HANDLE f)
-{
-    // \\XXX\C$ reads are limited, with some randomness (e.g. 48 MB), on Windows 7 32 bit, so we break this into chunks of some MB. Meh.
-    while (count > 0)
-    {
-        size_t chunkn = min (count * size, 15*1024*1024);  
-        DWORD n ;
-        ReadFile(f, ptr, (DWORD) chunkn, &n, NULL);
-        if (n != chunkn)
-            ERROR ("error number for reading from file: %s", GetLastError());
-        count -= (size_t) (n / size);
-        ptr = n + (char*) ptr;
-    }
-}
-
-// ----------------------------------------------------------------------------
-// fwriteOrDie(): like fwrite() but terminate with err msg in case of error;
-// Windows C std lib fwrite() has problems writing >100 MB at a time (fails
-// with Invalid Argument error), so we break it into chunks (yak!!)
-// ----------------------------------------------------------------------------
-
-void fwriteOrDie (const void * ptr, size_t size, size_t count, FILE * f)
-{
-    const char * p1 = (const char *) ptr;
-    size_t totalBytes = size * count;
-    while (totalBytes > 0)
-    {
-        size_t wantWrite = totalBytes;
-#define LIMIT (16*1024*1024)    // limit to 16 MB at a time
-        if (wantWrite > LIMIT)
-        {
-            wantWrite = LIMIT;
-        }
-        size_t n = fwrite ((const void *) p1, 1, wantWrite, f);
-        if (n != wantWrite)
-        {
-            ERROR ("error writing to file (ptr=0x%08lx, size=%d,"
-                " count=%d, writing %d bytes after %d): %s",
-                ptr, size, count, (int) wantWrite,
-                (int) (size * count - totalBytes),
-                strerror (errno));
-        }
-        totalBytes -= wantWrite;
-        p1 += wantWrite;
-    }
-}
-
-void fwriteOrDie (const void * ptr, size_t size, size_t count, const HANDLE f)
-{
-    const char * p1 = (const char *) ptr;
-    DWORD totalBytes = (DWORD) (size * count);
-    while (totalBytes > 0)
-    {
-        DWORD wantWrite = totalBytes;
-#define LIMIT (16*1024*1024)    // limit to 16 MB at a time
-        if (wantWrite > LIMIT)
-        {
-            wantWrite = LIMIT;
-        }
-        DWORD byteWritten = 0 ;
-        if (WriteFile(f, (const void *) p1, wantWrite, &byteWritten, NULL) == false)
-        {
-            ERROR ("error writing to file (ptr=0x%08lx, size=%d,"
-                " count=%d, writing %d bytes after %d): %s",
-                ptr, size, count, (int) wantWrite,
-                (int) (size * count - totalBytes),
-                strerror (errno));
-        }
-        totalBytes -= wantWrite;
-        p1 += wantWrite;
-    }
-}
-
-
-// ----------------------------------------------------------------------------
-// fprintfOrDie(): like fprintf() but terminate with err msg in case of error
-// ----------------------------------------------------------------------------
-
-#pragma warning(push)
-#pragma warning(disable : 4793) // 'vararg' : causes native code generation
-void fprintfOrDie (FILE * f, const char * fmt, ...)
-{
-    va_list arg_ptr;
-    va_start (arg_ptr, fmt);
-    int rc = vfprintf (f, fmt, arg_ptr);
-    if (rc < 0)
-    {
-        ERROR ("error writing to file: %s", strerror (errno));
-    }
-}
-#pragma warning(pop)
-
-// ----------------------------------------------------------------------------
-// fflushOrDie(): like fflush() but terminate with err msg in case of error
-// ----------------------------------------------------------------------------
-
-void fflushOrDie (FILE * f)
-{
-    int rc = fflush (f);
-    if (rc != 0)
-    {
-    ERROR ("error flushing to file: %s", strerror (errno));
-    }
-}
-
-// ----------------------------------------------------------------------------
-// filesize(): determine size of the file in bytes (with open file)
-// BUGBUG: how about files > 4 GB?
-// ----------------------------------------------------------------------------
-size_t filesize (FILE * f)
-{
-    long curPos = ftell (f);
-    if (curPos == -1L)
-    {
-    ERROR ("error determining file position: %s", strerror (errno));
-    }
-    int rc = fseek (f, 0, SEEK_END);
-    if (rc != 0)
-    {
-    ERROR ("error seeking to end of file: %s", strerror (errno));
-    }
-    long len = ftell (f);
-    if (len == -1L)
-    {
-    ERROR ("error determining file position: %s", strerror (errno));
-    }
-    rc = fseek (f, curPos, SEEK_SET);
-    if (rc != 0)
-    {
-    ERROR ("error resetting file position: %s", strerror (errno));
-    }
-    return (size_t) len;
-}
-
-// filesize(): determine size of the file in bytes (with pathname)
-size_t filesize (const wchar_t * pathname)
-{
-    FILE * f = fopenOrDie (pathname, L"rb");
-    try
-    {
-        size_t len = filesize (f);
-        fclose (f);
-        return (size_t) len;
-    }
-    catch (...)
-    {
-        fclose (f);
-        throw;
-    }
-}
-
-#ifndef UNDER_CE    // no 64-bit under winCE
-
-// filesize64(): determine size of the file in bytes (with pathname)
-__int64 filesize64 (const wchar_t * pathname)
-{
-    __stat64 fileinfo;
-    if (_wstat64 (pathname,&fileinfo) == -1) 
-        return 0;
-    else
-        return fileinfo.st_size;
-}
-#endif
-
-// ----------------------------------------------------------------------------
-// fseekOrDie(),ftellOrDie(), fget/setpos(): seek functions with error handling
-// ----------------------------------------------------------------------------
-
-long fseekOrDie (FILE * f, long offset, int mode)
-{
-    long curPos = ftell (f);
-    if (curPos == -1L)
-    {
-    ERROR ("error seeking: %s", strerror (errno));
-    }
-    int rc = fseek (f, offset, mode);
-    if (rc != 0)
-    {
-    ERROR ("error seeking: %s", strerror (errno));
-    }
-    return curPos;
-}
-
-unsigned __int64 fgetpos (FILE * f)
-{
-    fpos_t post;
-    int rc = ::fgetpos (f, &post);
-    if (rc != 0)
-        ERROR ("error getting file position: %s", strerror (errno));
-    return post;
-}
-
-void fsetpos (FILE * f, unsigned __int64 reqpos)
-{
-    // ::fsetpos() flushes the read buffer. This conflicts with a situation where
-    // we generally read linearly but skip a few bytes or KB occasionally, as is
-    // the case in speech recognition tools. This requires a number of optimizations.
-
-    unsigned __int64 curpos = fgetpos (f);
-    unsigned __int64 cureob = curpos + f->_cnt; // UGH: we mess with an internal structure here
-    while (reqpos >= curpos && reqpos < cureob)
-    {
-        // if we made it then do not call fsetpos()
-        if (reqpos == fgetpos (f))
-            return;
-
-        // if we seek within the existing buffer, then just move to the position by dummy reads
-        char buf[65536];
-        size_t n = min ((size_t) reqpos - (size_t) curpos, _countof (buf));
-        fread (buf, sizeof (buf[0]), n, f);     // (this may fail, but really shouldn't)
-        curpos += n;
-
-        // since we mess with f->_cnt, if something unexpected happened to the buffer then back off
-        if (curpos != fgetpos (f) || curpos + f->_cnt != cureob)
-            break;                              // oops
-    }
-
-    // actually perform the seek
-    fpos_t post = reqpos;
-    int rc = ::fsetpos (f, &post);
-    if (rc != 0)
-        ERROR ("error setting file position: %s", strerror (errno));
-}
-
-// ----------------------------------------------------------------------------
-// unlinkOrDie(): unlink() with error handling
-// ----------------------------------------------------------------------------
-
-void unlinkOrDie (const std::string & pathname)
-{
-    if (_unlink (pathname.c_str()) != 0 && errno != ENOENT)     // if file is missing that's what we want
-    ERROR ("error deleting file '%s': %s", pathname.c_str(), strerror (errno));
-}
-void unlinkOrDie (const std::wstring & pathname)
-{
-    if (_wunlink (pathname.c_str()) != 0 && errno != ENOENT)    // if file is missing that's what we want
-    ERROR ("error deleting file '%S': %s", pathname.c_str(), strerror (errno));
-}
-
-// ----------------------------------------------------------------------------
-// renameOrDie(): rename() with error handling
-// ----------------------------------------------------------------------------
-
-#ifndef UNDER_CE // CE only supports Unicode APIs
-void renameOrDie (const std::string & from, const std::string & to)
-{
-    if (!MoveFileA (from.c_str(),to.c_str()))
-    ERROR ("error renaming: %s", GetLastError());
-}
-#endif
-
-void renameOrDie (const std::wstring & from, const std::wstring & to)
-{
-    if (!MoveFileW (from.c_str(),to.c_str()))
-    ERROR ("error renaming: %s", GetLastError());
-}
-
-// ----------------------------------------------------------------------------
-// fexists(): test if a file exists
-// ----------------------------------------------------------------------------
-
-bool fexists (const wchar_t * pathname)
-{
-    WIN32_FIND_DATAW findFileData;
-    HANDLE hFind = FindFirstFileW (pathname, &findFileData);
-    if (hFind != INVALID_HANDLE_VALUE)
-    {
-        FindClose (hFind);
-        return true;
-    }
-    else
-    {
-        return false;
-    }
-}
-
-#ifndef UNDER_CE // CE only supports Unicode APIs
-bool fexists (const char * pathname)
-{
-    WIN32_FIND_DATAA findFileData;
-    HANDLE hFind = FindFirstFileA (pathname, &findFileData);
-    if (hFind != INVALID_HANDLE_VALUE)
-    {
-        FindClose (hFind);
-        return true;
-    }
-    else
-    {
-        return false;
-    }
-}
-#endif
-
-// ----------------------------------------------------------------------------
-// funicode(): test if a file uses unicode by reading its BOM
-// ----------------------------------------------------------------------------
-
-bool funicode (FILE * f)
-{
-    unsigned short testCode;
-    if (fread (&testCode, sizeof(short), 1, f) == 1 &&
-        (int)testCode == 0xFEFF)
-        return true;
-    fseek (f,0,SEEK_SET);
-    //rewind (f);
-    return false;
-}
-
-// ----------------------------------------------------------------------------
-// fgetline(): like fgets() but terminate with err msg in case of error;
-// removes the newline character at the end (like gets());
-// Returns 'buf' (always). buf guaranteed to be 0-terminated.
-// ----------------------------------------------------------------------------
-
-static inline wchar_t * fgets (wchar_t * buf, int n, FILE * f) { return fgetws (buf, n, f); }
-static inline string _utf8 (const string & s) { return s; }
-static inline string _utf8 (const wstring & s) { return msra::strfun::utf8 (s); }
-static inline size_t strnlen (wchar_t * s, size_t n) { return wcsnlen (s, n); }
-
-#ifdef UNDER_CE     // strlen for char * not defined in winCE
-static inline size_t strnlen (const char *s, size_t n) { return std::find (s,s+n,'\0') - s; }
-#endif
-
-template<class CHAR>
-CHAR * fgetline (FILE * f, CHAR * buf, int size)
-{
-
-    unsigned __int64 filepos = fgetpos (f); // (for error message only)
-    CHAR * p = fgets (buf, size, f);
-    if (p == NULL)            // EOF reached: next time feof() = true
-    {
-        if (ferror (f))
-            ERROR ("error reading line: %s", strerror (errno));
-        buf[0] = 0;
-        return buf;
-    }
-    size_t n = strnlen (p, size);
-
-    // check for buffer overflow
-
-    if (n >= (size_t) size -1)
-    {
-        basic_string<CHAR> example (p, n < 100 ? n : 100);
-        ERROR ("input line too long at file offset %I64d (max. %d characters allowed) [%s ...]",
-               filepos, size -1, _utf8 (example).c_str());
-    }
-
-    // remove newline at end
-
-    if (n > 0 && p[n-1] == '\n')    // UNIX and Windows style
-    {
-        n--;
-        p[n] = 0;
-        if (n > 0 && p[n-1] == '\r')    // Windows style
-        {
-            n--;
-            p[n] = 0;
-        }
-    }
-    else if (n > 0 && p[n-1] == '\r')    // Mac style
-    {
-        n--;
-        p[n] = 0;
-    }
-
-    return buf;
-}
-
-#if 0
-const wchar_t * fgetline (FILE * f, wchar_t * buf, int size)
-{
-    wchar_t * p = fgetws (buf, size, f);
-    if (p == NULL)            // EOF reached: next time feof() = true
-    {
-        if (ferror (f))
-            ERROR ("error reading line: %s", strerror (errno));
-        buf[0] = 0;
-        return buf;
-    }
-    size_t n = wcsnlen (p, size); // SECURITY NOTE: string use has been reviewed
-
-    // check for buffer overflow
-
-    if (n >= (size_t) size -1)
-    {
-        wstring example (buf, min (n, 100));
-        ERROR ("input line too long at file offset %U64d (max. %d characters allowed) [%S ...]",
-               fgetpos (f), size -1, example.c_str());
-    }
-
-    // remove newline at end
-
-    if (n > 0 && p[n-1] == L'\n')    // UNIX and Windows style
-    {
-        n--;
-        p[n] = 0;
-        if (n > 0 && p[n-1] == L'\r')    // Windows style
-        {
-            n--;
-            p[n] = 0;
-        }
-    }
-    else if (n > 0 && p[n-1] == L'\r')    // Mac style
-    {
-        n--;
-        p[n] = 0;
-    }
-
-    return buf;
-}
-#endif
-
-// STL string version
-std::string fgetline (FILE * f)
-{
-    fixed_vector<char> buf (1000000);
-    return fgetline (f, &buf[0], (int) buf.size());
-}
-
-// STL string version
-std::wstring fgetlinew (FILE * f)
-{
-    fixed_vector<wchar_t> buf (1000000);
-    return fgetline (f, &buf[0], (int) buf.size());
-}
-
-// STL string version avoiding most memory allocations
-void fgetline (FILE * f, std::string & s, ARRAY<char> & buf)
-{
-    buf.resize (1000000);    // enough? // KIT: increased to 1M to be safe
-    const char * p = fgetline (f, &buf[0], (int) buf.size());
-    s.assign (p);
-}
-
-void fgetline (FILE * f, std::wstring & s, ARRAY<wchar_t> & buf)
-{
-    buf.resize (1000000);    // enough? // KIT: increased to 1M to be safe
-    const wchar_t * p = fgetline (f, &buf[0], (int) buf.size());
-    s.assign (p);
-}
-
-// char buffer version
-void fgetline (FILE * f, ARRAY<char> & buf)
-{
-    const int BUF_SIZE = 1000000;    // enough? // KIT: increased to 1M to be safe
-    buf.resize (BUF_SIZE);
-    fgetline (f, &buf[0], (int) buf.size());
-    buf.resize (strnlen (&buf[0], BUF_SIZE) +1); // SECURITY NOTE: string use has been reviewed
-}
-
-void fgetline (FILE * f, ARRAY<wchar_t> & buf)
-{
-    const int BUF_SIZE = 1000000;    // enough? // KIT: increased to 1M to be safe
-    buf.resize (BUF_SIZE);
-    fgetline (f, &buf[0], (int) buf.size());
-    buf.resize (wcsnlen (&buf[0], BUF_SIZE) +1); // SECURITY NOTE: string use has been reviewed
-}
-
-// read a 0-terminated string
-const char * fgetstring (FILE * f, __out_z_cap(size) char * buf, int size)
-{
-    int i;
-    for (i = 0; ; i++)
-    {
-    int c = fgetc (f);
-    if (c == EOF)
-            ERROR ("error reading string or missing 0: %s", strerror (errno));
-    if (c == 0) break;
-    if (i >= size -1)
-    {
-        ERROR ("input line too long (max. %d characters allowed)", size -1);
-    }
-    buf[i] = (char) c;
-    }
-    ASSERT (i < size);
-    buf[i] = 0;
-    return buf;
-}
-
-const char * fgetstring (const HANDLE f, __out_z_cap(size) char * buf, int size)
-{
-    int i;
-    for (i = 0; ; i++)
-    {
-        char c; 
-        freadOrDie((void*) &c, sizeof(char), 1, f);
-        if (c == (char) 0) break;
-        if (i >= size -1)
-        {
-            ERROR ("input line too long (max. %d characters allowed)", size -1);
-        }
-        buf[i] = (char) c;
-    }
-    ASSERT (i < size);
-    buf[i] = 0;
-    return buf;
-}
-
-// read a 0-terminated wstring
-wstring fgetwstring (FILE * f)
-{
-    wstring res;
-    for (;;)
-    {
-    int c = fgetwc (f);
-    if (c == EOF)
-            ERROR ("error reading string or missing 0: %s", strerror (errno));
-    if (c == 0) break;
-        res.push_back ((wchar_t) c);
-    }
-    return res;
-}
-
-void fskipspace (FILE * f)
-{
-    for (;;)
-    {
-    int c = fgetc (f);
-    if (c == EOF)       // hit the end
-        {
-            if (ferror (f))
-                ERROR ("error reading from file: %s", strerror (errno));
-            break;
-        }
-    if (!isspace (c))    // end of space: undo getting that character
-        {
-            int rc = ungetc (c, f);
-            if (rc != c)
-                ERROR ("error in ungetc(): %s", strerror (errno));
-            break;
-        }
-    }
-}
-
-// fskipNewLine(): skip all white space until end of line incl. the newline
-void fskipNewline (FILE * f)
-{
-    char c;
-
-    // skip white space
-    
-    do
-    {
-    freadOrDie (&c, sizeof (c), 1, f);
-    } while (c == ' ' || c == '\t');
-
-    if (c == '\r')            // Windows-style CR-LF
-    {
-    freadOrDie (&c, sizeof (c), 1, f);
-    }
-
-    if (c != '\n')
-    {
-    ERROR ("unexpected garbage at end of line");
-    }
-}
-
-// read a space-terminated token
-// ...TODO: eat trailing space like fscanf() doessurrounding space)
-const char * fgettoken (FILE * f, __out_z_cap(size) char * buf, int size)
-{
-    fskipspace (f);                         // skip leading space
-    int c = -1;
-    int i;
-    for (i = 0; ; i++)
-    {
-    c = fgetc (f);
-    if (c == EOF) break;
-    if (isspace (c)) break;
-    if (i >= size -1)
-        ERROR ("input token too long (max. %d characters allowed)", size -1);
-    buf[i] = (char) c;
-    }
-    // ... TODO: while (isspace (c)) c = fgetc (f);      // skip trailing space
-    if (c != EOF)
-    {
-    int rc = ungetc (c, f);
-    if (rc != c)
-        ERROR ("error in ungetc(): %s", strerror (errno));
-    }
-    ASSERT (i < size);
-    buf[i] = 0;
-    return buf;
-}
-
-STRING fgettoken (FILE * f)
-{
-    char buf[80];
-    return fgettoken (f, buf, sizeof(buf)/sizeof(*buf));
-}
-
-// ----------------------------------------------------------------------------
-// fputstring(): write a 0-terminated string
-// ----------------------------------------------------------------------------
-
-void fputstring (FILE * f, const char * str)
-{
-    fwriteOrDie ((void *) str, sizeof (*str), strnlen (str, SIZE_MAX)+1, f); // SECURITY NOTE: string use has been reviewed
-}
-
-void fputstring (const HANDLE f, const char * str)
-{
-    fwriteOrDie ((void *) str, sizeof (*str), strnlen (str, SIZE_MAX)+1, f); // SECURITY NOTE: string use has been reviewed
-}
-
-void fputstring (FILE * f, const std::string & str)
-{
-    fputstring (f, str.c_str());
-}
-
-void fputstring (FILE * f, const wchar_t * str)
-{
-    fwriteOrDie ((void *) str, sizeof (*str), wcsnlen (str, SIZE_MAX)+1, f); // SECURITY NOTE: string use has been reviewed
-}
-
-void fputstring (FILE * f, const std::wstring & str)
-{
-    fputstring (f, str.c_str());
-}
-
-
-// ----------------------------------------------------------------------------
-// fgetTag(): read a 4-byte tag & return as a string
-// ----------------------------------------------------------------------------
-
-std::string fgetTag (FILE * f)
-{
-    char tag[5];
-    freadOrDie (&tag[0], sizeof (tag[0]), 4, f);
-    tag[4] = 0;
-    return std::string (tag);
-}
-
-std::string fgetTag (const HANDLE f)
-{
-    char tag[5];
-    freadOrDie (&tag[0], sizeof (tag[0]), 4, f);
-    tag[4] = 0;
-    return std::string (tag);
-}
-
-// ----------------------------------------------------------------------------
-// fcheckTag(): read a 4-byte tag & verify it; terminate if wrong tag
-// ----------------------------------------------------------------------------
-
-void fcheckTag (FILE * f, const char * expectedTag)
-{
-    fcompareTag (fgetTag (f), expectedTag);
-}
-
-
-void fcheckTag (const HANDLE f, const char * expectedTag)
-{
-    fcompareTag (fgetTag (f), expectedTag);
-}
-
-void fcheckTag_ascii (FILE * f, const STRING & expectedTag)
-{
-    char buf[20];    // long enough for a tag
-    fskipspace (f);
-    fgettoken (f, buf, sizeof(buf)/sizeof(*buf));
-    if (expectedTag != buf)
-    {
-        ERROR ("invalid tag '%s' found; expected '%s'", buf, expectedTag.c_str());
-    }
-}
-
-// ----------------------------------------------------------------------------
-// fcompareTag(): compare two tags; terminate if wrong tag
-// ----------------------------------------------------------------------------
-
-void fcompareTag (const STRING & readTag, const STRING & expectedTag)
-{
-    if (readTag != expectedTag)
-    {
-        ERROR ("invalid tag '%s' found; expected '%s'", 
-               readTag.c_str(), expectedTag.c_str());
-    }
-}
-
-// ----------------------------------------------------------------------------
-// fputTag(): write a 4-byte tag
-// ----------------------------------------------------------------------------
-
-void fputTag (FILE * f, const char * tag)
-{
-    const int TAG_LEN = 4;
-    ASSERT (strnlen (tag, TAG_LEN + 1) == TAG_LEN);
-    fwriteOrDie ((void *) tag, sizeof (*tag), strnlen (tag, TAG_LEN), f);
-}
-
-void fputTag(const HANDLE f, const char * tag)
-{
-    const int TAG_LEN = 4;
-    ASSERT (strnlen (tag, TAG_LEN + 1) == TAG_LEN);
-    fwriteOrDie ((void *) tag, sizeof (*tag), strnlen (tag, TAG_LEN), f);
-}
-
-// ----------------------------------------------------------------------------
-// fskipstring(): skip a 0-terminated string, such as a pad string
-// ----------------------------------------------------------------------------
-
-void fskipstring (FILE * f)
-{
-    char c;
-    do
-    {
-    freadOrDie (&c, sizeof (c), 1, f);
-    }
-    while (c);
-}
-
-// ----------------------------------------------------------------------------
-// fpad(): write a 0-terminated string to pad file to a n-byte boundary
-// (note: file must be opened in binmode to work properly on DOS/Windows!!!)
-// ----------------------------------------------------------------------------
-void fpad (FILE * f, int n)
-{
-    // get current writing position
-    int pos = ftell (f);
-    if (pos == -1)
-    {
-    ERROR ("error in ftell(): %s", strerror (errno));
-    }
-    // determine how many bytes are needed (at least 1 for the 0-terminator)
-    // and create a dummy string of that length incl. terminator
-    int len = n - (pos % n);
-    const char dummyString[] = "MSR-Asia: JL+FS";
-    size_t offset = sizeof(dummyString)/sizeof(dummyString[0]) - len;
-    ASSERT (offset >= 0);
-    fputstring (f, dummyString + offset);
-}
-// ----------------------------------------------------------------------------
-// fgetbyte(): read a byte value
-// ----------------------------------------------------------------------------
-
-char fgetbyte (FILE * f)
-{
-    char v;
-    freadOrDie (&v, sizeof (v), 1, f);
-    return v;
-}
-
-// ----------------------------------------------------------------------------
-// fgetshort(): read a short value
-// ----------------------------------------------------------------------------
-
-short fgetshort (FILE * f)
-{
-    short v;
-    freadOrDie (&v, sizeof (v), 1, f);
-    return v;
-}
-
-short fgetshort_bigendian (FILE * f)
-{
-    unsigned char b[2];
-    freadOrDie (&b, sizeof (b), 1, f);
-    return (short) ((b[0] << 8) + b[1]);
-}
-
-// ----------------------------------------------------------------------------
-// fgetint24(): read a 3-byte (24-bit) int value
-// ----------------------------------------------------------------------------
-
-int fgetint24 (FILE * f)
-{
-    int v;
-    ASSERT (sizeof (v) == 4);
-    freadOrDie (&v, sizeof (v) -1, 1, f);   // only read 3 lower-order bytes
-    v <<= 8;                                // shift up (upper 8 bits uninit'ed)
-    v >>= 8;                                // shift down 8 bits with sign-extend
-    return v;
-}
-
-// ----------------------------------------------------------------------------
-// fgetint(): read an int value
-// ----------------------------------------------------------------------------
-
-int fgetint (FILE * f)
-{
-    int v;
-    freadOrDie (&v, sizeof (v), 1, f);
-    return v;
-}
-
-int fgetint (const HANDLE f)
-{
-    int v;
-    freadOrDie (&v, sizeof (v), 1, f);
-    return v;
-}
-
-int fgetint_bigendian (FILE * f)
-{
-    unsigned char b[4];
-    freadOrDie (&b, sizeof (b), 1, f);
-    return (int) (((((b[0] << 8) + b[1]) << 8) + b[2]) << 8) + b[3];
-}
-
-int fgetint_ascii (FILE * f)
-{
-    fskipspace (f);
-    int res = 0;
-    char c;
-    freadOrDie (&c, sizeof (c), 1, f);
-    while (isdigit ((unsigned char)c))
-    {
-    res = (10 * res) + (c - '0');
-    freadOrDie (&c, sizeof (c), 1, f);
-    }
-    int rc = ungetc (c, f);
-    if (rc != c)
-    {
-    ERROR ("error in ungetc(): %s", strerror (errno));
-    }
-    return res;
-}
-
-// ----------------------------------------------------------------------------
-// fgetfloat(): read a float value
-// ----------------------------------------------------------------------------
-
-float fgetfloat (FILE * f)
-{
-    float v;
-    freadOrDie (&v, sizeof (v), 1, f);
-    return v;
-}
-
-float fgetfloat_bigendian (FILE * f)
-{
-    int bitpattern = fgetint_bigendian (f);
-    return *((float*) &bitpattern);
-}
-
-float fgetfloat_ascii (FILE * f)
-{
-    float val;
-    fskipspace (f);
-    int rc = fscanf (f, "%f", &val); // security hint: safe overloads
-    if (rc == 0)
-    ERROR ("error reading float value from file (invalid format): %s");
-    else if (rc == EOF)
-    ERROR ("error reading from file: %s", strerror (errno));
-    ASSERT (rc == 1);
-    return val;
-}
-
-// ----------------------------------------------------------------------------
-// fgetdouble(): read a double value
-// ----------------------------------------------------------------------------
-
-double fgetdouble (FILE * f)
-{
-    double v;
-    freadOrDie (&v, sizeof (v), 1, f);
-    return v;
-}
-
-// ----------------------------------------------------------------------------
-// fgetwav(): read an entire .wav file
-// ----------------------------------------------------------------------------
-
-void WAVEHEADER::prepareRest (int sampleCount)
-{
-    FmtLength   = 16; 
-
-    wFormatTag      = 1;
-    nAvgBytesPerSec = nSamplesPerSec * nBlockAlign;
-
-    riffchar[0] = 'R';
-    riffchar[1] = 'I';
-    riffchar[2] = 'F';
-    riffchar[3] = 'F';
-    if (sampleCount != -1)
-    {
-        DataLength  = sampleCount * nBlockAlign;
-        RiffLength  = 36 + DataLength;
-    }
-    else
-    {
-        DataLength  = 0xffffffff;
-        RiffLength  = 0xffffffff;
-    }
-
-    wavechar[0] = 'W';
-    wavechar[1] = 'A';
-    wavechar[2] = 'V';
-    wavechar[3] = 'E';
-    wavechar[4] = 'f';
-    wavechar[5] = 'm';
-    wavechar[6] = 't';
-    wavechar[7] = ' ';
-
-    datachar[0] = 'd';
-    datachar[1] = 'a';
-    datachar[2] = 't';
-    datachar[3] = 'a';
-}
-
-void WAVEHEADER::prepare (unsigned int Fs, int Bits, int Channels, int SampleCount)
-{
-    nChannels       = (short) Channels; 
-    nSamplesPerSec  = Fs; 
-    nBlockAlign     = (short) (Channels * (Bits/8));
-    nAvgBytesPerSec = Fs * nBlockAlign;
-    wBitsPerSample  = (short) Bits;
-
-    prepareRest (SampleCount);
-}
-
-void WAVEHEADER::prepare (const WAVEFORMATEX & wfx, int sampleCount /* -1 for unknown */)
-{
-    nChannels       = wfx.nChannels;
-    nSamplesPerSec  = wfx.nSamplesPerSec;
-    nBlockAlign     = wfx.nBlockAlign;
-    wBitsPerSample  = wfx.wBitsPerSample;
-
-    prepareRest (sampleCount);
-}
-
-void WAVEHEADER::write (FILE * f)
-{
-    fputTag (f, "RIFF");
-    fputint (f, RiffLength);
-    fputTag (f, "WAVE");
-    fputTag (f, "fmt ");
-    fputint (f, FmtLength);
-    fputshort (f, wFormatTag);
-    fputshort (f, nChannels);
-    fputint (f, nSamplesPerSec);
-    fputint (f, nAvgBytesPerSec);
-    fputshort (f, nBlockAlign);
-    fputshort (f, wBitsPerSample);
-    ASSERT (FmtLength == 16);
-    ASSERT (wFormatTag == 1);
-    fputTag (f, "data");
-    fputint (f, DataLength);
-    fflushOrDie (f);
-}
-
-/*static*/ void WAVEHEADER::update (FILE * f)
-{
-    long curPos = ftell (f);
-    if (curPos == -1L)
-    {
-    ERROR ("error determining file position: %s", strerror (errno));
-    }
-    unsigned int len = (unsigned int) filesize (f);
-    unsigned int RiffLength = len - 8;
-    unsigned int DataLength = RiffLength - 36;
-    fseekOrDie (f, 4, SEEK_SET);
-    fputint (f, RiffLength);
-    fseekOrDie (f, 40, SEEK_SET);
-    fputint (f, DataLength);
-    fseekOrDie (f, curPos, SEEK_SET);
-}
-
-unsigned int WAVEHEADER::read (FILE * f, signed short & wRealFormatTag, int & bytesPerSample)
-{
-    // read header
-    fcheckTag (f, "RIFF");
-    /*unsigned int riffLen = */ fgetint (f);
-    fcheckTag (f, "WAVE");
-    fcheckTag (f, "fmt ");
-    unsigned int fmtLen = fgetint (f);
-    wRealFormatTag = fgetshort (f);
-    if (wRealFormatTag == -2)   // MARecorder.exe [Ivan Tashev] puts a -2 for
-    {                           // 8-channel recordings (meaning unknown).
-        wRealFormatTag = 1;     // Workaround: pretend it is 1 (seems safe)
-    }
-    (wRealFormatTag == 1 || wRealFormatTag == 7)
-        || ERROR ("WAVEHEADER::read: wFormatTag=%d not supported for now", wRealFormatTag);
-    unsigned short wChannels = fgetshort (f);
-    unsigned long dwSamplesPerSec = fgetint (f);
-    unsigned int sampleRate = dwSamplesPerSec;
-    /*unsigned long dwAvgBytesPerSec = */ fgetint (f);
-    unsigned short wBlockAlign = fgetshort (f);
-    unsigned short wBitsPerSample = fgetshort (f);
-    (wBitsPerSample <= 16) || ERROR ("WAVEHEADER::read: invalid wBitsPerSample %d", wBitsPerSample);
-    bytesPerSample = wBitsPerSample / 8;
-    (wBlockAlign == wChannels * bytesPerSample)
-        || ERROR ("WAVEHEADER::read: wBlockAlign != wChannels*bytesPerSample not supported");
-    while (fmtLen > 16) // unused extra garbage in header
-    {
-        fgetbyte (f);
-        fmtLen--;
-    }
-    if (wRealFormatTag == 7)
-    {
-        (bytesPerSample == 1) || ERROR ("WAVEHEADER::read: invalid wBitsPerSample %d for mulaw", wBitsPerSample);
-        fcheckTag (f, "fact");
-        unsigned int factLen = fgetint (f);
-        while (factLen > 0)
-        {
-            fgetbyte (f);
-            factLen--;
-        }
-    }
-    fcheckTag (f, "data");
-    unsigned int dataLen = fgetint (f);
-    unsigned int numSamples = dataLen / wBlockAlign;
-
-    // prepare a nice wave header without junk (44 bytes, 16-bit PCM)
-    prepare (sampleRate, wBitsPerSample, wChannels, numSamples);
-
-    return numSamples;
-}
-
-static short toolULawToLinear(unsigned char p_ucULawByte)
-{
-    static short anExpLut[8] = { 0, 132, 396, 924, 1980, 4092, 8316, 16764 };
-    short nSign, nExponent, nMantissa, nSample;
-
-    p_ucULawByte=~p_ucULawByte;
-    nSign=(p_ucULawByte & 0x80);
-    nExponent=(p_ucULawByte >> 4) & 0x07;
-    nMantissa=p_ucULawByte & 0x0F;
-    nSample=anExpLut[nExponent]+(nMantissa<<(nExponent+3));
-    if(nSign != 0) 
-        nSample = -nSample;
-
-    return nSample;
-}
-
-// fgetwavraw(): only read data of .wav file. For multi-channel data, samples
-// are kept interleaved.
-static void fgetwavraw(FILE * f, ARRAY<short> & wav, const WAVEHEADER & wavhd)
-{
-    int bytesPerSample = wavhd.wBitsPerSample / 8;  // (sample size on one channel)
-    wav.resize (wavhd.DataLength / bytesPerSample);
-    if (wavhd.wFormatTag == 7)    // mulaw
-    {
-        (wavhd.nChannels == 1) || ERROR ("fgetwav: wChannels=%d not supported for mulaw", wavhd.nChannels);
-        ARRAY<unsigned char> data;
-        int numSamples = wavhd.DataLength/wavhd.nBlockAlign;
-        data.resize (numSamples);
-        freadOrDie (&data[0], sizeof (data[0]), numSamples, f);
-        for (int i = 0; i < numSamples; i++)
-        {
-            wav[i] = toolULawToLinear (data[i]);
-        }
-    }
-    else if (bytesPerSample == 2)
-    {   // note: we may be reading an interleaved multi-channel signal.
-        freadOrDie (&wav[0], sizeof (wav[0]), wav.size(), f);
-    }
-    // ... TODO: support 8 bit linear PCM samples (implement when needed; samples scaled to 'short')
-    else
-    {
-        ERROR ("bytesPerSample != 2 is not supported except mulaw format!\n");
-    }
-}
-
-// ----------------------------------------------------------------------------
-// fgetwav(): read an entire .wav file. Stereo is mapped to mono.
-// ----------------------------------------------------------------------------
-
-void fgetwav (FILE * f, ARRAY<short> & wav, int & sampleRate)
-{
-    WAVEHEADER wavhd;           // will be filled in for 16-bit PCM!!
-    signed short wFormatTag;    // real format tag as found in data
-    int bytesPerSample;         // bytes per sample as found in data
-
-    unsigned int numSamples = wavhd.read (f, wFormatTag, bytesPerSample);
-    sampleRate = (int) wavhd.nSamplesPerSec;
-
-    if (wavhd.nChannels == 1)
-    {
-        fgetwavraw (f, wav, wavhd);
-    }
-    else if (wavhd.nChannels == 2)
-    {
-        //read raw data        
-        ARRAY<short> buf;
-        buf.resize(numSamples * 2);
-        fgetwavraw(f, buf, wavhd);
-        
-        //map to mono
-        wav.resize (numSamples);
-        const short * p = &buf[0];
-        for (int i = 0; i < (int) numSamples; i++)
-        {
-            int l = *p++;
-            int r = *p++;
-            int mono = ((l + r) + 1) >> 1;
-            wav[i] = (short) mono;
-        }
-    }
-    else
-    {
-        ERROR ("bytesPerSample/wChannels != 2 needs to be implemented");
-    }
-}
-
-void fgetwav (const wstring & fn, ARRAY<short> & wav, int & sampleRate)
-{
-    auto_file_ptr f = fopenOrDie (fn, L"rbS");
-    fgetwav (f, wav, sampleRate);
-}
-
-// ----------------------------------------------------------------------------
-// ... TODO:
-//  - rename this function!!
-//  - also change to read header itself and return sample rate and channels
-// fgetraw(): read data of multi-channel .wav file, and separate data of multiple channels. 
-//            For example, data[i][j]: i is channel index, 0 means the first 
-//            channel. j is sample index.
-// ----------------------------------------------------------------------------
-
-void fgetraw (FILE *f, ARRAY< ARRAY<short> > & data, const WAVEHEADER & wavhd)
-{
-    ARRAY<short> wavraw;
-    fgetwavraw (f, wavraw, wavhd);
-    data.resize (wavhd.nChannels);
-    int numSamples = wavhd.DataLength/wavhd.nBlockAlign;
-    ASSERT (numSamples == (int) wavraw.size() / wavhd.nChannels);
-
-    for (int i = 0; i < wavhd.nChannels; i++)
-    {
-        data[i].resize (numSamples);
-
-        for (int j = 0; j < numSamples; j++)
-        {
-            data[i][j] = wavraw[wavhd.nChannels*j + i];
-        }
-    }
-}
-
-// ----------------------------------------------------------------------------
-// fgetwfx(), fputwfx(): direct access to simple WAV headers
-// ----------------------------------------------------------------------------
-
-// read header and skip to first data byte; return #samples
-unsigned int fgetwfx (FILE * f, WAVEFORMATEX & wfx)
-{
-    // read header
-    fcheckTag (f, "RIFF");
-    /*unsigned int riffLen = */ fgetint (f);
-    fcheckTag (f, "WAVE");
-    fcheckTag (f, "fmt ");
-    wfx.cbSize = sizeof (wfx);
-    int fmtLen = fgetint (f);
-    wfx.wFormatTag = fgetshort (f);
-    if (wfx.wFormatTag == -2)   // MARecorder.exe [Ivan Tashev] puts a -2 for
-    {                           // 8-channel recordings (meaning unknown).
-        wfx.wFormatTag = 1;     // Workaround: pretend it is 1 (seems safe)
-    }
-    (wfx.wFormatTag == 1 || wfx.wFormatTag == 3 || wfx.wFormatTag == 7)
-        || ERROR ("WAVEHEADER::read: wFormatTag=%d not supported for now", wfx.wFormatTag);
-    wfx.nChannels = fgetshort (f);
-    wfx.nSamplesPerSec = fgetint (f);
-    wfx.nAvgBytesPerSec = fgetint (f);
-    wfx.nBlockAlign = fgetshort (f);
-    wfx.wBitsPerSample = fgetshort (f);
-    // unused extra garbage in header
-    for ( ; fmtLen > 16; fmtLen--) fgetbyte (f);
-    fcheckTag (f, "data");
-    unsigned int dataLen = fgetint (f);
-    unsigned int numSamples = dataLen / wfx.nBlockAlign;
-    return numSamples;
-}
-
-void fputwfx (FILE *f, const WAVEFORMATEX & wfx, unsigned int numSamples)
-{
-    unsigned int DataLength = numSamples * wfx.nBlockAlign;
-    (DataLength / wfx.nBlockAlign == numSamples)
-        || ERROR ("fputwfx: data size exceeds WAV header 32-bit range");
-    unsigned int RiffLength = 36 + DataLength;
-    unsigned int FmtLength  = 16; 
-    // file header
-    ASSERT (wfx.cbSize == 0 || wfx.cbSize == FmtLength + 2);
-    fputTag (f, "RIFF");
-    fputint (f, RiffLength);
-    fputTag (f, "WAVE");
-    // 'fmt ' chunk (to hold wfx)
-    fputTag (f, "fmt ");
-    fputint (f, FmtLength);
-    fputshort (f, wfx.wFormatTag);
-    fputshort (f, wfx.nChannels);
-    fputint (f, wfx.nSamplesPerSec);
-    fputint (f, wfx.nAvgBytesPerSec);
-    fputshort (f, wfx.nBlockAlign);
-    fputshort (f, wfx.wBitsPerSample);
-    // data chunk
-    fputTag (f, "data");
-    fputint (f, DataLength);
-    fflushOrDie (f);
-}
-
-// ----------------------------------------------------------------------------
-// fputwav(): write an entire .wav file (16 bit PCM)
-// ----------------------------------------------------------------------------
-
-void fputwav (FILE * f, const vector<short> & wav, int sampleRate, int nChannels)
-{
-    f;wav;sampleRate;nChannels;
-    // construct WAVEFORMATEX
-    WAVEFORMATEX wfx;
-    wfx.cbSize = 16 + 2;  //fmt data + extra data
-    wfx.nAvgBytesPerSec = (DWORD)(sampleRate * nChannels * 2); //short: 2 bytes per sample
-    wfx.nBlockAlign = (WORD)nChannels * 2; //short: 2bytes per sample
-    wfx.nChannels = (WORD)nChannels;
-    wfx.nSamplesPerSec = sampleRate;
-    wfx.wBitsPerSample = 16;
-    wfx.wFormatTag = WAVE_FORMAT_PCM;
-    //putwfx
-    fputwfx (f, wfx, (unsigned int) wav.size());
-    // wrtie the data
-    fwriteOrDie (&wav[0], sizeof(wav[0]), wav.size(), f);
-}
-
-void fputwav (const wstring & fn, const vector<short> & wav, int sampleRate, int nChannels)
-{
-    auto_file_ptr f = fopenOrDie (fn, L"wbS");
-    fputwav (f, wav, sampleRate, nChannels);
-    fflushOrDie (f);    // after this, fclose() (in destructor of f) cannot fail
-}
-
-// ----------------------------------------------------------------------------
-// fputbyte(): write a byte value
-// ----------------------------------------------------------------------------
-
-void fputbyte (FILE * f, char v)
-{
-    fwriteOrDie (&v, sizeof (v), 1, f);
-}
-
-// ----------------------------------------------------------------------------
-// fputshort(): write a short value
-// ----------------------------------------------------------------------------
-
-void fputshort (FILE * f, short v)
-{
-    fwriteOrDie (&v, sizeof (v), 1, f);
-}
-
-// ----------------------------------------------------------------------------
-// fputint24(): write a 3-byte (24-bit) int value
-// ----------------------------------------------------------------------------
-
-void fputint24 (FILE * f, int v)
-{
-    ASSERT (sizeof (v) == 4);
-    fwriteOrDie (&v, sizeof (v) -1, 1, f);  // write low-order 3 bytes
-}
-
-// ----------------------------------------------------------------------------
-// fputint(): write an int value
-// ----------------------------------------------------------------------------
-
-void fputint (FILE * f, int v)
-{
-    fwriteOrDie (&v, sizeof (v), 1, f);
-}
-
-void fputint (const HANDLE f, int v)
-{
-    fwriteOrDie (&v, sizeof (v), 1, f);
-}
-
-// ----------------------------------------------------------------------------
-// fputfloat(): write a float value
-// ----------------------------------------------------------------------------
-
-void fputfloat (FILE * f, float v)
-{
-    fwriteOrDie (&v, sizeof (v), 1, f);
-}
-
-// ----------------------------------------------------------------------------
-// fputdouble(): write a double value
-// ----------------------------------------------------------------------------
-
-void fputdouble (FILE * f, double v)
-{
-    fwriteOrDie (&v, sizeof (v), 1, f);
-}
-
-// ----------------------------------------------------------------------------
-// fputfile(): write a binary block or a string as a file
-// ----------------------------------------------------------------------------
-
-void fputfile (const WSTRING & pathname, const ARRAY<char> & buffer)
-{
-    FILE * f = fopenOrDie (pathname, L"wb");
-    try
-    {
-        if (buffer.size() > 0)
-        {   // ^^ otherwise buffer[0] is an illegal expression
-            fwriteOrDie (&buffer[0], sizeof (buffer[0]), buffer.size(), f);
-        }
-        fcloseOrDie (f);
-    }
-    catch (...)
-    {
-        fclose (f);
-        throw;
-    }
-}
-
-void fputfile (const WSTRING & pathname, const std::wstring & string)
-{
-    FILE * f = fopenOrDie (pathname, L"wb");
-    try
-    {
-        if (string.length() > 0)
-        {   // ^^ otherwise buffer[0] is an illegal expression
-            fwriteOrDie (string.c_str(), sizeof (string[0]), string.length(), f);
-        }
-        fcloseOrDie (f);
-    }
-    catch (...)
-    {
-        fclose (f);
-        throw;
-    }
-}
-
-void fputfile (const WSTRING & pathname, const std::string & string)
-{
-    FILE * f = fopenOrDie (pathname, L"wb");
-    try
-    {
-        if (string.length() > 0)
-        {   // ^^ otherwise buffer[0] is an illegal expression
-            fwriteOrDie (string.c_str(), sizeof (string[0]), string.length(), f);
-        }
-        fcloseOrDie (f);
-    }
-    catch (...)
-    {
-        fclose (f);
-        throw;
-    }
-}
-
-// ----------------------------------------------------------------------------
-// fgetfile(): load a file as a binary block
-// ----------------------------------------------------------------------------
-
-void fgetfile (const WSTRING & pathname, ARRAY<char> & buffer)
-{
-    FILE * f = fopenOrDie (pathname, L"rb");
-    size_t len = filesize (f);
-    buffer.resize (len);
-    if (buffer.size() > 0)
-    {   // ^^ otherwise buffer[0] is an illegal expression
-        freadOrDie (&buffer[0], sizeof (buffer[0]), buffer.size(), f);
-    }
-    fclose (f);
-}
-
-void fgetfile (FILE * f, ARRAY<char> & buffer)
-{   // this version reads until eof
-    buffer.resize (0);
-    buffer.reserve (1000000);   // avoid too many reallocations
-    ARRAY<char> inbuf;
-    inbuf.resize (65536);         // read in chunks of this size
-    while (!feof (f))           // read until eof
-    {
-        size_t n = fread (&inbuf[0], sizeof (inbuf[0]), inbuf.size(), f);
-        if (ferror (f))
-        {
-            ERROR ("fgetfile: error reading from file: %s", strerror (errno));
-        }
-        buffer.insert (buffer.end(), inbuf.begin(), inbuf.begin() + n);
-    }
-    buffer.reserve (buffer.size());
-}
-
-// load it into RAM in one huge chunk
-static size_t fgetfilechars (const std::wstring & path, vector<char> & buffer)
-{
-    auto_file_ptr f = fopenOrDie (path, L"rb");
-    size_t len = filesize (f);
-    buffer.reserve (len +1);
-    freadOrDie (buffer, len, f);
-    buffer.push_back (0);           // this makes it a proper C string
-    return len;
-}
-
-template<class LINES> static void strtoklines (char * s, LINES & lines)
-{
-    char * context;
-    for (char * p = strtok_s (s, "\r\n", &context); p; p = strtok_s (NULL, "\r\n", &context))
-        lines.push_back (p);
-}
-
-void msra::files::fgetfilelines (const std::wstring & path, vector<char> & buffer, std::vector<std::string> & lines)
-{
-    // load it into RAM in one huge chunk
-    const size_t len = fgetfilechars (path, buffer);
-
-    // parse into lines
-    lines.resize (0);
-    lines.reserve (len / 20);
-    strtoklines (&buffer[0], lines);
-}
-
-// same as above but returning const char* (avoiding the memory allocation)
-vector<char*> msra::files::fgetfilelines (const wstring & path, vector<char> & buffer)
-{
-    // load it into RAM in one huge chunk
-    const size_t len = fgetfilechars (path, buffer);
-
-    // parse into lines
-    vector<char *> lines;
-    lines.reserve (len / 20);
-    strtoklines (&buffer[0], lines);
-    return lines;
-}
-
-// ----------------------------------------------------------------------------
-// getfiletime(), setfiletime(): access modification time
-// ----------------------------------------------------------------------------
-
-bool getfiletime (const wstring & path, FILETIME & time)
-{   // return file modification time, false if cannot be determined
-    WIN32_FIND_DATAW findFileData;
-    auto_handle hFind (FindFirstFileW (path.c_str(), &findFileData), ::FindClose);
-    if (hFind != INVALID_HANDLE_VALUE)
-    {
-        time = findFileData.ftLastWriteTime;
-        return true;
-    }
-    else
-    {
-        return false;
-    }
-}
-
-void setfiletime (const wstring & path, const FILETIME & time)
-{   // update the file modification time of an existing file
-    auto_handle h (CreateFileW (path.c_str(), FILE_WRITE_ATTRIBUTES,
-                                FILE_SHARE_READ|FILE_SHARE_WRITE, NULL,
-                                OPEN_EXISTING, FILE_ATTRIBUTE_NORMAL, NULL));
-    if (h == INVALID_HANDLE_VALUE)
-    {
-        ERROR ("setfiletime: error opening file: %d", GetLastError());
-    }
-    BOOL rc = SetFileTime (h, NULL, NULL, &time);
-    if (!rc)
-    {
-        ERROR ("setfiletime: error setting file time information: %d", GetLastError());
-    }
-}
-
-// ----------------------------------------------------------------------------
-// expand_wildcards -- wildcard expansion of a path, including directories.
-// ----------------------------------------------------------------------------
-
-// Win32-style variant of this function (in case we want to use it some day)
-// Returns 0 in case of failure. May throw in case of bad_alloc.
-static BOOL ExpandWildcards (wstring path, vector<wstring> & paths)
-{
-    // convert root to DOS filename convention
-    for (size_t k = 0; k < path.length(); k++) if (path[k] == '/') path[k] = '\\';
-
-    // remove terminating backslash
-    size_t last = path.length() -1;
-    if (last >= 0 && path[last] == '\\') path.erase (last);
-
-    // convert root to long filename convention
-    //if (path.find (L"\\\\?\\") != 0)
-    //    path = L"\\\\?\\" + root;
-
-    // split off everything after first wildcard
-    size_t wpos = path.find_first_of (L"*?");
-    if (wpos == 2 && path[0] == '\\' && path[1] == '\\')
-        wpos = path.find_first_of (L"*?", 4);   // 4=skip "\\?\"
-    if (wpos == wstring::npos)
-    {   // no wildcard: just return it
-        paths.push_back (path);
-        return TRUE;
-    }
-
-    // split off everything afterwards if any
-    wstring rest;   // remaining path after this directory
-    size_t spos = path.find_first_of (L"\\", wpos +1);
-    if (spos != wstring::npos)
-    {
-        rest = path.substr (spos +1);
-        path.erase (spos);
-    }
-
-    // crawl folder
-    WIN32_FIND_DATAW ffdata;
-    auto_handle hFind (::FindFirstFileW (path.c_str(), &ffdata), ::FindClose);
-    if (hFind == INVALID_HANDLE_VALUE) 
-    {
-        DWORD err = ::GetLastError();
-        if (rest.empty() && err == 2) return TRUE;  // no matching file: empty
-        return FALSE;                   // another error
-    }
-    size_t pos = path.find_last_of (L"\\");
-    if (pos == wstring::npos) throw std::logic_error ("unexpected missing \\ in path");
-    wstring parent = path.substr (0, pos);
-    do
-    {
-        // skip this and parent directory
-        bool isDir = ((ffdata.dwFileAttributes & (FILE_ATTRIBUTE_DIRECTORY | FILE_ATTRIBUTE_REPARSE_POINT)) != 0);
-        if (isDir && ffdata.cFileName[0] == '.') continue;
-
-        wstring filename = parent + L"\\" + ffdata.cFileName;
-        if (rest.empty())
-        {
-            paths.push_back (filename);
-        }
-        else if (isDir)     // multi-wildcards: further expand
-        {
-            BOOL rc = ExpandWildcards (filename + L"\\" + rest, paths);
-            rc; // error here means no match, e.g. Access Denied to one subfolder
-        }
-    } while (::FindNextFileW(hFind, &ffdata) != 0);
-    return TRUE;
-}
-
-void expand_wildcards (const wstring & path, vector<wstring> & paths)
-{
-    BOOL rc = ExpandWildcards (path, paths);
-    if (!rc)
-        ERROR ("error in expanding wild cards '%S': %S", path.c_str(), FormatWin32Error (::GetLastError()).c_str());
-}
-
-// ----------------------------------------------------------------------------
-// make_intermediate_dirs() -- make all intermediate dirs on a path
-// ----------------------------------------------------------------------------
-
-static void mkdir (const wstring & path)
-{
-    int rc = _wmkdir (path.c_str());
-    if (rc >= 0 || errno == EEXIST)
-        return;     // no error or already existing --ok
-    if (errno == EACCES)
-    {
-        // bug in _wmkdir(): returns access_denied if folder exists but read-only --check existence
-        DWORD att = ::GetFileAttributesW (path.c_str());
-        if (att != INVALID_FILE_ATTRIBUTES || (att & FILE_ATTRIBUTE_DIRECTORY) != 0)
-            return; // ok
-    }
-    ERROR ("make_intermediate_dirs: error creating intermediate directory %S", path.c_str());
-}
-
-// make subdir of a file including parents
-void msra::files::make_intermediate_dirs (const wstring & filepath)
-{
-    vector<wchar_t> buf;
-    buf.resize (filepath.length() +1, 0);
-    wcscpy_s (&buf[0], buf.size(), filepath.c_str());
-    wstring subpath;
-    int skip = 0;
-    // if share (\\) then the first two levels (machine, share name) cannot be made
-    if ((buf[0] == '/' && buf[1] == '/') || (buf[0] == '\\' && buf[1] == '\\'))
-    {
-        subpath = L"/";
-        skip = 2;           // skip two levels (machine, share)
-    }
-    // make all constituents except the filename (to make a dir, include a trailing slash)
-    for (const wchar_t * p = wcstok (&buf[0], L"/\\"); p; p = wcstok (NULL, L"/\\"))
-    {
-        if (subpath != L"" && subpath != L"/" && subpath != L"\\" && skip == 0)
-        {
-            mkdir (subpath);
-        }
-        else if (skip > 0) skip--;  // skip this level
-        // rebuild the final path
-        if (subpath != L"") subpath += L"/";
-        subpath += p;
-    }
-}
-
-// ----------------------------------------------------------------------------
-// fuptodate() -- test whether an output file is at least as new as an input file
-// ----------------------------------------------------------------------------
-
-// test if file 'target' is not older than 'input' --used for make mode
-// 'input' must exist if 'inputrequired'; otherweise if 'target' exists, it is considered up to date
-// 'target' may or may not exist
-bool msra::files::fuptodate (const wstring & target, const wstring & input, bool inputrequired)
-{
-    FILETIME targettime;
-    if (!getfiletime (target, targettime)) return false;        // target missing: need to update
-    FILETIME inputtime;
-    if (!getfiletime (input, inputtime)) return !inputrequired; // input missing: if required, pretend to be out of date as to force caller to fail
-    ULARGE_INTEGER targett, inputt;
-    memcpy (&targett, &targettime, sizeof (targett));
-    memcpy (&inputt,  &inputtime, sizeof (inputt));
-    return !(targett.QuadPart < inputt.QuadPart);               // up to date if target not older than input
-}
diff --git a/MachineLearning/CNTK/prebuild.bat b/MachineLearning/CNTK/prebuild.bat
index 3abac808b..acbb6ec36 100644
--- a/MachineLearning/CNTK/prebuild.bat
+++ b/MachineLearning/CNTK/prebuild.bat
@@ -1,9 +1,11 @@
 @echo off 
 setlocal enabledelayedexpansion
 
-echo #ifndef _BUILDINFO_H > buildinfo.h
-echo #define _BUILDINFO_H >> buildinfo.h 
+::: This is called as a pre-build step for the CNTK executable.
+::: It creates buildinfo.h, which makes version information available to the executable itself.
 
+echo #ifndef _BUILDINFO_H > buildinfo.h$$
+echo #define _BUILDINFO_H >> buildinfo.h$$ 
 
 FOR /F "usebackq" %%i IN (`hostname`) DO SET HOST=%%i           
 :: assuming hostname always exists 
@@ -11,22 +13,25 @@ FOR /F "usebackq" %%i IN (`hostname`) DO SET HOST=%%i
 :: not sure whether git in path ? 
 git --version 2 > nul 
 if not %ERRORLEVEL% == 9009 (
-    echo #define _GIT_EXIST >> buildinfo.h
+    echo #define _GIT_EXIST >> buildinfo.h$$
     FOR /F "usebackq" %%i IN (`git rev-parse --abbrev-ref HEAD`) DO SET BRANCH=%%i
     FOR /F "usebackq" %%i IN (`git rev-parse HEAD`) DO SET COMMIT=%%i
-    echo #define _BUILDBRANCH_  "!BRANCH!"      >> buildinfo.h
-    echo #define _BUILDSHA1_    "!COMMIT!"      >> buildinfo.h
-) 
+    echo #define _BUILDBRANCH_  "!BRANCH!"      >> buildinfo.h$$
+    echo #define _BUILDSHA1_    "!COMMIT!"      >> buildinfo.h$$
+)
 
-
-echo #define _BUILDER_ "%USERNAME%"     >> buildinfo.h 
-echo #define _BUILDMACHINE_ "!HOST!"    >> buildinfo.h
+echo #define _BUILDER_ "%USERNAME%"     >> buildinfo.h$$ 
+echo #define _BUILDMACHINE_ "!HOST!"    >> buildinfo.h$$
 
 set a=%~dp0
 set buildpath="%a:\=\\%"
-echo #define _BUILDPATH_    %buildpath%     >> buildinfo.h
+echo #define _BUILDPATH_    %buildpath%     >> buildinfo.h$$
 
 set cuda_path="%CUDA_PATH:\=\\%"
-echo #define _CUDA_PATH_    %cuda_path%     >> buildinfo.h
+echo #define _CUDA_PATH_    %cuda_path%     >> buildinfo.h$$
 
-echo #endif >> buildinfo.h
+echo #endif >> buildinfo.h$$
+
+::: update file only if it changed (otherwise CNTK.cpp will get rebuilt each time)
+fc buildinfo.h$$ buildinfo.h > NUL
+if not ERRORLEVEL 0 move /Y buildinfo.h$$ buildinfo.h
diff --git a/MachineLearning/CNTKEval/CNTKEval.vcxproj b/MachineLearning/CNTKEval/CNTKEval.vcxproj
index baab9935c..679eb72cd 100644
--- a/MachineLearning/CNTKEval/CNTKEval.vcxproj
+++ b/MachineLearning/CNTKEval/CNTKEval.vcxproj
@@ -78,7 +78,7 @@
       <DelayLoadDLLs>CNTKMath.dll; nvml.dll; cudart64_70.dll</DelayLoadDLLs>
     </Link>
     <PostBuildEvent>
-      <Command>XCOPY /I /Y "%ProgramW6432%\NVIDIA Corporation\NVSMI\nvml*.dll" $(TargetDir)</Command>
+      <Command>xcopy /I /D /Y "%ProgramW6432%\NVIDIA Corporation\NVSMI\nvml*.dll" $(TargetDir)</Command>
       <Message>Copying NVidia GDK extension DLL to target folder</Message>
     </PostBuildEvent>
   </ItemDefinitionGroup>
@@ -108,12 +108,13 @@
       <DelayLoadDLLs>CNTKMath.dll; nvml.dll; cudart64_70.dll</DelayLoadDLLs>
     </Link>
     <PostBuildEvent>
-      <Command>XCOPY /I /Y "%ProgramW6432%\NVIDIA Corporation\NVSMI\nvml*.dll" $(TargetDir)</Command>
+      <Command>xcopy /I /D /Y "%ProgramW6432%\NVIDIA Corporation\NVSMI\nvml*.dll" $(TargetDir)</Command>
       <Message>Copying NVidia GDK extension DLL to target folder</Message>
     </PostBuildEvent>
   </ItemDefinitionGroup>
   <ItemGroup>
     <ClInclude Include="..\..\Common\Include\basetypes.h" />
+    <ClInclude Include="..\..\Common\Include\Basics.h" />
     <ClInclude Include="..\..\Common\Include\Eval.h" />
     <ClInclude Include="..\..\Common\Include\File.h" />
     <ClInclude Include="..\..\Common\Include\fileutil.h" />
diff --git a/MachineLearning/CNTKEval/CNTKEval.vcxproj.filters b/MachineLearning/CNTKEval/CNTKEval.vcxproj.filters
index df2805694..b0bbab3f2 100644
--- a/MachineLearning/CNTKEval/CNTKEval.vcxproj.filters
+++ b/MachineLearning/CNTKEval/CNTKEval.vcxproj.filters
@@ -43,6 +43,9 @@
     <ClInclude Include="..\..\Common\Include\TimerUtility.h">
       <Filter>Common\Include</Filter>
     </ClInclude>
+    <ClInclude Include="..\..\Common\Include\Basics.h">
+      <Filter>Common\Include</Filter>
+    </ClInclude>
   </ItemGroup>
   <ItemGroup>
     <Filter Include="Common">
diff --git a/MachineLearning/MachineLearning.sln b/MachineLearning/MachineLearning.sln
deleted file mode 100644
index 02eb8439f..000000000
--- a/MachineLearning/MachineLearning.sln
+++ /dev/null
@@ -1,29 +0,0 @@
-
-Microsoft Visual Studio Solution File, Format Version 12.00
-# Visual Studio 2012
-Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "cn", "cn\cn.vcxproj", "{E6F26F9A-FF64-4F0A-B749-CD309EE357EE}"
-EndProject
-Global
-	GlobalSection(TeamFoundationVersionControl) = preSolution
-		SccNumberOfProjects = 2
-		SccEnterpriseProvider = {4CA58AB2-18FA-4F8D-95D4-32DDF27D184C}
-		SccTeamFoundationServer = http://vstfcodebox:8080/tfs/kappa
-		SccLocalPath0 = .
-		SccProjectUniqueName1 = cn\\cn.vcxproj
-		SccProjectName1 = cn
-		SccLocalPath1 = cn
-	EndGlobalSection
-	GlobalSection(SolutionConfigurationPlatforms) = preSolution
-		Debug|x64 = Debug|x64
-		Release|x64 = Release|x64
-	EndGlobalSection
-	GlobalSection(ProjectConfigurationPlatforms) = postSolution
-		{E6F26F9A-FF64-4F0A-B749-CD309EE357EE}.Debug|x64.ActiveCfg = Debug|x64
-		{E6F26F9A-FF64-4F0A-B749-CD309EE357EE}.Debug|x64.Build.0 = Debug|x64
-		{E6F26F9A-FF64-4F0A-B749-CD309EE357EE}.Release|x64.ActiveCfg = Release|x64
-		{E6F26F9A-FF64-4F0A-B749-CD309EE357EE}.Release|x64.Build.0 = Release|x64
-	EndGlobalSection
-	GlobalSection(SolutionProperties) = preSolution
-		HideSolutionNode = FALSE
-	EndGlobalSection
-EndGlobal
diff --git a/MachineLearning/MachineLearning.vssscc b/MachineLearning/MachineLearning.vssscc
deleted file mode 100644
index 6cb031bcf..000000000
--- a/MachineLearning/MachineLearning.vssscc
+++ /dev/null
@@ -1,10 +0,0 @@
-""
-{
-"FILE_VERSION" = "9237"
-"ENLISTMENT_CHOICE" = "NEVER"
-"PROJECT_FILE_RELATIVE_PATH" = ""
-"NUMBER_OF_EXCLUDED_FILES" = "0"
-"ORIGINAL_PROJECT_FILE_PATH" = ""
-"NUMBER_OF_NESTED_PROJECTS" = "0"
-"SOURCE_CONTROL_SETTINGS_PROVIDER" = "PROJECT"
-}
diff --git a/Makefile.cpu b/Makefile.cpu
index 5e7ee5db5..4fabc23d5 100644
--- a/Makefile.cpu
+++ b/Makefile.cpu
@@ -68,7 +68,7 @@ COMMON_SRC = Common/fileutil.cpp Common/DataWriter.cpp Common/ConfigFile.cpp Com
 
 MATH_SRC = Math/Math/Matrix.cpp Math/Math/CPUMatrix.cpp Math/Math/CPUSparseMatrix.cpp Math/Math/NoGPU.cpp
 CN_SRC =  MachineLearning/CNTK/NetworkDescriptionLanguage.cpp MachineLearning/CNTK/CNTK.cpp MachineLearning/CNTK/ComputationNode.cpp \
-          MachineLearning/CNTK/ModelEditLanguage.cpp MachineLearning/CNTK/PTaskGraphBuilder.cpp \
+          MachineLearning/CNTK/ModelEditLanguage.cpp \
           MachineLearning/CNTK/SimpleNetworkBuilder.cpp MachineLearning/CNTK/tests.cpp MachineLearning/CNTKEval/CNTKEval.cpp
 BINARYREADER_SRC = DataReader/BinaryReader/BinaryWriter.cpp DataReader/BinaryReader/BinaryReader.cpp DataReader/BinaryReader/BinaryFile.cpp
 HTKMLFREADER_SRC = DataReader/HTKMLFReader_linux/HTKMLFWriter.cpp DataReader/HTKMLFReader_linux/DataWriter.cpp DataReader/HTKMLFReader_linux/DataReader.cpp DataReader/HTKMLFReader_linux/HTKMLFReader.cpp
diff --git a/Makefile.gpu b/Makefile.gpu
index 028eaf039..d7985a3f2 100644
--- a/Makefile.gpu
+++ b/Makefile.gpu
@@ -77,7 +77,7 @@ COMMON_SRC = Common/fileutil.cpp Common/DataWriter.cpp Common/ConfigFile.cpp Com
 MATH_SRC = Math/Math/Matrix.cpp Math/Math/GPUMatrix.cu Math/Math/GPUMatrixCUDAKernels.cu Math/Math/GPUSparseMatrix.cu Math/Math/GPUWatcher.cu \
 		   Math/Math/CPUMatrix.cpp Math/Math/CPUSparseMatrix.cpp #Math/Math/InstantiateTemplates.cu
 CN_SRC =  MachineLearning/CNTK/NetworkDescriptionLanguage.cpp MachineLearning/CNTK/CNTK.cpp MachineLearning/CNTK/ComputationNode.cpp \
-          MachineLearning/CNTK/ModelEditLanguage.cpp MachineLearning/CNTK/PTaskGraphBuilder.cpp \
+          MachineLearning/CNTK/ModelEditLanguage.cpp \
           MachineLearning/CNTK/SimpleNetworkBuilder.cpp MachineLearning/CNTK/tests.cpp MachineLearning/CNTKEval/CNTKEval.cpp
 BINARYREADER_SRC = #DataReader/BinaryReader/BinaryWriter.cpp DataReader/BinaryReader/BinaryReader.cpp DataReader/BinaryReader/BinaryFile.cpp
 HTKMLFREADER_SRC = DataReader/HTKMLFReader_linux/HTKMLFWriter.cpp DataReader/HTKMLFReader_linux/DataWriter.cpp DataReader/HTKMLFReader_linux/DataReader.cpp DataReader/HTKMLFReader_linux/HTKMLFReader.cpp
diff --git a/Makefile_kaldi.cpu b/Makefile_kaldi.cpu
index 145dbbd48..d8eac11bf 100644
--- a/Makefile_kaldi.cpu
+++ b/Makefile_kaldi.cpu
@@ -73,7 +73,7 @@ COMMON_SRC = Common/fileutil.cpp Common/DataWriter.cpp Common/ConfigFile.cpp Com
 
 MATH_SRC = Math/Math/Matrix.cpp Math/Math/CPUMatrix.cpp Math/Math/CPUSparseMatrix.cpp Math/Math/NoGPU.cpp
 CN_SRC =  MachineLearning/CNTK/NetworkDescriptionLanguage.cpp MachineLearning/CNTK/CNTK.cpp MachineLearning/CNTK/ComputationNode.cpp \
-          MachineLearning/CNTK/ModelEditLanguage.cpp MachineLearning/CNTK/PTaskGraphBuilder.cpp \
+          MachineLearning/CNTK/ModelEditLanguage.cpp \
           MachineLearning/CNTK/SimpleNetworkBuilder.cpp MachineLearning/CNTK/tests.cpp MachineLearning/CNTKEval/CNTKEval.cpp
 BINARYREADER_SRC = DataReader/BinaryReader/BinaryWriter.cpp DataReader/BinaryReader/BinaryReader.cpp DataReader/BinaryReader/BinaryFile.cpp
 HTKMLFREADER_SRC = DataReader/HTKMLFReader_linux/HTKMLFWriter.cpp DataReader/HTKMLFReader_linux/DataWriter.cpp DataReader/HTKMLFReader_linux/DataReader.cpp DataReader/HTKMLFReader_linux/HTKMLFReader.cpp
diff --git a/Makefile_kaldi.gpu b/Makefile_kaldi.gpu
index 7b4fe76ef..d56b86e8e 100644
--- a/Makefile_kaldi.gpu
+++ b/Makefile_kaldi.gpu
@@ -80,7 +80,7 @@ COMMON_SRC = Common/fileutil.cpp Common/DataWriter.cpp Common/ConfigFile.cpp Com
 MATH_SRC = Math/Math/Matrix.cpp Math/Math/GPUMatrix.cu Math/Math/GPUMatrixCUDAKernels.cu Math/Math/GPUSparseMatrix.cu Math/Math/GPUWatcher.cu \
 		   Math/Math/CPUMatrix.cpp Math/Math/CPUSparseMatrix.cpp #Math/Math/InstantiateTemplates.cu
 CN_SRC =  MachineLearning/CNTK/NetworkDescriptionLanguage.cpp MachineLearning/CNTK/CNTK.cpp MachineLearning/CNTK/ComputationNode.cpp \
-          MachineLearning/CNTK/ModelEditLanguage.cpp MachineLearning/CNTK/PTaskGraphBuilder.cpp \
+          MachineLearning/CNTK/ModelEditLanguage.cpp \
           MachineLearning/CNTK/SimpleNetworkBuilder.cpp MachineLearning/CNTK/tests.cpp MachineLearning/CNTKEval/CNTKEval.cpp
 BINARYREADER_SRC = #DataReader/BinaryReader/BinaryWriter.cpp DataReader/BinaryReader/BinaryReader.cpp DataReader/BinaryReader/BinaryFile.cpp
 HTKMLFREADER_SRC = DataReader/HTKMLFReader_linux/HTKMLFWriter.cpp DataReader/HTKMLFReader_linux/DataWriter.cpp DataReader/HTKMLFReader_linux/DataReader.cpp DataReader/HTKMLFReader_linux/HTKMLFReader.cpp
diff --git a/Math/CNTKMathTest/MatrixFileWriteAndRead.cpp b/Math/CNTKMathTest/MatrixFileWriteAndRead.cpp
index adfd1bf34..19e57c3be 100644
--- a/Math/CNTKMathTest/MatrixFileWriteAndRead.cpp
+++ b/Math/CNTKMathTest/MatrixFileWriteAndRead.cpp
@@ -7,10 +7,10 @@
 #include <string>
 #include "CppUnitTest.h"
 #include "..\Math\Matrix.h"
-#include "..\..\common\include\basetypes.h"
+#include "..\..\common\include\Basics.h"
 #include "..\..\common\include\fileutil.h"
-#include "..\..\common\include\file.h"
-#include "..\..\common\file.cpp"
+#include "..\..\common\include\File.h"
+#include "..\..\common\File.cpp"
 #include "..\..\common\fileutil.cpp"
 
 
diff --git a/Math/Math/CNTKMathCUDA.vcxproj b/Math/Math/CNTKMathCUDA.vcxproj
index feb45bd70..2c4c0666b 100644
--- a/Math/Math/CNTKMathCUDA.vcxproj
+++ b/Math/Math/CNTKMathCUDA.vcxproj
@@ -86,10 +86,10 @@
       <Profile>true</Profile>
     </Link>
     <PostBuildEvent>
-      <Command>xcopy /D /I /Y "$(CUDA_PATH)\bin\cudart64_70.dll" $(OutputPath)</Command>
+      <Command>xcopy /D /I /Y "$(CUDA_PATH)\bin\cudart64_*.dll" $(OutputPath)</Command>
     </PostBuildEvent>
     <PostBuildEvent>
-      <Message>Copying cudart64_65.dll</Message>
+      <Message>Copying cudart64 DLL</Message>
     </PostBuildEvent>
     <CudaCompile>
       <TargetMachinePlatform>64</TargetMachinePlatform>
@@ -133,8 +133,8 @@
       <DelayLoadDLLs>cublas64_65.dll;cusparse64_65.dll;curand64_65.dll;cudart64_65.dll;%(DelayLoadDLLs)</DelayLoadDLLs>
     </Link>
     <PostBuildEvent>
-      <Command>xcopy /D /I /Y "$(CUDA_PATH)\bin\cudart64_70.dll" $(OutputPath)</Command>
-      <Message>Copying cudart64_65.dll</Message>
+      <Command>xcopy /D /I /Y "$(CUDA_PATH)\bin\cudart64_*.dll" $(OutputPath)</Command>
+      <Message>Copying cudart64 DLL</Message>
     </PostBuildEvent>
     <CudaCompile>
       <FastMath>true</FastMath>
diff --git a/Math/Math/GPUMatrix.cu b/Math/Math/GPUMatrix.cu
index 49aa96154..77f4940c8 100644
--- a/Math/Math/GPUMatrix.cu
+++ b/Math/Math/GPUMatrix.cu
@@ -1741,8 +1741,8 @@ namespace Microsoft { namespace MSR { namespace CNTK {
             Resize(a.GetNumRows(), a.GetNumCols());
 
         PrepareDevice();
-        LONG64 N=(LONG64)GetNumElements();
-        int blocksPerGrid =(int)ceil(1.0*N/threadsPerBlock);                
+        //LONG64 N=(LONG64)GetNumElements();
+        //int blocksPerGrid =(int)ceil(1.0*N/threadsPerBlock);                
         cudaEvent_t done = nullptr;
         if (do_sync)    CUDA_CALL(cudaEventCreate(&done));        
 
@@ -1760,7 +1760,7 @@ namespace Microsoft { namespace MSR { namespace CNTK {
         UNCONST(ElemType, a, my_a);
         UNCONST(ElemType, b, my_b);
 
-        cudaEvent_t done;
+        cudaEvent_t done = nullptr;
         if (do_sync) CUDA_CALL(cudaEventCreate(&done));
 
         int p = 512;
@@ -1806,7 +1806,7 @@ namespace Microsoft { namespace MSR { namespace CNTK {
     {
         UNCONST(ElemType, a, my_a);
         UNCONST(ElemType, b, my_b);
-        cudaEvent_t done;
+        cudaEvent_t done = nullptr;
         if (do_sync) CUDA_CALL(cudaEventCreate(&done));
         int p = 512;
         int width = a.GetNumCols();
@@ -1837,6 +1837,7 @@ namespace Microsoft { namespace MSR { namespace CNTK {
         assert(GetNumRows() == a.GetNumRows());
         assert(GetNumCols() == b.GetNumRows());
         assert(a.GetNumCols() == b.GetNumRows());
+        c;  // TODO: this function seems like a stub
         /*
         EnsureAuxMemory();
         int p = 512;
diff --git a/Math/Math/GPUMatrixCUDAKernels.cu b/Math/Math/GPUMatrixCUDAKernels.cu
index 4b28b1e53..9cbe57c10 100644
--- a/Math/Math/GPUMatrixCUDAKernels.cu
+++ b/Math/Math/GPUMatrixCUDAKernels.cu
@@ -3245,7 +3245,7 @@ __global__ void _assignNceDerivative(
         int rowIndex = i / sampleCount;
 
         ElemType er = tmp[i]; // precalculated error for this output node
-        ElemType log_pnw = val[2 * i + 1];
+        //ElemType log_pnw = val[2 * i + 1];
 
         // calculate gradients
         int loadPerThread = (width + blockDim.x - 1) / blockDim.x;
diff --git a/Math/Math/Math.vcxproj b/Math/Math/Math.vcxproj
index 660bb2cd4..33b3c951b 100644
--- a/Math/Math/Math.vcxproj
+++ b/Math/Math/Math.vcxproj
@@ -51,7 +51,7 @@
   </ImportGroup>
   <PropertyGroup Label="UserMacros" />
   <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'">
-    <LinkIncremental>true</LinkIncremental>
+    <LinkIncremental>false</LinkIncremental>
     <IncludePath>..\..\common\include;$(ACML_PATH)\include;$(CUDA_PATH)\include;$(IncludePath)</IncludePath>
     <LibraryPath>$(SolutionDir)$(Platform)\$(Configuration);$(ACML_PATH)\lib;$(CUDA_PATH)\lib\$(Platform);$(LibraryPath)</LibraryPath>
     <IntDir>$(Platform)\$(Configuration)\$(ProjectName)\</IntDir>
@@ -81,7 +81,7 @@
       <GenerateDebugInformation>true</GenerateDebugInformation>
       <AdditionalDependencies>libacml_mp_dll.lib;%(AdditionalDependencies)</AdditionalDependencies>
       <AdditionalLibraryDirectories>$(SolutionDir)$(Platform)\$(Configuration)\</AdditionalLibraryDirectories>
-      <DelayLoadDLLs>cublas64_70.dll;cusparse64_70.dll;curand64_70.dll;cudart64_70.dll;libacml_dll.dll;libacml_mp_dll.dll;nvcuda.dll;%(DelayLoadDLLs)</DelayLoadDLLs>
+      <DelayLoadDLLs>cublas64_70.dll; cusparse64_70.dll; curand64_70.dll; cudart64_70.dll; libacml_dll.dll; libacml_mp_dll.dll; %(DelayLoadDLLs)</DelayLoadDLLs>
       <Profile>true</Profile>
     </Link>
     <PostBuildEvent>
@@ -132,7 +132,7 @@
       <AdditionalLibraryDirectories>$(SolutionDir)$(Platform)\$(Configuration)\</AdditionalLibraryDirectories>
       <AdditionalDependencies>libacml_mp_dll.lib;%(AdditionalDependencies)</AdditionalDependencies>
       <Profile>true</Profile>
-      <DelayLoadDLLs>cublas64_70.dll;cusparse64_70.dll;curand64_70.dll;cudart64_70.dll;libacml_dll.dll;libacml_mp_dll.dll;nvcuda.dll;%(DelayLoadDLLs)</DelayLoadDLLs>
+      <DelayLoadDLLs>cublas64_70.dll; cusparse64_70.dll; curand64_70.dll; cudart64_70.dll; libacml_dll.dll; libacml_mp_dll.dll; %(DelayLoadDLLs)</DelayLoadDLLs>
     </Link>
     <PostBuildEvent>
       <Command>xcopy /D /I /Y "$(ACML_PATH)\lib\*.dll" $(OutputPath)</Command>

From 544595242243e2cfacf9cfdb7e2bdd007b49b198 Mon Sep 17 00:00:00 2001
From: Frank Seide <fseide@microsoft.com>
Date: Mon, 18 May 2015 20:37:41 -0700
Subject: [PATCH 30/49] (removed a defunct reference from the UCIFastReader VS
 Project)

---
 .../UCIFastReader/UCIFastReader.vcxproj       |   1 -
 .../UCIFastReader.vcxproj.filters             | 112 +++++++++---------
 2 files changed, 53 insertions(+), 60 deletions(-)

diff --git a/DataReader/UCIFastReader/UCIFastReader.vcxproj b/DataReader/UCIFastReader/UCIFastReader.vcxproj
index 7588216b2..bc9c45608 100644
--- a/DataReader/UCIFastReader/UCIFastReader.vcxproj
+++ b/DataReader/UCIFastReader/UCIFastReader.vcxproj
@@ -106,7 +106,6 @@
     <ClInclude Include="..\..\Common\Include\DataWriter.h" />
     <ClInclude Include="..\..\Common\Include\File.h" />
     <ClInclude Include="..\..\Common\Include\fileutil.h" />
-    <ClInclude Include="minibatchsourcehelpers.h" />
     <ClInclude Include="stdafx.h" />
     <ClInclude Include="targetver.h" />
     <ClInclude Include="UCIFastReader.h" />
diff --git a/DataReader/UCIFastReader/UCIFastReader.vcxproj.filters b/DataReader/UCIFastReader/UCIFastReader.vcxproj.filters
index 985aba8c1..d4f9aa547 100644
--- a/DataReader/UCIFastReader/UCIFastReader.vcxproj.filters
+++ b/DataReader/UCIFastReader/UCIFastReader.vcxproj.filters
@@ -1,60 +1,54 @@
-<?xml version="1.0" encoding="utf-8"?>
-<Project ToolsVersion="4.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
-  <ItemGroup>
-    <ClCompile Include="Exports.cpp" />
-    <ClCompile Include="dllmain.cpp" />
-    <ClCompile Include="stdafx.cpp" />
-    <ClCompile Include="UCIFastReader.cpp" />
-    <ClCompile Include="UCIParser.cpp" />
-    <ClCompile Include="..\..\Common\ConfigFile.cpp">
-      <Filter>Common</Filter>
-    </ClCompile>
-    <ClCompile Include="..\..\Common\DataReader.cpp">
-      <Filter>Common</Filter>
-    </ClCompile>
-    <ClCompile Include="..\..\Common\DataWriter.cpp">
-      <Filter>Common</Filter>
-    </ClCompile>
-    <ClCompile Include="..\..\Common\File.cpp">
-      <Filter>Common</Filter>
-    </ClCompile>
-    <ClCompile Include="..\..\Common\fileutil.cpp">
-      <Filter>Common</Filter>
-    </ClCompile>
-  </ItemGroup>
-  <ItemGroup>
-    <ClInclude Include="stdafx.h" />
-    <ClInclude Include="targetver.h" />
-    <ClInclude Include="UCIFastReader.h" />
-    <ClInclude Include="UCIParser.h" />
-    <ClInclude Include="minibatchsourcehelpers.h">
-      <Filter>Duplicates to remove</Filter>
-    </ClInclude>
-    <ClInclude Include="..\..\Common\Include\basetypes.h">
-      <Filter>Common\Include</Filter>
-    </ClInclude>
-    <ClInclude Include="..\..\Common\Include\DataReader.h">
-      <Filter>Common\Include</Filter>
-    </ClInclude>
-    <ClInclude Include="..\..\Common\Include\DataWriter.h">
-      <Filter>Common\Include</Filter>
-    </ClInclude>
-    <ClInclude Include="..\..\Common\Include\File.h">
-      <Filter>Common\Include</Filter>
-    </ClInclude>
-    <ClInclude Include="..\..\Common\Include\fileutil.h">
-      <Filter>Common\Include</Filter>
-    </ClInclude>
-  </ItemGroup>
-  <ItemGroup>
-    <Filter Include="Common">
-      <UniqueIdentifier>{8e18fb2e-ab57-4862-ad16-5e322d6f2fbc}</UniqueIdentifier>
-    </Filter>
-    <Filter Include="Common\Include">
-      <UniqueIdentifier>{0dbad9d8-ce99-4f36-b871-3b98a27f58c2}</UniqueIdentifier>
-    </Filter>
-    <Filter Include="Duplicates to remove">
-      <UniqueIdentifier>{1032308c-b577-4b1e-9f49-9570b93800ec}</UniqueIdentifier>
-    </Filter>
-  </ItemGroup>
+<?xml version="1.0" encoding="utf-8"?>
+<Project ToolsVersion="4.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
+  <ItemGroup>
+    <ClCompile Include="Exports.cpp" />
+    <ClCompile Include="dllmain.cpp" />
+    <ClCompile Include="stdafx.cpp" />
+    <ClCompile Include="UCIFastReader.cpp" />
+    <ClCompile Include="UCIParser.cpp" />
+    <ClCompile Include="..\..\Common\ConfigFile.cpp">
+      <Filter>Common</Filter>
+    </ClCompile>
+    <ClCompile Include="..\..\Common\DataReader.cpp">
+      <Filter>Common</Filter>
+    </ClCompile>
+    <ClCompile Include="..\..\Common\DataWriter.cpp">
+      <Filter>Common</Filter>
+    </ClCompile>
+    <ClCompile Include="..\..\Common\File.cpp">
+      <Filter>Common</Filter>
+    </ClCompile>
+    <ClCompile Include="..\..\Common\fileutil.cpp">
+      <Filter>Common</Filter>
+    </ClCompile>
+  </ItemGroup>
+  <ItemGroup>
+    <ClInclude Include="stdafx.h" />
+    <ClInclude Include="targetver.h" />
+    <ClInclude Include="UCIFastReader.h" />
+    <ClInclude Include="UCIParser.h" />
+    <ClInclude Include="..\..\Common\Include\basetypes.h">
+      <Filter>Common\Include</Filter>
+    </ClInclude>
+    <ClInclude Include="..\..\Common\Include\DataReader.h">
+      <Filter>Common\Include</Filter>
+    </ClInclude>
+    <ClInclude Include="..\..\Common\Include\DataWriter.h">
+      <Filter>Common\Include</Filter>
+    </ClInclude>
+    <ClInclude Include="..\..\Common\Include\File.h">
+      <Filter>Common\Include</Filter>
+    </ClInclude>
+    <ClInclude Include="..\..\Common\Include\fileutil.h">
+      <Filter>Common\Include</Filter>
+    </ClInclude>
+  </ItemGroup>
+  <ItemGroup>
+    <Filter Include="Common">
+      <UniqueIdentifier>{8e18fb2e-ab57-4862-ad16-5e322d6f2fbc}</UniqueIdentifier>
+    </Filter>
+    <Filter Include="Common\Include">
+      <UniqueIdentifier>{0dbad9d8-ce99-4f36-b871-3b98a27f58c2}</UniqueIdentifier>
+    </Filter>
+  </ItemGroup>
 </Project>
\ No newline at end of file

From df921f68356b21dadbfe81a622f0e66dad72e615 Mon Sep 17 00:00:00 2001
From: Frank Seide <fseide@microsoft.com>
Date: Mon, 18 May 2015 21:07:51 -0700
Subject: [PATCH 31/49] fixed a strange commenting-out of the
 _assignSigmoidDerivative() kernel launch

---
 Math/Math/GPUMatrix.cu | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/Math/Math/GPUMatrix.cu b/Math/Math/GPUMatrix.cu
index 77f4940c8..7a318ede2 100644
--- a/Math/Math/GPUMatrix.cu
+++ b/Math/Math/GPUMatrix.cu
@@ -1741,12 +1741,12 @@ namespace Microsoft { namespace MSR { namespace CNTK {
             Resize(a.GetNumRows(), a.GetNumCols());
 
         PrepareDevice();
-        //LONG64 N=(LONG64)GetNumElements();
-        //int blocksPerGrid =(int)ceil(1.0*N/threadsPerBlock);                
+        LONG64 N=(LONG64)GetNumElements();
+        int blocksPerGrid =(int)ceil(1.0*N/threadsPerBlock);                
         cudaEvent_t done = nullptr;
         if (do_sync)    CUDA_CALL(cudaEventCreate(&done));        
 
-        //_assignSigmoidDerivative<ElemType><<<blocksPerGrid,threadsPerBlock,0,t_stream>>>(a.m_pArray, m_pArray, N);
+        _assignSigmoidDerivative<ElemType><<<blocksPerGrid,threadsPerBlock,0,t_stream>>>(a.m_pArray, m_pArray, N);
         if (do_sync)    CUDA_CALL(cudaEventRecord(done));        
         if (do_sync)    CUDA_CALL(cudaEventSynchronize(done)); 
         if (do_sync)    CUDA_CALL(cudaEventDestroy(done));

From fb315ffea46e6c2233232bdb82b1fc323d72c739 Mon Sep 17 00:00:00 2001
From: Frank Seide <fseide@microsoft.com>
Date: Mon, 18 May 2015 21:52:20 -0700
Subject: [PATCH 32/49] removed a 'trash' folder that got accidentally checked
 in

---
 Common/trash/nvml.h | 3253 -------------------------------------------
 1 file changed, 3253 deletions(-)
 delete mode 100644 Common/trash/nvml.h

diff --git a/Common/trash/nvml.h b/Common/trash/nvml.h
deleted file mode 100644
index 8e5161c40..000000000
--- a/Common/trash/nvml.h
+++ /dev/null
@@ -1,3253 +0,0 @@
-/*
- * Copyright 1993-2014 NVIDIA Corporation.  All rights reserved.
- *
- * NOTICE TO USER:   
- *
- * This source code is subject to NVIDIA ownership rights under U.S. and 
- * international Copyright laws.  Users and possessors of this source code 
- * are hereby granted a nonexclusive, royalty-free license to use this code 
- * in individual and commercial software.
- *
- * NVIDIA MAKES NO REPRESENTATION ABOUT THE SUITABILITY OF THIS SOURCE 
- * CODE FOR ANY PURPOSE.  IT IS PROVIDED "AS IS" WITHOUT EXPRESS OR 
- * IMPLIED WARRANTY OF ANY KIND.  NVIDIA DISCLAIMS ALL WARRANTIES WITH 
- * REGARD TO THIS SOURCE CODE, INCLUDING ALL IMPLIED WARRANTIES OF 
- * MERCHANTABILITY, NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
- * IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY SPECIAL, INDIRECT, INCIDENTAL, 
- * OR CONSEQUENTIAL DAMAGES, OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS 
- * OF USE, DATA OR PROFITS,  WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE 
- * OR OTHER TORTIOUS ACTION,  ARISING OUT OF OR IN CONNECTION WITH THE USE 
- * OR PERFORMANCE OF THIS SOURCE CODE.  
- *
- * U.S. Government End Users.   This source code is a "commercial item" as 
- * that term is defined at  48 C.F.R. 2.101 (OCT 1995), consisting  of 
- * "commercial computer  software"  and "commercial computer software 
- * documentation" as such terms are  used in 48 C.F.R. 12.212 (SEPT 1995) 
- * and is provided to the U.S. Government only as a commercial end item.  
- * Consistent with 48 C.F.R.12.212 and 48 C.F.R. 227.7202-1 through 
- * 227.7202-4 (JUNE 1995), all U.S. Government End Users acquire the 
- * source code with only those rights set forth herein. 
- *
- * Any use of this source code in individual and commercial software must 
- * include, in the user documentation and internal comments to the code,
- * the above Disclaimer and U.S. Government End Users Notice.
- */
-
-/* 
-NVML API Reference
-
-The NVIDIA Management Library (NVML) is a C-based programmatic interface for monitoring and 
-managing various states within NVIDIA Tesla &tm; GPUs. It is intended to be a platform for building
-3rd party applications, and is also the underlying library for the NVIDIA-supported nvidia-smi
-tool. NVML is thread-safe so it is safe to make simultaneous NVML calls from multiple threads.
-
-API Documentation
-
-Supported OS platforms:
-- Windows: Windows Server 2008 R2 64bit, Windows 7 64bit
-- Linux: 32-bit and 64-bit
-
-Supported products:
-- Full Support
-    - NVIDIA Tesla &tm; Line:
-            S2050, C2050, C2070, C2075,
-            M2050, M2070, M2075, M2090,
-            X2070, X2090,
-            K10, K20, K20X, K20Xm, K20c, K20m, K20s, K40c, K40m, K40t, K40s, K40st
-    - NVIDIA Quadro &reg; Line:
-            410, 600, 2000, 4000, 5000, 6000, 7000, M2070-Q
-            K2000, K2000D, K4000, K5000, K6000
-    - NVIDIA GRID &tm; Line:
-            K1, K2, K340, K520
-    - NVIDIA GeForce &reg; Line: None
-- Limited Support
-    - NVIDIA Tesla &tm; Line:    S1070, C1060, M1060 and all other previous generation Tesla-branded parts
-    - NVIDIA Quadro &reg; Line:  All other current and previous generation Quadro-branded parts
-    - NVIDIA GRID &tm; Line:     All other current and previous generation GRID-branded parts
-    - NVIDIA GeForce &reg; Line: All current and previous generation GeForce-branded parts
-
-The NVML library can be found at \%ProgramW6432\%\\"NVIDIA Corporation"\\NVSMI\\ on Windows, but
-will not be added to the path. To dynamically link to NVML, add this path to the PATH environmental
-variable. To dynamically load NVML, call LoadLibrary with this path.
-
-On Linux the NVML library will be found on the standard library path. For 64 bit Linux, both the 32 bit
-and 64 bit NVML libraries will be installed.
-*/
-
-#ifndef __nvml_nvml_h__
-#define __nvml_nvml_h__
-
-#ifdef __cplusplus
-extern "C" {
-#endif
-
-/*
- * On Windows, set up methods for DLL export
- * define NVML_STATIC_IMPORT when using nvml_loader library
- */
-#if defined _WINDOWS
-    #if !defined NVML_STATIC_IMPORT
-        #if defined NVML_LIB_EXPORT
-            #define DECLDIR __declspec(dllexport)
-        #else
-            #define DECLDIR __declspec(dllimport)
-        #endif
-    #else
-        #define DECLDIR
-    #endif
-#else
-    #define DECLDIR
-#endif
-
-/**
- * NVML API versioning support
- */
-#define NVML_API_VERSION            6
-#define NVML_API_VERSION_STR        "6"
-#define nvmlInit                    nvmlInit_v2
-#define nvmlDeviceGetPciInfo        nvmlDeviceGetPciInfo_v2
-#define nvmlDeviceGetCount          nvmlDeviceGetCount_v2
-#define nvmlDeviceGetHandleByIndex  nvmlDeviceGetHandleByIndex_v2
-#define nvmlDeviceGetHandleByPciBusId nvmlDeviceGetHandleByPciBusId_v2
-
-/***************************************************************************************************/
-/** @defgroup nvmlDeviceStructs Device Structs
- *  @{
- */
-/***************************************************************************************************/
-
-/**
- * Special constant that some fields take when they are not available.
- * Used when only part of the struct is not available.
- *
- * Each structure explicitly states when to check for this value.
- */
-#define NVML_VALUE_NOT_AVAILABLE (-1)
-
-typedef struct nvmlDevice_st* nvmlDevice_t;
-
-/**
- * Buffer size guaranteed to be large enough for pci bus id
- */
-#define NVML_DEVICE_PCI_BUS_ID_BUFFER_SIZE   16
-
-/**
- * PCI information about a GPU device.
- */
-typedef struct nvmlPciInfo_st 
-{
-    char busId[NVML_DEVICE_PCI_BUS_ID_BUFFER_SIZE]; //!< The tuple domain:bus:device.function PCI identifier (&amp; NULL terminator)
-    unsigned int domain;             //!< The PCI domain on which the device's bus resides, 0 to 0xffff
-    unsigned int bus;                //!< The bus on which the device resides, 0 to 0xff
-    unsigned int device;             //!< The device's id on the bus, 0 to 31
-    unsigned int pciDeviceId;        //!< The combined 16-bit device id and 16-bit vendor id
-    
-    // Added in NVML 2.285 API
-    unsigned int pciSubSystemId;     //!< The 32-bit Sub System Device ID
-    
-    // NVIDIA reserved for internal use only
-    unsigned int reserved0;
-    unsigned int reserved1;
-    unsigned int reserved2;
-    unsigned int reserved3;
-} nvmlPciInfo_t;
-
-/**
- * Detailed ECC error counts for a device.
- *
- * @deprecated  Different GPU families can have different memory error counters
- *              See \ref nvmlDeviceGetMemoryErrorCounter
- */
-typedef struct nvmlEccErrorCounts_st 
-{
-    unsigned long long l1Cache;      //!< L1 cache errors
-    unsigned long long l2Cache;      //!< L2 cache errors
-    unsigned long long deviceMemory; //!< Device memory errors
-    unsigned long long registerFile; //!< Register file errors
-} nvmlEccErrorCounts_t;
-
-/** 
- * Utilization information for a device.
- * Each sample period may be between 1 second and 1/6 second, depending on the product being queried.
- */
-typedef struct nvmlUtilization_st 
-{
-    unsigned int gpu;                //!< Percent of time over the past sample period during which one or more kernels was executing on the GPU
-    unsigned int memory;             //!< Percent of time over the past sample period during which global (device) memory was being read or written
-} nvmlUtilization_t;
-
-/** 
- * Memory allocation information for a device.
- */
-typedef struct nvmlMemory_st 
-{
-    unsigned long long total;        //!< Total installed FB memory (in bytes)
-    unsigned long long free;         //!< Unallocated FB memory (in bytes)
-    unsigned long long used;         //!< Allocated FB memory (in bytes). Note that the driver/GPU always sets aside a small amount of memory for bookkeeping
-} nvmlMemory_t;
-
-/**
- * BAR1 Memory allocation Information for a device
- */
-typedef struct nvmlBAR1Memory_st
-{
-    unsigned long long bar1Total;    //!< Total BAR1 Memory (in bytes)
-    unsigned long long bar1Free;     //!< Unallocated BAR1 Memory (in bytes)
-    unsigned long long bar1Used;     //!< Allocated Used Memory (in bytes)
-}nvmlBAR1Memory_t;
-
-/**
- * Information about running compute processes on the GPU
- */
-typedef struct nvmlProcessInfo_st
-{
-    unsigned int pid;                 //!< Process ID
-    unsigned long long usedGpuMemory; //!< Amount of used GPU memory in bytes.
-                                      //! Under WDDM, \ref NVML_VALUE_NOT_AVAILABLE is always reported
-                                      //! because Windows KMD manages all the memory and not the NVIDIA driver
-} nvmlProcessInfo_t;
-
-
-/**
- * Enum to represent type of bridge chip
- */
-typedef enum nvmlBridgeChipType_enum
-{
-    NVML_BRIDGE_CHIP_PLX = 0,
-    NVML_BRIDGE_CHIP_BRO4 = 1           
-}nvmlBridgeChipType_t;
-
-/**
- * Maximum limit on Physical Bridges per Board
- */
-#define NVML_MAX_PHYSICAL_BRIDGE                         (128)
-
-/**
- * Information about the Bridge Chip Firmware
- */
-typedef struct nvmlBridgeChipInfo_st
-{
-    nvmlBridgeChipType_t type;                  //!< Type of Bridge Chip 
-    unsigned int fwVersion;                     //!< Firmware Version
-}nvmlBridgeChipInfo_t;
-
-/**
- * This structure stores the complete Hierarchy of the Bridge Chip within the board. The immediate 
- * bridge is stored at index 0 of bridgeInfoList, parent to immediate bridge is at index 1 and so forth.
- */
-typedef struct nvmlBridgeChipHierarchy_st
-{
-    unsigned char  bridgeCount;                 //!< Number of Bridge Chips on the Board
-    nvmlBridgeChipInfo_t bridgeChipInfo[NVML_MAX_PHYSICAL_BRIDGE]; //!< Hierarchy of Bridge Chips on the board
-}nvmlBridgeChipHierarchy_t;
-
-
-/** @} */
-
-/***************************************************************************************************/
-/** @defgroup nvmlDeviceEnumvs Device Enums
- *  @{
- */
-/***************************************************************************************************/
-
-/** 
- * Generic enable/disable enum. 
- */
-typedef enum nvmlEnableState_enum 
-{
-    NVML_FEATURE_DISABLED    = 0,     //!< Feature disabled 
-    NVML_FEATURE_ENABLED     = 1      //!< Feature enabled
-} nvmlEnableState_t;
-
-//! Generic flag used to specify the default behavior of some functions. See description of particular functions for details.
-#define nvmlFlagDefault     0x00      
-//! Generic flag used to force some behavior. See description of particular functions for details.
-#define nvmlFlagForce       0x01      
-
-/** 
- * Temperature sensors. 
- */
-typedef enum nvmlTemperatureSensors_enum 
-{
-    NVML_TEMPERATURE_GPU      = 0,    //!< Temperature sensor for the GPU die
-    
-    // Keep this last
-    NVML_TEMPERATURE_COUNT
-} nvmlTemperatureSensors_t;
-
-/** 
- * Compute mode. 
- *
- * NVML_COMPUTEMODE_EXCLUSIVE_PROCESS was added in CUDA 4.0.
- * Earlier CUDA versions supported a single exclusive mode, 
- * which is equivalent to NVML_COMPUTEMODE_EXCLUSIVE_THREAD in CUDA 4.0 and beyond.
- */
-typedef enum nvmlComputeMode_enum 
-{
-    NVML_COMPUTEMODE_DEFAULT           = 0,  //!< Default compute mode -- multiple contexts per device
-    NVML_COMPUTEMODE_EXCLUSIVE_THREAD  = 1,  //!< Compute-exclusive-thread mode -- only one context per device, usable from one thread at a time
-    NVML_COMPUTEMODE_PROHIBITED        = 2,  //!< Compute-prohibited mode -- no contexts per device
-    NVML_COMPUTEMODE_EXCLUSIVE_PROCESS = 3,  //!< Compute-exclusive-process mode -- only one context per device, usable from multiple threads at a time
-    
-    // Keep this last
-    NVML_COMPUTEMODE_COUNT
-} nvmlComputeMode_t;
-
-/** 
- * ECC bit types.
- *
- * @deprecated See \ref nvmlMemoryErrorType_t for a more flexible type
- */
-#define nvmlEccBitType_t nvmlMemoryErrorType_t
-
-/**
- * Single bit ECC errors
- *
- * @deprecated Mapped to \ref NVML_MEMORY_ERROR_TYPE_CORRECTED
- */
-#define NVML_SINGLE_BIT_ECC NVML_MEMORY_ERROR_TYPE_CORRECTED
-
-/**
- * Double bit ECC errors
- *
- * @deprecated Mapped to \ref NVML_MEMORY_ERROR_TYPE_UNCORRECTED
- */
-#define NVML_DOUBLE_BIT_ECC NVML_MEMORY_ERROR_TYPE_UNCORRECTED
-
-/**
- * Memory error types
- */
-typedef enum nvmlMemoryErrorType_enum
-{
-    /**
-     * A memory error that was corrected
-     * 
-     * For ECC errors, these are single bit errors
-     * For Texture memory, these are errors fixed by resend
-     */
-    NVML_MEMORY_ERROR_TYPE_CORRECTED = 0,
-    /**
-     * A memory error that was not corrected
-     * 
-     * For ECC errors, these are double bit errors
-     * For Texture memory, these are errors where the resend fails
-     */
-    NVML_MEMORY_ERROR_TYPE_UNCORRECTED = 1,
-    
-    
-    // Keep this last
-    NVML_MEMORY_ERROR_TYPE_COUNT //!< Count of memory error types
-
-} nvmlMemoryErrorType_t;
-
-/** 
- * ECC counter types. 
- *
- * Note: Volatile counts are reset each time the driver loads. On Windows this is once per boot. On Linux this can be more frequent.
- *       On Linux the driver unloads when no active clients exist. If persistence mode is enabled or there is always a driver 
- *       client active (e.g. X11), then Linux also sees per-boot behavior. If not, volatile counts are reset each time a compute app
- *       is run.
- */
-typedef enum nvmlEccCounterType_enum 
-{
-    NVML_VOLATILE_ECC      = 0,      //!< Volatile counts are reset each time the driver loads.
-    NVML_AGGREGATE_ECC     = 1,      //!< Aggregate counts persist across reboots (i.e. for the lifetime of the device)
-    
-    // Keep this last
-    NVML_ECC_COUNTER_TYPE_COUNT      //!< Count of memory counter types
-} nvmlEccCounterType_t;
-
-/** 
- * Clock types. 
- * 
- * All speeds are in Mhz.
- */
-typedef enum nvmlClockType_enum 
-{
-    NVML_CLOCK_GRAPHICS  = 0,        //!< Graphics clock domain
-    NVML_CLOCK_SM        = 1,        //!< SM clock domain
-    NVML_CLOCK_MEM       = 2,        //!< Memory clock domain
-    
-    // Keep this last
-    NVML_CLOCK_COUNT //<! Count of clock types
-} nvmlClockType_t;
-
-/** 
- * Driver models. 
- *
- * Windows only.
- */
-typedef enum nvmlDriverModel_enum 
-{
-    NVML_DRIVER_WDDM      = 0,       //!< WDDM driver model -- GPU treated as a display device
-    NVML_DRIVER_WDM       = 1        //!< WDM (TCC) model (recommended) -- GPU treated as a generic device
-} nvmlDriverModel_t;
-
-/**
- * Allowed PStates.
- */
-typedef enum nvmlPStates_enum 
-{
-    NVML_PSTATE_0               = 0,       //!< Performance state 0 -- Maximum Performance
-    NVML_PSTATE_1               = 1,       //!< Performance state 1 
-    NVML_PSTATE_2               = 2,       //!< Performance state 2
-    NVML_PSTATE_3               = 3,       //!< Performance state 3
-    NVML_PSTATE_4               = 4,       //!< Performance state 4
-    NVML_PSTATE_5               = 5,       //!< Performance state 5
-    NVML_PSTATE_6               = 6,       //!< Performance state 6
-    NVML_PSTATE_7               = 7,       //!< Performance state 7
-    NVML_PSTATE_8               = 8,       //!< Performance state 8
-    NVML_PSTATE_9               = 9,       //!< Performance state 9
-    NVML_PSTATE_10              = 10,      //!< Performance state 10
-    NVML_PSTATE_11              = 11,      //!< Performance state 11
-    NVML_PSTATE_12              = 12,      //!< Performance state 12
-    NVML_PSTATE_13              = 13,      //!< Performance state 13
-    NVML_PSTATE_14              = 14,      //!< Performance state 14
-    NVML_PSTATE_15              = 15,      //!< Performance state 15 -- Minimum Performance 
-    NVML_PSTATE_UNKNOWN         = 32       //!< Unknown performance state
-} nvmlPstates_t;
-
-/**
- * GPU Operation Mode
- *
- * GOM allows to reduce power usage and optimize GPU throughput by disabling GPU features.
- *
- * Each GOM is designed to meet specific user needs.
- */
-typedef enum nvmlGom_enum
-{
-    NVML_GOM_ALL_ON                    = 0, //!< Everything is enabled and running at full speed
-
-    NVML_GOM_COMPUTE                   = 1, //!< Designed for running only compute tasks. Graphics operations
-                                            //!< are not allowed
-
-    NVML_GOM_LOW_DP                    = 2  //!< Designed for running graphics applications that don't require
-                                            //!< high bandwidth double precision
-} nvmlGpuOperationMode_t;
-
-/** 
- * Available infoROM objects.
- */
-typedef enum nvmlInforomObject_enum 
-{
-    NVML_INFOROM_OEM            = 0,       //!< An object defined by OEM
-    NVML_INFOROM_ECC            = 1,       //!< The ECC object determining the level of ECC support
-    NVML_INFOROM_POWER          = 2,       //!< The power management object
-
-    // Keep this last
-    NVML_INFOROM_COUNT                     //!< This counts the number of infoROM objects the driver knows about
-} nvmlInforomObject_t;
-
-/** 
- * Return values for NVML API calls. 
- */
-typedef enum nvmlReturn_enum 
-{
-    NVML_SUCCESS = 0,                   //!< The operation was successful
-    NVML_ERROR_UNINITIALIZED = 1,       //!< NVML was not first initialized with nvmlInit()
-    NVML_ERROR_INVALID_ARGUMENT = 2,    //!< A supplied argument is invalid
-    NVML_ERROR_NOT_SUPPORTED = 3,       //!< The requested operation is not available on target device
-    NVML_ERROR_NO_PERMISSION = 4,       //!< The current user does not have permission for operation
-    NVML_ERROR_ALREADY_INITIALIZED = 5, //!< Deprecated: Multiple initializations are now allowed through ref counting
-    NVML_ERROR_NOT_FOUND = 6,           //!< A query to find an object was unsuccessful
-    NVML_ERROR_INSUFFICIENT_SIZE = 7,   //!< An input argument is not large enough
-    NVML_ERROR_INSUFFICIENT_POWER = 8,  //!< A device's external power cables are not properly attached
-    NVML_ERROR_DRIVER_NOT_LOADED = 9,   //!< NVIDIA driver is not loaded
-    NVML_ERROR_TIMEOUT = 10,            //!< User provided timeout passed
-    NVML_ERROR_IRQ_ISSUE = 11,          //!< NVIDIA Kernel detected an interrupt issue with a GPU
-    NVML_ERROR_LIBRARY_NOT_FOUND = 12,  //!< NVML Shared Library couldn't be found or loaded
-    NVML_ERROR_FUNCTION_NOT_FOUND = 13, //!< Local version of NVML doesn't implement this function
-    NVML_ERROR_CORRUPTED_INFOROM = 14,  //!< infoROM is corrupted
-    NVML_ERROR_GPU_IS_LOST = 15,        //!< The GPU has fallen off the bus or has otherwise become inaccessible
-    NVML_ERROR_UNKNOWN = 999            //!< An internal driver error occurred
-} nvmlReturn_t;
-
-/**
- * Memory locations
- *
- * See \ref nvmlDeviceGetMemoryErrorCounter
- */
-typedef enum nvmlMemoryLocation_enum
-{
-    NVML_MEMORY_LOCATION_L1_CACHE = 0,       //!< GPU L1 Cache
-    NVML_MEMORY_LOCATION_L2_CACHE = 1,       //!< GPU L2 Cache
-    NVML_MEMORY_LOCATION_DEVICE_MEMORY = 2,  //!< GPU Device Memory
-    NVML_MEMORY_LOCATION_REGISTER_FILE = 3,  //!< GPU Register File
-    NVML_MEMORY_LOCATION_TEXTURE_MEMORY = 4, //!< GPU Texture Memory
-    
-    // Keep this last
-    NVML_MEMORY_LOCATION_COUNT              //!< This counts the number of memory locations the driver knows about
-} nvmlMemoryLocation_t;
-
-/**
- * Causes for page retirement
- */
-typedef enum nvmlPageRetirementCause_enum
-{
-    NVML_PAGE_RETIREMENT_CAUSE_MULTIPLE_SINGLE_BIT_ECC_ERRORS = 0, //!< Page was retired due to multiple single bit ECC error
-    NVML_PAGE_RETIREMENT_CAUSE_DOUBLE_BIT_ECC_ERROR = 1,           //!< Page was retired due to double bit ECC error
-
-    // Keep this last
-    NVML_PAGE_RETIREMENT_CAUSE_COUNT
-} nvmlPageRetirementCause_t;
-
-/**
- * API types that allow changes to default permission restrictions
- */
-typedef enum nvmlRestrictedAPI_enum
-{
-    NVML_RESTRICTED_API_SET_APPLICATION_CLOCKS = 0,   //!< APIs that change application clocks, @see nvmlDeviceSetApplicationsClocks 
-                                                      //!< and @see nvmlDeviceResetApplicationsClocks
-
-    // Keep this last
-    NVML_RESTRICTED_API_COUNT
-} nvmlRestrictedAPI_t;
-
-/** @} */
-
-/***************************************************************************************************/
-/** @defgroup nvmlUnitStructs Unit Structs
- *  @{
- */
-/***************************************************************************************************/
-
-typedef struct nvmlUnit_st* nvmlUnit_t;
-
-/** 
- * Description of HWBC entry 
- */
-typedef struct nvmlHwbcEntry_st 
-{
-    unsigned int hwbcId;
-    char firmwareVersion[32];
-} nvmlHwbcEntry_t;
-
-/** 
- * Fan state enum. 
- */
-typedef enum nvmlFanState_enum 
-{
-    NVML_FAN_NORMAL       = 0,     //!< Fan is working properly
-    NVML_FAN_FAILED       = 1      //!< Fan has failed
-} nvmlFanState_t;
-
-/** 
- * Led color enum. 
- */
-typedef enum nvmlLedColor_enum 
-{
-    NVML_LED_COLOR_GREEN       = 0,     //!< GREEN, indicates good health
-    NVML_LED_COLOR_AMBER       = 1      //!< AMBER, indicates problem
-} nvmlLedColor_t;
-
-
-/** 
- * LED states for an S-class unit.
- */
-typedef struct nvmlLedState_st 
-{
-    char cause[256];               //!< If amber, a text description of the cause
-    nvmlLedColor_t color;          //!< GREEN or AMBER
-} nvmlLedState_t;
-
-/** 
- * Static S-class unit info.
- */
-typedef struct nvmlUnitInfo_st 
-{
-    char name[96];                      //!< Product name
-    char id[96];                        //!< Product identifier
-    char serial[96];                    //!< Product serial number
-    char firmwareVersion[96];           //!< Firmware version
-} nvmlUnitInfo_t;
-
-/** 
- * Power usage information for an S-class unit.
- * The power supply state is a human readable string that equals "Normal" or contains
- * a combination of "Abnormal" plus one or more of the following:
- *    
- *    - High voltage
- *    - Fan failure
- *    - Heatsink temperature
- *    - Current limit
- *    - Voltage below UV alarm threshold
- *    - Low-voltage
- *    - SI2C remote off command
- *    - MOD_DISABLE input
- *    - Short pin transition 
-*/
-typedef struct nvmlPSUInfo_st 
-{
-    char state[256];                 //!< The power supply state
-    unsigned int current;            //!< PSU current (A)
-    unsigned int voltage;            //!< PSU voltage (V)
-    unsigned int power;              //!< PSU power draw (W)
-} nvmlPSUInfo_t;
-
-/** 
- * Fan speed reading for a single fan in an S-class unit.
- */
-typedef struct nvmlUnitFanInfo_st 
-{
-    unsigned int speed;              //!< Fan speed (RPM)
-    nvmlFanState_t state;            //!< Flag that indicates whether fan is working properly
-} nvmlUnitFanInfo_t;
-
-/** 
- * Fan speed readings for an entire S-class unit.
- */
-typedef struct nvmlUnitFanSpeeds_st 
-{
-    nvmlUnitFanInfo_t fans[24];      //!< Fan speed data for each fan
-    unsigned int count;              //!< Number of fans in unit
-} nvmlUnitFanSpeeds_t;
-
-/** @} */
-
-/***************************************************************************************************/
-/** @addtogroup nvmlEvents 
- *  @{
- */
-/***************************************************************************************************/
-
-/** 
- * Handle to an event set
- */
-typedef struct nvmlEventSet_st* nvmlEventSet_t;
-
-/** @defgroup nvmlEventType Event Types
- * @{
- * Event Types which user can be notified about.
- * See description of particular functions for details.
- *
- * See \ref nvmlDeviceRegisterEvents and \ref nvmlDeviceGetSupportedEventTypes to check which devices 
- * support each event.
- *
- * Types can be combined with bitwise or operator '|' when passed to \ref nvmlDeviceRegisterEvents
- */
-//! Event about single bit ECC errors
-/**
- * \note A corrected texture memory error is not an ECC error, so it does not generate a single bit event
- */
-#define nvmlEventTypeSingleBitEccError     0x0000000000000001LL
-
-//! Event about double bit ECC errors
-/**
- * \note An uncorrected texture memory error is not an ECC error, so it does not generate a double bit event
- */
-#define nvmlEventTypeDoubleBitEccError     0x0000000000000002LL
-
-//! Event about PState changes
-/**
- *  \note On Fermi architecture PState changes are also an indicator that GPU is throttling down due to
- *  no work being executed on the GPU, power capping or thermal capping. In a typical situation,
- *  Fermi-based GPU should stay in P0 for the duration of the execution of the compute process.
- */
-#define nvmlEventTypePState                0x0000000000000004LL
-
-//! Event that Xid critical error occurred
-#define nvmlEventTypeXidCriticalError      0x0000000000000008LL
-
-//! Event about clock changes
-/**
- * Kepler only
- */
-#define nvmlEventTypeClock                 0x0000000000000010LL
-
-//! Mask with no events
-#define nvmlEventTypeNone                  0x0000000000000000LL
-//! Mask of all events
-#define nvmlEventTypeAll (nvmlEventTypeNone    \
-        | nvmlEventTypeSingleBitEccError       \
-        | nvmlEventTypeDoubleBitEccError       \
-        | nvmlEventTypePState                  \
-        | nvmlEventTypeClock                   \
-        | nvmlEventTypeXidCriticalError        \
-        )
-/** @} */
-
-/** 
- * Information about occurred event
- */
-typedef struct nvmlEventData_st
-{
-    nvmlDevice_t        device;         //!< Specific device where the event occurred
-    unsigned long long  eventType;      //!< Information about what specific event occurred
-    unsigned long long  eventData;      //!< Stores last XID error for the device in the event of nvmlEventTypeXidCriticalError, 
-                                        //  eventData is 0 for any other event. eventData is set as 999 for unknown xid error.
-} nvmlEventData_t;
-
-/** @} */
-
-/***************************************************************************************************/
-/** @addtogroup nvmlClocksThrottleReasons
- *  @{
- */
-/***************************************************************************************************/
-
-/** Nothing is running on the GPU and the clocks are dropping to Idle state
- * \note This limiter may be removed in a later release
- */
-#define nvmlClocksThrottleReasonGpuIdle                   0x0000000000000001LL
-
-/** GPU clocks are limited by current setting of applications clocks
- *
- * @see nvmlDeviceSetApplicationsClocks
- * @see nvmlDeviceGetApplicationsClock
- */
-#define nvmlClocksThrottleReasonApplicationsClocksSetting   0x0000000000000002LL
-
-/** 
- * @deprecated Renamed to \ref nvmlClocksThrottleReasonApplicationsClocksSetting 
- *             as the name describes the situation more accurately.
- */
-#define nvmlClocksThrottleReasonUserDefinedClocks         nvmlClocksThrottleReasonApplicationsClocksSetting 
-
-/** SW Power Scaling algorithm is reducing the clocks below requested clocks 
- *
- * @see nvmlDeviceGetPowerUsage
- * @see nvmlDeviceSetPowerManagementLimit
- * @see nvmlDeviceGetPowerManagementLimit
- */
-#define nvmlClocksThrottleReasonSwPowerCap                0x0000000000000004LL
-
-/** HW Slowdown (reducing the core clocks by a factor of 2 or more) is engaged
- * 
- * This is an indicator of:
- *   - temperature being too high
- *   - External Power Brake Assertion is triggered (e.g. by the system power supply)
- *   - Power draw is too high and Fast Trigger protection is reducing the clocks
- *   - May be also reported during PState or clock change
- *      - This behavior may be removed in a later release.
- *
- * @see nvmlDeviceGetTemperature
- * @see nvmlDeviceGetPowerUsage
- */
-#define nvmlClocksThrottleReasonHwSlowdown                0x0000000000000008LL
-
-/** Some other unspecified factor is reducing the clocks */
-#define nvmlClocksThrottleReasonUnknown                   0x8000000000000000LL
-
-/** Bit mask representing no clocks throttling
- *
- * Clocks are as high as possible.
- * */
-#define nvmlClocksThrottleReasonNone                      0x0000000000000000LL
-
-/** Bit mask representing all supported clocks throttling reasons 
- * New reasons might be added to this list in the future
- */
-#define nvmlClocksThrottleReasonAll (nvmlClocksThrottleReasonNone \
-      | nvmlClocksThrottleReasonGpuIdle                           \
-      | nvmlClocksThrottleReasonApplicationsClocksSetting         \
-      | nvmlClocksThrottleReasonSwPowerCap                        \
-      | nvmlClocksThrottleReasonHwSlowdown                        \
-      | nvmlClocksThrottleReasonUnknown                           \
-        ) 
-/** @} */
-
-/***************************************************************************************************/
-/** @defgroup nvmlAccountingStats Accounting Statistics
- *  @{
- *
- *  Set of APIs designed to provide per process information about usage of GPU.
- *
- *  @note All accounting statistics and accounting mode live in nvidia driver and reset 
- *        to default (Disabled) when driver unloads.
- *        It is advised to run with persistence mode enabled.
- *
- *  @note Enabling accounting mode has no negative impact on the GPU performance.
- */
-/***************************************************************************************************/
-
-/**
- * Describes accounting statistics of a process.
- */
-typedef struct nvmlAccountingStats_st {
-    unsigned int gpuUtilization;                //!< Percent of time over the process's lifetime during which one or more kernels was executing on the GPU.
-                                                //! Utilization stats just like returned by \ref nvmlDeviceGetUtilizationRates but for the life time of a
-                                                //! process (not just the last sample period).
-                                                //! Set to NVML_VALUE_NOT_AVAILABLE if nvmlDeviceGetUtilizationRates is not supported
-    
-    unsigned int memoryUtilization;             //!< Percent of time over the process's lifetime during which global (device) memory was being read or written.
-                                                //! Set to NVML_VALUE_NOT_AVAILABLE if nvmlDeviceGetUtilizationRates is not supported
-    
-    unsigned long long maxMemoryUsage;          //!< Maximum total memory in bytes that was ever allocated by the process.
-                                                //! Set to NVML_VALUE_NOT_AVAILABLE if nvmlProcessInfo_t->usedGpuMemory is not supported
-    
-
-    unsigned long long time;                    //!< Amount of time in ms during which the compute context was active
-    
-    unsigned int reserved[8];
-} nvmlAccountingStats_t;
-
-/** @} */
-
-/***************************************************************************************************/
-/** @defgroup nvmlInitializationAndCleanup Initialization and Cleanup
- * This chapter describes the methods that handle NVML initialization and cleanup.
- * It is the user's responsibility to call \ref nvmlInit() before calling any other methods, and 
- * nvmlShutdown() once NVML is no longer being used.
- *  @{
- */
-/***************************************************************************************************/
-
-/**
- * Initialize NVML, but don't initialize any GPUs yet.
- *
- * \note In NVML 5.319 new nvmlInit_v2 has replaced nvmlInit"_v1" (default in NVML 4.304 and older) that
- *       did initialize all GPU devices in the system.
- *       
- * This allows NVML to communicate with a GPU
- * when other GPUs in the system are unstable or in a bad state.  When using this API, GPUs are
- * discovered and initialized in nvmlDeviceGetHandleBy* functions instead.
- * 
- * \note To contrast nvmlInit_v2 with nvmlInit"_v1", NVML 4.304 nvmlInit"_v1" will fail when any detected GPU is in
- *       a bad or unstable state.
- * 
- * For all products.
- *
- * This method, should be called once before invoking any other methods in the library.
- * A reference count of the number of initializations is maintained.  Shutdown only occurs
- * when the reference count reaches zero.
- * 
- * @return 
- *         - \ref NVML_SUCCESS                   if NVML has been properly initialized
- *         - \ref NVML_ERROR_DRIVER_NOT_LOADED   if NVIDIA driver is not running
- *         - \ref NVML_ERROR_NO_PERMISSION       if NVML does not have permission to talk to the driver
- *         - \ref NVML_ERROR_UNKNOWN             on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlInit(void);
-
-/**
- * Shut down NVML by releasing all GPU resources previously allocated with \ref nvmlInit().
- * 
- * For all products.
- *
- * This method should be called after NVML work is done, once for each call to \ref nvmlInit()
- * A reference count of the number of initializations is maintained.  Shutdown only occurs
- * when the reference count reaches zero.  For backwards compatibility, no error is reported if
- * nvmlShutdown() is called more times than nvmlInit().
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if NVML has been properly shut down
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlShutdown(void);
-
-/** @} */
-
-/***************************************************************************************************/
-/** @defgroup nvmlErrorReporting Error reporting
- * This chapter describes helper functions for error reporting routines.
- *  @{
- */
-/***************************************************************************************************/
-
-/**
- * Helper method for converting NVML error codes into readable strings.
- *
- * For all products
- *
- * @param result                               NVML error code to convert
- *
- * @return String representation of the error.
- *
- */
-const DECLDIR char* nvmlErrorString(nvmlReturn_t result);
-/** @} */
-
-
-/***************************************************************************************************/
-/** @defgroup nvmlConstants Constants
- *  @{
- */
-/***************************************************************************************************/
-
-/**
- * Buffer size guaranteed to be large enough for \ref nvmlDeviceGetInforomVersion and \ref nvmlDeviceGetInforomImageVersion
- */
-#define NVML_DEVICE_INFOROM_VERSION_BUFFER_SIZE       16
-
-/**
- * Buffer size guaranteed to be large enough for \ref nvmlDeviceGetUUID
- */
-#define NVML_DEVICE_UUID_BUFFER_SIZE                  80
-
-/**
- * Buffer size guaranteed to be large enough for \ref nvmlSystemGetDriverVersion
- */
-#define NVML_SYSTEM_DRIVER_VERSION_BUFFER_SIZE        80
-
-/**
- * Buffer size guaranteed to be large enough for \ref nvmlSystemGetNVMLVersion
- */
-#define NVML_SYSTEM_NVML_VERSION_BUFFER_SIZE          80
-
-/**
- * Buffer size guaranteed to be large enough for \ref nvmlDeviceGetName
- */
-#define NVML_DEVICE_NAME_BUFFER_SIZE                  64
-
-/**
- * Buffer size guaranteed to be large enough for \ref nvmlDeviceGetSerial
- */
-#define NVML_DEVICE_SERIAL_BUFFER_SIZE                30
-
-/**
- * Buffer size guaranteed to be large enough for \ref nvmlDeviceGetVbiosVersion
- */
-#define NVML_DEVICE_VBIOS_VERSION_BUFFER_SIZE         32
-
-/** @} */
-
-/***************************************************************************************************/
-/** @defgroup nvmlSystemQueries System Queries
- * This chapter describes the queries that NVML can perform against the local system. These queries
- * are not device-specific.
- *  @{
- */
-/***************************************************************************************************/
-
-/**
- * Retrieves the version of the system's graphics driver.
- * 
- * For all products.
- *
- * The version identifier is an alphanumeric string.  It will not exceed 80 characters in length
- * (including the NULL terminator).  See \ref nvmlConstants::NVML_SYSTEM_DRIVER_VERSION_BUFFER_SIZE.
- *
- * @param version                              Reference in which to return the version identifier
- * @param length                               The maximum allowed length of the string returned in \a version
- *
- * @return 
- *         - \ref NVML_SUCCESS                 if \a version has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a version is NULL
- *         - \ref NVML_ERROR_INSUFFICIENT_SIZE if \a length is too small 
- */
-nvmlReturn_t DECLDIR nvmlSystemGetDriverVersion(char *version, unsigned int length);
-
-/**
- * Retrieves the version of the NVML library.
- * 
- * For all products.
- *
- * The version identifier is an alphanumeric string.  It will not exceed 80 characters in length
- * (including the NULL terminator).  See \ref nvmlConstants::NVML_SYSTEM_NVML_VERSION_BUFFER_SIZE.
- *
- * @param version                              Reference in which to return the version identifier
- * @param length                               The maximum allowed length of the string returned in \a version
- *
- * @return 
- *         - \ref NVML_SUCCESS                 if \a version has been set
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a version is NULL
- *         - \ref NVML_ERROR_INSUFFICIENT_SIZE if \a length is too small 
- */
-nvmlReturn_t DECLDIR nvmlSystemGetNVMLVersion(char *version, unsigned int length);
-
-/**
- * Gets name of the process with provided process id
- *
- * For all products.
- *
- * Returned process name is cropped to provided length.
- * name string is encoded in ANSI.
- *
- * @param pid                                  The identifier of the process
- * @param name                                 Reference in which to return the process name
- * @param length                               The maximum allowed length of the string returned in \a name
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a name has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a name is NULL
- *         - \ref NVML_ERROR_NOT_FOUND         if process doesn't exists
- *         - \ref NVML_ERROR_NO_PERMISSION     if the user doesn't have permission to perform this operation
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlSystemGetProcessName(unsigned int pid, char *name, unsigned int length);
-
-/** @} */
-
-/***************************************************************************************************/
-/** @defgroup nvmlUnitQueries Unit Queries
- * This chapter describes that queries that NVML can perform against each unit. For S-class systems only.
- * In each case the device is identified with an nvmlUnit_t handle. This handle is obtained by 
- * calling \ref nvmlUnitGetHandleByIndex().
- *  @{
- */
-/***************************************************************************************************/
-
- /**
- * Retrieves the number of units in the system.
- *
- * For S-class products.
- *
- * @param unitCount                            Reference in which to return the number of units
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a unitCount has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a unitCount is NULL
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlUnitGetCount(unsigned int *unitCount);
-
-/**
- * Acquire the handle for a particular unit, based on its index.
- *
- * For S-class products.
- *
- * Valid indices are derived from the \a unitCount returned by \ref nvmlUnitGetCount(). 
- *   For example, if \a unitCount is 2 the valid indices are 0 and 1, corresponding to UNIT 0 and UNIT 1.
- *
- * The order in which NVML enumerates units has no guarantees of consistency between reboots.
- *
- * @param index                                The index of the target unit, >= 0 and < \a unitCount
- * @param unit                                 Reference in which to return the unit handle
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a unit has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a index is invalid or \a unit is NULL
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlUnitGetHandleByIndex(unsigned int index, nvmlUnit_t *unit);
-
-/**
- * Retrieves the static information associated with a unit.
- *
- * For S-class products.
- *
- * See \ref nvmlUnitInfo_t for details on available unit info.
- *
- * @param unit                                 The identifier of the target unit
- * @param info                                 Reference in which to return the unit information
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a info has been populated
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a unit is invalid or \a info is NULL
- */
-nvmlReturn_t DECLDIR nvmlUnitGetUnitInfo(nvmlUnit_t unit, nvmlUnitInfo_t *info);
-
-/**
- * Retrieves the LED state associated with this unit.
- *
- * For S-class products.
- *
- * See \ref nvmlLedState_t for details on allowed states.
- *
- * @param unit                                 The identifier of the target unit
- * @param state                                Reference in which to return the current LED state
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a state has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a unit is invalid or \a state is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if this is not an S-class product
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- * 
- * @see nvmlUnitSetLedState()
- */
-nvmlReturn_t DECLDIR nvmlUnitGetLedState(nvmlUnit_t unit, nvmlLedState_t *state);
-
-/**
- * Retrieves the PSU stats for the unit.
- *
- * For S-class products.
- *
- * See \ref nvmlPSUInfo_t for details on available PSU info.
- *
- * @param unit                                 The identifier of the target unit
- * @param psu                                  Reference in which to return the PSU information
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a psu has been populated
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a unit is invalid or \a psu is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if this is not an S-class product
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlUnitGetPsuInfo(nvmlUnit_t unit, nvmlPSUInfo_t *psu);
-
-/**
- * Retrieves the temperature readings for the unit, in degrees C.
- *
- * For S-class products.
- *
- * Depending on the product, readings may be available for intake (type=0), 
- * exhaust (type=1) and board (type=2).
- *
- * @param unit                                 The identifier of the target unit
- * @param type                                 The type of reading to take
- * @param temp                                 Reference in which to return the intake temperature
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a temp has been populated
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a unit or \a type is invalid or \a temp is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if this is not an S-class product
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlUnitGetTemperature(nvmlUnit_t unit, unsigned int type, unsigned int *temp);
-
-/**
- * Retrieves the fan speed readings for the unit.
- *
- * For S-class products.
- *
- * See \ref nvmlUnitFanSpeeds_t for details on available fan speed info.
- *
- * @param unit                                 The identifier of the target unit
- * @param fanSpeeds                            Reference in which to return the fan speed information
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a fanSpeeds has been populated
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a unit is invalid or \a fanSpeeds is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if this is not an S-class product
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlUnitGetFanSpeedInfo(nvmlUnit_t unit, nvmlUnitFanSpeeds_t *fanSpeeds);
-
-/**
- * Retrieves the set of GPU devices that are attached to the specified unit.
- *
- * For S-class products.
- *
- * The \a deviceCount argument is expected to be set to the size of the input \a devices array.
- *
- * @param unit                                 The identifier of the target unit
- * @param deviceCount                          Reference in which to provide the \a devices array size, and
- *                                             to return the number of attached GPU devices
- * @param devices                              Reference in which to return the references to the attached GPU devices
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a deviceCount and \a devices have been populated
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INSUFFICIENT_SIZE if \a deviceCount indicates that the \a devices array is too small
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a unit is invalid, either of \a deviceCount or \a devices is NULL
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlUnitGetDevices(nvmlUnit_t unit, unsigned int *deviceCount, nvmlDevice_t *devices);
-
-/**
- * Retrieves the IDs and firmware versions for any Host Interface Cards (HICs) in the system.
- * 
- * For S-class products.
- *
- * The \a hwbcCount argument is expected to be set to the size of the input \a hwbcEntries array.
- * The HIC must be connected to an S-class system for it to be reported by this function.
- *
- * @param hwbcCount                            Size of hwbcEntries array
- * @param hwbcEntries                          Array holding information about hwbc
- *
- * @return 
- *         - \ref NVML_SUCCESS                 if \a hwbcCount and \a hwbcEntries have been populated
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if either \a hwbcCount or \a hwbcEntries is NULL
- *         - \ref NVML_ERROR_INSUFFICIENT_SIZE if \a hwbcCount indicates that the \a hwbcEntries array is too small
- */
-nvmlReturn_t DECLDIR nvmlSystemGetHicVersion(unsigned int *hwbcCount, nvmlHwbcEntry_t *hwbcEntries);
-/** @} */
-
-/***************************************************************************************************/
-/** @defgroup nvmlDeviceQueries Device Queries
- * This chapter describes that queries that NVML can perform against each device.
- * In each case the device is identified with an nvmlDevice_t handle. This handle is obtained by  
- * calling one of \ref nvmlDeviceGetHandleByIndex(), \ref nvmlDeviceGetHandleBySerial(),
- * \ref nvmlDeviceGetHandleByPciBusId(). or \ref nvmlDeviceGetHandleByUUID(). 
- *  @{
- */
-/***************************************************************************************************/
-
- /**
- * Retrieves the number of compute devices in the system. A compute device is a single GPU.
- * 
- * For all products.
- *
- * Note: New nvmlDeviceGetCount_v2 (default in NVML 5.319) returns count of all devices in the system
- *       even if nvmlDeviceGetHandleByIndex_v2 returns NVML_ERROR_NO_PERMISSION for such device.
- *       Update your code to handle this error, or use NVML 4.304 or older nvml header file.
- *       For backward binary compatibility reasons _v1 version of the API is still present in the shared
- *       library.
- *       Old _v1 version of nvmlDeviceGetCount doesn't count devices that NVML has no permission to talk to.
- *
- * @param deviceCount                          Reference in which to return the number of accessible devices
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a deviceCount has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a deviceCount is NULL
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetCount(unsigned int *deviceCount);
-
-/**
- * Acquire the handle for a particular device, based on its index.
- * 
- * For all products.
- *
- * Valid indices are derived from the \a accessibleDevices count returned by 
- *   \ref nvmlDeviceGetCount(). For example, if \a accessibleDevices is 2 the valid indices  
- *   are 0 and 1, corresponding to GPU 0 and GPU 1.
- *
- * The order in which NVML enumerates devices has no guarantees of consistency between reboots. For that reason it
- *   is recommended that devices be looked up by their PCI ids or UUID. See 
- *   \ref nvmlDeviceGetHandleByUUID() and \ref nvmlDeviceGetHandleByPciBusId().
- *
- * Note: The NVML index may not correlate with other APIs, such as the CUDA device index.
- *
- * Starting from NVML 5, this API causes NVML to initialize the target GPU
- * NVML may initialize additional GPUs if:
- *  - The target GPU is an SLI slave
- * 
- * Note: New nvmlDeviceGetCount_v2 (default in NVML 5.319) returns count of all devices in the system
- *       even if nvmlDeviceGetHandleByIndex_v2 returns NVML_ERROR_NO_PERMISSION for such device.
- *       Update your code to handle this error, or use NVML 4.304 or older nvml header file.
- *       For backward binary compatibility reasons _v1 version of the API is still present in the shared
- *       library.
- *       Old _v1 version of nvmlDeviceGetCount doesn't count devices that NVML has no permission to talk to.
- *
- *       This means that nvmlDeviceGetHandleByIndex_v2 and _v1 can return different devices for the same index.
- *       If you don't touch macros that map old (_v1) versions to _v2 versions at the top of the file you don't
- *       need to worry about that.
- *
- * @param index                                The index of the target GPU, >= 0 and < \a accessibleDevices
- * @param device                               Reference in which to return the device handle
- * 
- * @return 
- *         - \ref NVML_SUCCESS                  if \a device has been set
- *         - \ref NVML_ERROR_UNINITIALIZED      if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT   if \a index is invalid or \a device is NULL
- *         - \ref NVML_ERROR_INSUFFICIENT_POWER if any attached devices have improperly attached external power cables
- *         - \ref NVML_ERROR_NO_PERMISSION      if the user doesn't have permission to talk to this device
- *         - \ref NVML_ERROR_IRQ_ISSUE          if NVIDIA kernel detected an interrupt issue with the attached GPUs
- *         - \ref NVML_ERROR_GPU_IS_LOST        if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN            on any unexpected error
- *
- * @see nvmlDeviceGetIndex
- * @see nvmlDeviceGetCount
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetHandleByIndex(unsigned int index, nvmlDevice_t *device);
-
-/**
- * Acquire the handle for a particular device, based on its board serial number.
- *
- * For all products.
- *
- * This number corresponds to the value printed directly on the board, and to the value returned by
- *   \ref nvmlDeviceGetSerial().
- *
- * @deprecated Since more than one GPU can exist on a single board this function is deprecated in favor 
- *             of \ref nvmlDeviceGetHandleByUUID.
- *             For dual GPU boards this function will return NVML_ERROR_INVALID_ARGUMENT.
- *
- * Starting from NVML 5, this API causes NVML to initialize the target GPU
- * NVML may initialize additional GPUs as it searches for the target GPU
- *
- * @param serial                               The board serial number of the target GPU
- * @param device                               Reference in which to return the device handle
- * 
- * @return 
- *         - \ref NVML_SUCCESS                  if \a device has been set
- *         - \ref NVML_ERROR_UNINITIALIZED      if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT   if \a serial is invalid, \a device is NULL or more than one
- *                                              device has the same serial (dual GPU boards)
- *         - \ref NVML_ERROR_NOT_FOUND          if \a serial does not match a valid device on the system
- *         - \ref NVML_ERROR_INSUFFICIENT_POWER if any attached devices have improperly attached external power cables
- *         - \ref NVML_ERROR_IRQ_ISSUE          if NVIDIA kernel detected an interrupt issue with the attached GPUs
- *         - \ref NVML_ERROR_GPU_IS_LOST        if any GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN            on any unexpected error
- *
- * @see nvmlDeviceGetSerial
- * @see nvmlDeviceGetHandleByUUID
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetHandleBySerial(const char *serial, nvmlDevice_t *device);
-
-/**
- * Acquire the handle for a particular device, based on its globally unique immutable UUID associated with each device.
- *
- * For all products.
- *
- * @param uuid                                 The UUID of the target GPU
- * @param device                               Reference in which to return the device handle
- * 
- * Starting from NVML 5, this API causes NVML to initialize the target GPU
- * NVML may initialize additional GPUs as it searches for the target GPU
- *
- * @return 
- *         - \ref NVML_SUCCESS                  if \a device has been set
- *         - \ref NVML_ERROR_UNINITIALIZED      if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT   if \a uuid is invalid or \a device is null
- *         - \ref NVML_ERROR_NOT_FOUND          if \a uuid does not match a valid device on the system
- *         - \ref NVML_ERROR_INSUFFICIENT_POWER if any attached devices have improperly attached external power cables
- *         - \ref NVML_ERROR_IRQ_ISSUE          if NVIDIA kernel detected an interrupt issue with the attached GPUs
- *         - \ref NVML_ERROR_GPU_IS_LOST        if any GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN            on any unexpected error
- *
- * @see nvmlDeviceGetUUID
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetHandleByUUID(const char *uuid, nvmlDevice_t *device);
-
-/**
- * Acquire the handle for a particular device, based on its PCI bus id.
- * 
- * For all products.
- *
- * This value corresponds to the nvmlPciInfo_t::busId returned by \ref nvmlDeviceGetPciInfo().
- *
- * Starting from NVML 5, this API causes NVML to initialize the target GPU
- * NVML may initialize additional GPUs if:
- *  - The target GPU is an SLI slave
- *
- * \note NVML 4.304 and older version of nvmlDeviceGetHandleByPciBusId"_v1" returns NVML_ERROR_NOT_FOUND 
- *       instead of NVML_ERROR_NO_PERMISSION.
- *
- * @param pciBusId                             The PCI bus id of the target GPU
- * @param device                               Reference in which to return the device handle
- * 
- * @return 
- *         - \ref NVML_SUCCESS                  if \a device has been set
- *         - \ref NVML_ERROR_UNINITIALIZED      if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT   if \a pciBusId is invalid or \a device is NULL
- *         - \ref NVML_ERROR_NOT_FOUND          if \a pciBusId does not match a valid device on the system
- *         - \ref NVML_ERROR_INSUFFICIENT_POWER if the attached device has improperly attached external power cables
- *         - \ref NVML_ERROR_NO_PERMISSION      if the user doesn't have permission to talk to this device
- *         - \ref NVML_ERROR_IRQ_ISSUE          if NVIDIA kernel detected an interrupt issue with the attached GPUs
- *         - \ref NVML_ERROR_GPU_IS_LOST        if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN            on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetHandleByPciBusId(const char *pciBusId, nvmlDevice_t *device);
-
-/**
- * Retrieves the name of this device. 
- * 
- * For all products.
- *
- * The name is an alphanumeric string that denotes a particular product, e.g. Tesla &tm; C2070. It will not
- * exceed 64 characters in length (including the NULL terminator).  See \ref
- * nvmlConstants::NVML_DEVICE_NAME_BUFFER_SIZE.
- *
- * @param device                               The identifier of the target device
- * @param name                                 Reference in which to return the product name
- * @param length                               The maximum allowed length of the string returned in \a name
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a name has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid, or \a name is NULL
- *         - \ref NVML_ERROR_INSUFFICIENT_SIZE if \a length is too small
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetName(nvmlDevice_t device, char *name, unsigned int length);
-
-/**
- * Retrieves the NVML index of this device.
- *
- * For all products.
- * 
- * Valid indices are derived from the \a accessibleDevices count returned by 
- *   \ref nvmlDeviceGetCount(). For example, if \a accessibleDevices is 2 the valid indices  
- *   are 0 and 1, corresponding to GPU 0 and GPU 1.
- *
- * The order in which NVML enumerates devices has no guarantees of consistency between reboots. For that reason it
- *   is recommended that devices be looked up by their PCI ids or GPU UUID. See 
- *   \ref nvmlDeviceGetHandleByPciBusId() and \ref nvmlDeviceGetHandleByUUID().
- *
- * Note: The NVML index may not correlate with other APIs, such as the CUDA device index.
- *
- * @param device                               The identifier of the target device
- * @param index                                Reference in which to return the NVML index of the device
- *
- * @return 
- *         - \ref NVML_SUCCESS                 if \a index has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid, or \a index is NULL
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- *
- * @see nvmlDeviceGetHandleByIndex()
- * @see nvmlDeviceGetCount()
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetIndex(nvmlDevice_t device, unsigned int *index);
-
-/**
- * Retrieves the globally unique board serial number associated with this device's board.
- *
- * For Tesla &tm; and Quadro &reg; products from the Fermi and Kepler families.
- *
- * The serial number is an alphanumeric string that will not exceed 30 characters (including the NULL terminator).
- * This number matches the serial number tag that is physically attached to the board.  See \ref
- * nvmlConstants::NVML_DEVICE_SERIAL_BUFFER_SIZE.
- *
- * @param device                               The identifier of the target device
- * @param serial                               Reference in which to return the board/module serial number
- * @param length                               The maximum allowed length of the string returned in \a serial
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a serial has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid, or \a serial is NULL
- *         - \ref NVML_ERROR_INSUFFICIENT_SIZE if \a length is too small
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not support this feature
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetSerial(nvmlDevice_t device, char *serial, unsigned int length);
-
-/**
- * Retrieves the globally unique immutable UUID associated with this device, as a 5 part hexadecimal string,
- * that augments the immutable, board serial identifier.
- *
- * For all CUDA capable GPUs.
- *
- * The UUID is a globally unique identifier. It is the only available identifier for pre-Fermi-architecture products.
- * It does NOT correspond to any identifier printed on the board.  It will not exceed 80 characters in length
- * (including the NULL terminator).  See \ref nvmlConstants::NVML_DEVICE_UUID_BUFFER_SIZE.
- *
- * @param device                               The identifier of the target device
- * @param uuid                                 Reference in which to return the GPU UUID
- * @param length                               The maximum allowed length of the string returned in \a uuid
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a uuid has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid, or \a uuid is NULL
- *         - \ref NVML_ERROR_INSUFFICIENT_SIZE if \a length is too small 
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not support this feature
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetUUID(nvmlDevice_t device, char *uuid, unsigned int length);
-
-/**
- * Retrieves minor number for the device. The minor number for the device is such that the Nvidia device node file for 
- * each GPU will have the form /dev/nvidia[minor number].
- *
- * For all the GPUs. Supported only for Linux
- *
- * @param device                                The identifier of the target device
- * @param minorNumber                           Reference in which to return the minor number for the device
- * @return
- *         - \ref NVML_SUCCESS                 if the minor number is successfully retrieved
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a minorNumber is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if this query is not supported by the device
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetMinorNumber(nvmlDevice_t device, unsigned int *minorNumber);
-
-/**
- * Retrieves the version information for the device's infoROM object.
- *
- * For Tesla &tm; and Quadro &reg; products from the Fermi and Kepler families.
- *
- * Fermi and higher parts have non-volatile on-board memory for persisting device info, such as aggregate 
- * ECC counts. The version of the data structures in this memory may change from time to time. It will not
- * exceed 16 characters in length (including the NULL terminator).
- * See \ref nvmlConstants::NVML_DEVICE_INFOROM_VERSION_BUFFER_SIZE.
- *
- * See \ref nvmlInforomObject_t for details on the available infoROM objects.
- *
- * @param device                               The identifier of the target device
- * @param object                               The target infoROM object
- * @param version                              Reference in which to return the infoROM version
- * @param length                               The maximum allowed length of the string returned in \a version
- *
- * @return 
- *         - \ref NVML_SUCCESS                 if \a version has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a version is NULL
- *         - \ref NVML_ERROR_INSUFFICIENT_SIZE if \a length is too small 
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not have an infoROM
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- *
- * @see nvmlDeviceGetInforomImageVersion
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetInforomVersion(nvmlDevice_t device, nvmlInforomObject_t object, char *version, unsigned int length);
-
-/**
- * Retrieves the global infoROM image version
- *
- * For Tesla &tm; and Quadro &reg; products from the Kepler family.
- *
- * Image version just like VBIOS version uniquely describes the exact version of the infoROM flashed on the board 
- * in contrast to infoROM object version which is only an indicator of supported features.
- * Version string will not exceed 16 characters in length (including the NULL terminator).
- * See \ref nvmlConstants::NVML_DEVICE_INFOROM_VERSION_BUFFER_SIZE.
- *
- * @param device                               The identifier of the target device
- * @param version                              Reference in which to return the infoROM image version
- * @param length                               The maximum allowed length of the string returned in \a version
- *
- * @return 
- *         - \ref NVML_SUCCESS                 if \a version has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a version is NULL
- *         - \ref NVML_ERROR_INSUFFICIENT_SIZE if \a length is too small 
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not have an infoROM
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- *
- * @see nvmlDeviceGetInforomVersion
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetInforomImageVersion(nvmlDevice_t device, char *version, unsigned int length);
-
-/**
- * Retrieves the checksum of the configuration stored in the device's infoROM.
- *
- * For Tesla &tm; and Quadro &reg; products from the Fermi and Kepler families.
- *
- * Can be used to make sure that two GPUs have the exact same configuration.
- * Current checksum takes into account configuration stored in PWR and ECC infoROM objects.
- * Checksum can change between driver releases or when user changes configuration (e.g. disable/enable ECC)
- *
- * @param device                               The identifier of the target device
- * @param checksum                             Reference in which to return the infoROM configuration checksum
- *
- * @return 
- *         - \ref NVML_SUCCESS                 if \a checksum has been set
- *         - \ref NVML_ERROR_CORRUPTED_INFOROM if the device's checksum couldn't be retrieved due to infoROM corruption
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a checksum is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not support this feature
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error 
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetInforomConfigurationChecksum(nvmlDevice_t device, unsigned int *checksum);
-
-/**
- * Reads the infoROM from the flash and verifies the checksums.
- *
- * For Tesla &tm; and Quadro &reg; products from the Fermi and Kepler families.
- *
- * @param device                               The identifier of the target device
- *
- * @return 
- *         - \ref NVML_SUCCESS                 if infoROM is not corrupted
- *         - \ref NVML_ERROR_CORRUPTED_INFOROM if the device's infoROM is corrupted
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not support this feature
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error 
- */
-nvmlReturn_t DECLDIR nvmlDeviceValidateInforom(nvmlDevice_t device);
-
-/**
- * Retrieves the display mode for the device.
- *
- * For Tesla &tm; and Quadro &reg; products from the Fermi and Kepler families.
- *
- * This method indicates whether a physical display (e.g. monitor) is currently connected to
- * any of the device's connectors.
- *
- * See \ref nvmlEnableState_t for details on allowed modes.
- *
- * @param device                               The identifier of the target device
- * @param display                              Reference in which to return the display mode
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a display has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a display is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not support this feature
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetDisplayMode(nvmlDevice_t device, nvmlEnableState_t *display);
-
-/**
- * Retrieves the display active state for the device.
- *
- * For Tesla &tm; and Quadro &reg; products from the Fermi and Kepler families.
- *
- * This method indicates whether a display is initialized on the device.
- * For example whether X Server is attached to this device and has allocated memory for the screen.
- *
- * Display can be active even when no monitor is physically attached.
- *
- * See \ref nvmlEnableState_t for details on allowed modes.
- *
- * @param device                               The identifier of the target device
- * @param isActive                             Reference in which to return the display active state
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a isActive has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a isActive is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not support this feature
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetDisplayActive(nvmlDevice_t device, nvmlEnableState_t *isActive);
-
-/**
- * Retrieves the persistence mode associated with this device.
- *
- * For all CUDA-capable products.
- * For Linux only.
- *
- * When driver persistence mode is enabled the driver software state is not torn down when the last 
- * client disconnects. By default this feature is disabled. 
- *
- * See \ref nvmlEnableState_t for details on allowed modes.
- *
- * @param device                               The identifier of the target device
- * @param mode                                 Reference in which to return the current driver persistence mode
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a mode has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a mode is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not support this feature
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- *
- * @see nvmlDeviceSetPersistenceMode()
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetPersistenceMode(nvmlDevice_t device, nvmlEnableState_t *mode);
-
-/**
- * Retrieves the PCI attributes of this device.
- * 
- * For all products.
- *
- * See \ref nvmlPciInfo_t for details on the available PCI info.
- *
- * @param device                               The identifier of the target device
- * @param pci                                  Reference in which to return the PCI info
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a pci has been populated
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a pci is NULL
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetPciInfo(nvmlDevice_t device, nvmlPciInfo_t *pci);
-
-/**
- * Retrieves the maximum PCIe link generation possible with this device and system
- *
- * I.E. for a generation 2 PCIe device attached to a generation 1 PCIe bus the max link generation this function will
- * report is generation 1.
- * 
- * For Tesla &tm; and Quadro &reg; products from the Fermi and Kepler families.
- * 
- * @param device                               The identifier of the target device
- * @param maxLinkGen                           Reference in which to return the max PCIe link generation
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a maxLinkGen has been populated
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a maxLinkGen is null
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if PCIe link information is not available
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetMaxPcieLinkGeneration(nvmlDevice_t device, unsigned int *maxLinkGen);
-
-/**
- * Retrieves the maximum PCIe link width possible with this device and system
- *
- * I.E. for a device with a 16x PCIe bus width attached to a 8x PCIe system bus this function will report
- * a max link width of 8.
- * 
- * For Tesla &tm; and Quadro &reg; products from the Fermi and Kepler families.
- * 
- * @param device                               The identifier of the target device
- * @param maxLinkWidth                         Reference in which to return the max PCIe link generation
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a maxLinkWidth has been populated
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a maxLinkWidth is null
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if PCIe link information is not available
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetMaxPcieLinkWidth(nvmlDevice_t device, unsigned int *maxLinkWidth);
-
-/**
- * Retrieves the current PCIe link generation
- * 
- * For Tesla &tm; and Quadro &reg; products from the Fermi and Kepler families.
- * 
- * @param device                               The identifier of the target device
- * @param currLinkGen                          Reference in which to return the current PCIe link generation
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a currLinkGen has been populated
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a currLinkGen is null
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if PCIe link information is not available
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetCurrPcieLinkGeneration(nvmlDevice_t device, unsigned int *currLinkGen);
-
-/**
- * Retrieves the current PCIe link width
- * 
- * For Tesla &tm; and Quadro &reg; products from the Fermi and Kepler families.
- * 
- * @param device                               The identifier of the target device
- * @param currLinkWidth                        Reference in which to return the current PCIe link generation
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a currLinkWidth has been populated
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a currLinkWidth is null
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if PCIe link information is not available
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetCurrPcieLinkWidth(nvmlDevice_t device, unsigned int *currLinkWidth);
-
-/**
- * Retrieves the current clock speeds for the device.
- *
- * For Tesla &tm; and Quadro &reg; products from the Fermi and Kepler families.
- *
- * See \ref nvmlClockType_t for details on available clock information.
- *
- * @param device                               The identifier of the target device
- * @param type                                 Identify which clock domain to query
- * @param clock                                Reference in which to return the clock speed in MHz
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a clock has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a clock is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device cannot report the specified clock
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetClockInfo(nvmlDevice_t device, nvmlClockType_t type, unsigned int *clock);
-
-/**
- * Retrieves the maximum clock speeds for the device.
- *
- * For Tesla &tm; and Quadro &reg; products from the Fermi and Kepler families.
- *
- * See \ref nvmlClockType_t for details on available clock information.
- *
- * \note On GPUs from Fermi family current P0 clocks (reported by \ref nvmlDeviceGetClockInfo) can differ from max clocks
- *       by few MHz.
- *
- * @param device                               The identifier of the target device
- * @param type                                 Identify which clock domain to query
- * @param clock                                Reference in which to return the clock speed in MHz
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a clock has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a clock is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device cannot report the specified clock
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetMaxClockInfo(nvmlDevice_t device, nvmlClockType_t type, unsigned int *clock);
-
-/**
- * Retrieves the current setting of a clock that applications will use unless an overspec situation occurs.
- * Can be changed using \ref nvmlDeviceSetApplicationsClocks.
- *
- * For Tesla &tm; products from the Kepler family.
- *
- * @param device                               The identifier of the target device
- * @param clockType                            Identify which clock domain to query
- * @param clockMHz                             Reference in which to return the clock in MHz
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a clockMHz has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a clockMHz is NULL or \a clockType is invalid
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not support this feature
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetApplicationsClock(nvmlDevice_t device, nvmlClockType_t clockType, unsigned int *clockMHz);
-
-/**
- * Retrieves the default applications clock that GPU boots with or 
- * defaults to after \ref nvmlDeviceResetApplicationsClocks call.
- *
- * For Tesla &tm; products from the Kepler family.
- *
- * @param device                               The identifier of the target device
- * @param clockType                            Identify which clock domain to query
- * @param clockMHz                             Reference in which to return the default clock in MHz
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a clockMHz has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a clockMHz is NULL or \a clockType is invalid
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not support this feature
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- *
- * \see nvmlDeviceGetApplicationsClock
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetDefaultApplicationsClock(nvmlDevice_t device, nvmlClockType_t clockType, unsigned int *clockMHz);
-
-/**
- * Resets the application clock to the default value
- *
- * This is the applications clock that will be used after system reboot or driver reload.
- * Default value is constant, but the current value an be changed using \ref nvmlDeviceSetApplicationsClocks.
- *
- * @see nvmlDeviceGetApplicationsClock
- * @see nvmlDeviceSetApplicationsClocks
- *
- * For Tesla &tm; products from the Kepler family.
- *
- * @param device                               The identifier of the target device
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if new settings were successfully set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not support this feature
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlDeviceResetApplicationsClocks(nvmlDevice_t device);
-
-/**
- * Retrieves the list of possible memory clocks that can be used as an argument for \ref nvmlDeviceSetApplicationsClocks.
- *
- * For Tesla &tm; products from the Kepler family.
- *
- * @param device                               The identifier of the target device
- * @param count                                Reference in which to provide the \a clocksMHz array size, and
- *                                             to return the number of elements
- * @param clocksMHz                            Reference in which to return the clock in MHz
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a count and \a clocksMHz have been populated 
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a count is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not support this feature
- *         - \ref NVML_ERROR_INSUFFICIENT_SIZE if \a count is too small (\a count is set to the number of
- *                                                required elements)
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- *
- * @see nvmlDeviceSetApplicationsClocks
- * @see nvmlDeviceGetSupportedGraphicsClocks
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetSupportedMemoryClocks(nvmlDevice_t device, unsigned int *count, unsigned int *clocksMHz);
-
-/**
- * Retrieves the list of possible graphics clocks that can be used as an argument for \ref nvmlDeviceSetApplicationsClocks.
- *
- * For Tesla &tm; products and Quadro &reg; products from the Kepler family.
- *
- * @param device                               The identifier of the target device
- * @param memoryClockMHz                       Memory clock for which to return possible graphics clocks
- * @param count                                Reference in which to provide the \a clocksMHz array size, and
- *                                             to return the number of elements
- * @param clocksMHz                            Reference in which to return the clocks in MHz
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a count and \a clocksMHz have been populated 
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_NOT_FOUND         if the specified \a memoryClockMHz is not a supported frequency
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a clock is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not support this feature
- *         - \ref NVML_ERROR_INSUFFICIENT_SIZE if \a count is too small 
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- *
- * @see nvmlDeviceSetApplicationsClocks
- * @see nvmlDeviceGetSupportedMemoryClocks
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetSupportedGraphicsClocks(nvmlDevice_t device, unsigned int memoryClockMHz, unsigned int *count, unsigned int *clocksMHz);
-
-
-/**
- * Retrieves the intended operating speed of the device's fan.
- *
- * Note: The reported speed is the intended fan speed.  If the fan is physically blocked and unable to spin, the
- * output will not match the actual fan speed.
- * 
- * For all discrete products with dedicated fans.
- *
- * The fan speed is expressed as a percent of the maximum, i.e. full speed is 100%.
- *
- * @param device                               The identifier of the target device
- * @param speed                                Reference in which to return the fan speed percentage
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a speed has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a speed is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not have a fan
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetFanSpeed(nvmlDevice_t device, unsigned int *speed);
-
-/**
- * Retrieves the current temperature readings for the device, in degrees C. 
- * 
- * For all discrete and S-class products.
- *
- * See \ref nvmlTemperatureSensors_t for details on available temperature sensors.
- *
- * @param device                               The identifier of the target device
- * @param sensorType                           Flag that indicates which sensor reading to retrieve
- * @param temp                                 Reference in which to return the temperature reading
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a temp has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid, \a sensorType is invalid or \a temp is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not have the specified sensor
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetTemperature(nvmlDevice_t device, nvmlTemperatureSensors_t sensorType, unsigned int *temp);
-
-/**
- * Retrieves the current performance state for the device. 
- *
- * For Tesla &tm; and Quadro &reg; products from the Fermi and Kepler families.
- *
- * See \ref nvmlPstates_t for details on allowed performance states.
- *
- * @param device                               The identifier of the target device
- * @param pState                               Reference in which to return the performance state reading
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a pState has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a pState is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not support this feature
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetPerformanceState(nvmlDevice_t device, nvmlPstates_t *pState);
-
-/**
- * Retrieves current clocks throttling reasons.
- *
- * For Tesla &tm; products from Kepler family.
- *
- * \note More than one bit can be enabled at the same time. Multiple reasons can be affecting clocks at once.
- *
- * @param device                                The identifier of the target device
- * @param clocksThrottleReasons                 Reference in which to return bitmask of active clocks throttle
- *                                                  reasons
- *
- * @return 
- *         - \ref NVML_SUCCESS                 if \a clocksThrottleReasons has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a clocksThrottleReasons is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not support this feature
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- *
- * @see nvmlClocksThrottleReasons
- * @see nvmlDeviceGetSupportedClocksThrottleReasons
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetCurrentClocksThrottleReasons(nvmlDevice_t device, unsigned long long *clocksThrottleReasons);
-
-/**
- * Retrieves bitmask of supported clocks throttle reasons that can be returned by 
- * \ref nvmlDeviceGetCurrentClocksThrottleReasons
- *
- * For all devices
- *
- * @param device                               The identifier of the target device
- * @param supportedClocksThrottleReasons       Reference in which to return bitmask of supported
- *                                              clocks throttle reasons
- *
- * @return 
- *         - \ref NVML_SUCCESS                 if \a supportedClocksThrottleReasons has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a supportedClocksThrottleReasons is NULL
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- *
- * @see nvmlClocksThrottleReasons
- * @see nvmlDeviceGetCurrentClocksThrottleReasons
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetSupportedClocksThrottleReasons(nvmlDevice_t device, unsigned long long *supportedClocksThrottleReasons);
-
-/**
- * Deprecated: Use \ref nvmlDeviceGetPerformanceState. This function exposes an incorrect generalization.
- *
- * Retrieve the current performance state for the device. 
- *
- * For Tesla &tm; and Quadro &reg; products from the Fermi and Kepler families.
- *
- * See \ref nvmlPstates_t for details on allowed performance states.
- *
- * @param device                               The identifier of the target device
- * @param pState                               Reference in which to return the performance state reading
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a pState has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a pState is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not support this feature
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetPowerState(nvmlDevice_t device, nvmlPstates_t *pState);
-
-/**
- * Retrieves the power management mode associated with this device.
- *
- * For "GF11x" Tesla &tm; and Quadro &reg; products from the Fermi family.
- *     - Requires \a NVML_INFOROM_POWER version 3.0 or higher.
- *
- * For Tesla &tm; and Quadro &reg; products from the Kepler family.
- *     - Does not require \a NVML_INFOROM_POWER object.
- *
- * This flag indicates whether any power management algorithm is currently active on the device. An 
- * enabled state does not necessarily mean the device is being actively throttled -- only that 
- * that the driver will do so if the appropriate conditions are met.
- *
- * See \ref nvmlEnableState_t for details on allowed modes.
- *
- * @param device                               The identifier of the target device
- * @param mode                                 Reference in which to return the current power management mode
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a mode has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a mode is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not support this feature
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetPowerManagementMode(nvmlDevice_t device, nvmlEnableState_t *mode);
-
-/**
- * Retrieves the power management limit associated with this device.
- *
- * For "GF11x" Tesla &tm; and Quadro &reg; products from the Fermi family.
- *     - Requires \a NVML_INFOROM_POWER version 3.0 or higher.
- *
- * For Tesla &tm; and Quadro &reg; products from the Kepler family.
- *     - Does not require \a NVML_INFOROM_POWER object.
- *
- * The power limit defines the upper boundary for the card's power draw. If
- * the card's total power draw reaches this limit the power management algorithm kicks in.
- *
- * This reading is only available if power management mode is supported. 
- * See \ref nvmlDeviceGetPowerManagementMode.
- *
- * @param device                               The identifier of the target device
- * @param limit                                Reference in which to return the power management limit in milliwatts
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a limit has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a limit is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not support this feature
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetPowerManagementLimit(nvmlDevice_t device, unsigned int *limit);
-
-/**
- * Retrieves information about possible values of power management limits on this device.
- *
- * For Tesla &tm; and Quadro &reg; products from the Kepler family.
- *
- * @param device                               The identifier of the target device
- * @param minLimit                             Reference in which to return the minimum power management limit in milliwatts
- * @param maxLimit                             Reference in which to return the maximum power management limit in milliwatts
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a minLimit and \a maxLimit have been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a minLimit or \a maxLimit is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not support this feature
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- *
- * @see nvmlDeviceSetPowerManagementLimit
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetPowerManagementLimitConstraints(nvmlDevice_t device, unsigned int *minLimit, unsigned int *maxLimit);
-
-/**
- * Retrieves default power management limit on this device, in milliwatts.
- * Default power management limit is a power management limit that the device boots with.
- *
- * For Tesla &tm; and Quadro &reg; products from the Kepler family.
- *
- * @param device                               The identifier of the target device
- * @param defaultLimit                         Reference in which to return the default power management limit in milliwatts
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a defaultLimit has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a defaultLimit is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not support this feature
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetPowerManagementDefaultLimit(nvmlDevice_t device, unsigned int *defaultLimit);
-
-/**
- * Retrieves power usage for this GPU in milliwatts and its associated circuitry (e.g. memory)
- *
- * For "GF11x" Tesla &tm; and Quadro &reg; products from the Fermi family.
- *     - Requires \a NVML_INFOROM_POWER version 3.0 or higher.
- *
- * For Tesla &tm; and Quadro &reg; products from the Kepler family.
- *     - Does not require \a NVML_INFOROM_POWER object.
- *
- * On Fermi and Kepler GPUs the reading is accurate to within +/- 5% of current power draw.
- *
- * It is only available if power management mode is supported. See \ref nvmlDeviceGetPowerManagementMode.
- *
- * @param device                               The identifier of the target device
- * @param power                                Reference in which to return the power usage information
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a power has been populated
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a power is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not support power readings
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetPowerUsage(nvmlDevice_t device, unsigned int *power);
-
-/**
- * Get the effective power limit that the driver enforces after taking into account all limiters
- *
- * Note: This can be different from the \ref nvmlDeviceGetPowerManagementLimit if other limits are set elsewhere
- * This includes the out of band power limit interface
- *
- * @param device                           The device to communicate with
- * @param limit                            Reference in which to return the power management limit in milliwatts
- *
- * @return 
- *         - \ref NVML_SUCCESS                 if \a limit has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a limit is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not support this feature
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetEnforcedPowerLimit(nvmlDevice_t device, unsigned int *limit);
-
-/**
- * Retrieves the current GOM and pending GOM (the one that GPU will switch to after reboot).
- *
- * For GK110 M-class and X-class Tesla &tm; products from the Kepler family.
- * Not supported on Quadro &reg; and Tesla &tm; C-class products.
- *
- * @param device                               The identifier of the target device
- * @param current                              Reference in which to return the current GOM
- * @param pending                              Reference in which to return the pending GOM
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a mode has been populated
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a current or \a pending is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not support this feature
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- *
- * @see nvmlGpuOperationMode_t
- * @see nvmlDeviceSetGpuOperationMode
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetGpuOperationMode(nvmlDevice_t device, nvmlGpuOperationMode_t *current, nvmlGpuOperationMode_t *pending);
-
-/**
- * Retrieves the amount of used, free and total memory available on the device, in bytes.
- * 
- * For all products.
- *
- * Enabling ECC reduces the amount of total available memory, due to the extra required parity bits.
- * Under WDDM most device memory is allocated and managed on startup by Windows.
- *
- * Under Linux and Windows TCC, the reported amount of used memory is equal to the sum of memory allocated 
- * by all active channels on the device.
- *
- * See \ref nvmlMemory_t for details on available memory info.
- *
- * @param device                               The identifier of the target device
- * @param memory                               Reference in which to return the memory information
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a memory has been populated
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a memory is NULL
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetMemoryInfo(nvmlDevice_t device, nvmlMemory_t *memory);
-
-/**
- * Retrieves the current compute mode for the device.
- *
- * For all CUDA-capable products.
- *
- * See \ref nvmlComputeMode_t for details on allowed compute modes.
- *
- * @param device                               The identifier of the target device
- * @param mode                                 Reference in which to return the current compute mode
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a mode has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a mode is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not support this feature
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- *
- * @see nvmlDeviceSetComputeMode()
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetComputeMode(nvmlDevice_t device, nvmlComputeMode_t *mode);
-
-/**
- * Retrieves the current and pending ECC modes for the device.
- *
- * For Tesla &tm; and Quadro &reg; products from the Fermi and Kepler families.
- * Requires \a NVML_INFOROM_ECC version 1.0 or higher.
- *
- * Changing ECC modes requires a reboot. The "pending" ECC mode refers to the target mode following
- * the next reboot.
- *
- * See \ref nvmlEnableState_t for details on allowed modes.
- *
- * @param device                               The identifier of the target device
- * @param current                              Reference in which to return the current ECC mode
- * @param pending                              Reference in which to return the pending ECC mode
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a current and \a pending have been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or either \a current or \a pending is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not support this feature
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- *
- * @see nvmlDeviceSetEccMode()
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetEccMode(nvmlDevice_t device, nvmlEnableState_t *current, nvmlEnableState_t *pending);
-
-/**
- * Retrieves the total ECC error counts for the device.
- *
- * For Tesla &tm; and Quadro &reg; products from the Fermi and Kepler families.
- * Requires \a NVML_INFOROM_ECC version 1.0 or higher.
- * Requires ECC Mode to be enabled.
- *
- * The total error count is the sum of errors across each of the separate memory systems, i.e. the total set of 
- * errors across the entire device.
- *
- * See \ref nvmlMemoryErrorType_t for a description of available error types.\n
- * See \ref nvmlEccCounterType_t for a description of available counter types.
- *
- * @param device                               The identifier of the target device
- * @param errorType                            Flag that specifies the type of the errors. 
- * @param counterType                          Flag that specifies the counter-type of the errors. 
- * @param eccCounts                            Reference in which to return the specified ECC errors
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a eccCounts has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device, \a errorType or \a counterType is invalid, or \a eccCounts is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not support this feature
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- *
- * @see nvmlDeviceClearEccErrorCounts()
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetTotalEccErrors(nvmlDevice_t device, nvmlMemoryErrorType_t errorType, nvmlEccCounterType_t counterType, unsigned long long *eccCounts);
-
-/**
- * Retrieves the detailed ECC error counts for the device.
- *
- * @deprecated   This API supports only a fixed set of ECC error locations
- *               On different GPU architectures different locations are supported
- *               See \ref nvmlDeviceGetMemoryErrorCounter
- *
- * For Tesla &tm; and Quadro &reg; products from the Fermi and Kepler families.
- * Requires \a NVML_INFOROM_ECC version 2.0 or higher to report aggregate location-based ECC counts.
- * Requires \a NVML_INFOROM_ECC version 1.0 or higher to report all other ECC counts.
- * Requires ECC Mode to be enabled.
- *
- * Detailed errors provide separate ECC counts for specific parts of the memory system.
- *
- * Reports zero for unsupported ECC error counters when a subset of ECC error counters are supported.
- *
- * See \ref nvmlMemoryErrorType_t for a description of available bit types.\n
- * See \ref nvmlEccCounterType_t for a description of available counter types.\n
- * See \ref nvmlEccErrorCounts_t for a description of provided detailed ECC counts.
- *
- * @param device                               The identifier of the target device
- * @param errorType                            Flag that specifies the type of the errors. 
- * @param counterType                          Flag that specifies the counter-type of the errors. 
- * @param eccCounts                            Reference in which to return the specified ECC errors
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a eccCounts has been populated
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device, \a errorType or \a counterType is invalid, or \a eccCounts is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not support this feature
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- *
- * @see nvmlDeviceClearEccErrorCounts()
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetDetailedEccErrors(nvmlDevice_t device, nvmlMemoryErrorType_t errorType, nvmlEccCounterType_t counterType, nvmlEccErrorCounts_t *eccCounts);
-
-/**
- * Retrieves the requested memory error counter for the device.
- *
- * For Tesla &tm; and Quadro &reg; products from the Fermi family.
- * Requires \a NVML_INFOROM_ECC version 2.0 or higher to report aggregate location-based memory error counts.
- * Requires \a NVML_INFOROM_ECC version 1.0 or higher to report all other memory error counts.
- *
- * For all Tesla &tm; and Quadro &reg; products from the Kepler family.
- *
- * Requires ECC Mode to be enabled.
- *
- * See \ref nvmlMemoryErrorType_t for a description of available memory error types.\n
- * See \ref nvmlEccCounterType_t for a description of available counter types.\n
- * See \ref nvmlMemoryLocation_t for a description of available counter locations.\n
- * 
- * @param device                               The identifier of the target device
- * @param errorType                            Flag that specifies the type of error.
- * @param counterType                          Flag that specifies the counter-type of the errors. 
- * @param locationType                         Specifies the location of the counter. 
- * @param count                                Reference in which to return the ECC counter
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a count has been populated
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device, \a bitTyp,e \a counterType or \a locationType is
- *                                             invalid, or \a count is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not support ECC error reporting in the specified memory
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetMemoryErrorCounter(nvmlDevice_t device, nvmlMemoryErrorType_t errorType,
-                                                   nvmlEccCounterType_t counterType,
-                                                   nvmlMemoryLocation_t locationType, unsigned long long *count);
-
-/**
- * Retrieves the current utilization rates for the device's major subsystems.
- *
- * For Tesla &tm; and Quadro &reg; products from the Fermi and Kepler families.
- *
- * See \ref nvmlUtilization_t for details on available utilization rates.
- *
- * \note During driver initialization when ECC is enabled one can see high GPU and Memory Utilization readings.
- *       This is caused by ECC Memory Scrubbing mechanism that is performed during driver initialization.
- *
- * @param device                               The identifier of the target device
- * @param utilization                          Reference in which to return the utilization information
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a utilization has been populated
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a utilization is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not support this feature
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetUtilizationRates(nvmlDevice_t device, nvmlUtilization_t *utilization);
-
-/**
- * Retrieves the current and pending driver model for the device.
- *
- * For Tesla &tm; and Quadro &reg; products from the Fermi and Kepler families.
- * For windows only.
- *
- * On Windows platforms the device driver can run in either WDDM or WDM (TCC) mode. If a display is attached
- * to the device it must run in WDDM mode. TCC mode is preferred if a display is not attached.
- *
- * See \ref nvmlDriverModel_t for details on available driver models.
- *
- * @param device                               The identifier of the target device
- * @param current                              Reference in which to return the current driver model
- * @param pending                              Reference in which to return the pending driver model
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if either \a current and/or \a pending have been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or both \a current and \a pending are NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the platform is not windows
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- * 
- * @see nvmlDeviceSetDriverModel()
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetDriverModel(nvmlDevice_t device, nvmlDriverModel_t *current, nvmlDriverModel_t *pending);
-
-/**
- * Get VBIOS version of the device.
- *
- * For all products.
- *
- * The VBIOS version may change from time to time. It will not exceed 32 characters in length 
- * (including the NULL terminator).  See \ref nvmlConstants::NVML_DEVICE_VBIOS_VERSION_BUFFER_SIZE.
- *
- * @param device                               The identifier of the target device
- * @param version                              Reference to which to return the VBIOS version
- * @param length                               The maximum allowed length of the string returned in \a version
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a version has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid, or \a version is NULL
- *         - \ref NVML_ERROR_INSUFFICIENT_SIZE if \a length is too small 
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetVbiosVersion(nvmlDevice_t device, char *version, unsigned int length);
-
-/**
- * Get Bridge Chip Information for all the bridge chips on the board.
- * 
- * For all fully supported multi-GPU products
- * 
- * @param device                                The identifier of the target device
- * @param bridgeHierarchy                       Reference to the returned bridge chip Hierarchy
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if bridge chip exists
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid, or \a bridgeInfo is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if bridge chip not supported on the device
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- * 
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetBridgeChipInfo(nvmlDevice_t device, nvmlBridgeChipHierarchy_t *bridgeHierarchy);
-
-/**
- * Get information about processes with a compute context on a device
- *
- * For Tesla &tm; and Quadro &reg; products from the Fermi and Kepler families.
- *
- * This function returns information only about compute running processes (e.g. CUDA application which have
- * active context). Any graphics applications (e.g. using OpenGL, DirectX) won't be listed by this function.
- *
- * To query the current number of running compute processes, call this function with *infoCount = 0. The
- * return code will be NVML_ERROR_INSUFFICIENT_SIZE, or NVML_SUCCESS if none are running. For this call
- * \a infos is allowed to be NULL.
- *
- * Keep in mind that information returned by this call is dynamic and the number of elements might change in
- * time. Allocate more space for \a infos table in case new compute processes are spawned.
- *
- * @param device                               The identifier of the target device
- * @param infoCount                            Reference in which to provide the \a infos array size, and
- *                                             to return the number of returned elements
- * @param infos                                Reference in which to return the process information
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a infoCount and \a infos have been populated
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INSUFFICIENT_SIZE if \a infoCount indicates that the \a infos array is too small
- *                                             \a infoCount will contain minimal amount of space necessary for
- *                                             the call to complete
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid, either of \a infoCount or \a infos is NULL
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- *
- * @see \ref nvmlSystemGetProcessName
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetComputeRunningProcesses(nvmlDevice_t device, unsigned int *infoCount, nvmlProcessInfo_t *infos);
-
-/**
- * Check if the GPU devices are on the same physical board.
- *
- * @param device1                               The first GPU device
- * @param device2                               The second GPU device
- * @param onSameBoard                           Reference in which to return the status.
- *                                              Non-zero indicates that the GPUs are on the same board.
- *
- * @return
- *         - \ref NVML_SUCCESS                 if \a onSameBoard has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a dev1 or \a dev2 are invalid or \a onSameBoard is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if this check is not supported by the device
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the either GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlDeviceOnSameBoard(nvmlDevice_t device1, nvmlDevice_t device2, int *onSameBoard);
-
-/**
- * Retrieves the root/admin permissions on the target API. See \a nvmlRestrictedAPI_t for the list of supported APIs.
- * If an API is restricted only root users can call that API. See \a nvmlDeviceGetAPIRestriction to change current permissions.
- *
- * For Tesla and Quadro &tm products from the Kepler+ family.
- *
- * @param device                               The identifier of the target device
- * @param apiType                              Target API type for this operation
- * @param isRestricted                         Reference in which to return the current restriction 
- *                                             NVML_FEATURE_ENABLED indicates that the API is root-only
- *                                             NVML_FEATURE_DISABLED indicates that the API is accessible to all users
- *
- * @return
- *         - \ref NVML_SUCCESS                 if \a isRestricted has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid, \a apiType incorrect or \a isRestricted is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if this query is not supported by the device
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- *
- * @see nvmlRestrictedAPI_t
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetAPIRestriction(nvmlDevice_t device, nvmlRestrictedAPI_t apiType, nvmlEnableState_t *isRestricted);
-
-
-/**
- * Gets Total, Available and Used size of BAR1 memory.
- * 
- * BAR1 is used to map the FB (device memory) so that it can be directly accessed by the CPU or by 3rd party 
- * devices (peer-to-peer on the PCIE bus). 
- * 
- * For Tesla and Quadro &tm products from the Kepler+ family.
- *
- * @param device                               The identifier of the target device
- * @param bar1Memory                           Reference in which BAR1 memory
- *                                             information is returned.
- *
- * @return
- *         - \ref NVML_SUCCESS                 if BAR1 memory is successfully retrieved
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid, \a bar1Memory is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if this query is not supported by the device
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- *
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetBAR1MemoryInfo(nvmlDevice_t device, nvmlBAR1Memory_t *bar1Memory);
-
-/**
- * @}
- */
-
-/** @addtogroup nvmlAccountingStats
- *  @{
- */
-
-/**
- * Queries the state of per process accounting mode.
- *
- * For Tesla &tm; and Quadro &reg; products from the Kepler family.
- *
- * See \ref nvmlDeviceGetAccountingStats for more details.
- * See \ref nvmlDeviceSetAccountingMode
- *
- * @param device                               The identifier of the target device
- * @param mode                                 Reference in which to return the current accounting mode
- *
- * @return 
- *         - \ref NVML_SUCCESS                 if the mode has been successfully retrieved 
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a mode are NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device doesn't support this feature
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetAccountingMode(nvmlDevice_t device, nvmlEnableState_t *mode);
-
-/**
- * Queries process's accounting stats.
- *
- * For Tesla &tm; and Quadro &reg; products from the Kepler family.
- * 
- * Accounting stats capture GPU utilization and other statistics across the lifetime of a process.
- * Accounting stats can be queried during life time of the process and after its termination.
- * Accounting stats are kept in a circular buffer, newly created processes overwrite information about old
- * processes.
- *
- * See \ref nvmlAccountingStats_t for description of each returned metric.
- * List of processes that can be queried can be retrieved from \ref nvmlDeviceGetAccountingPids.
- *
- * @note Accounting Mode needs to be on. See \ref nvmlDeviceGetAccountingMode.
- * @note Only compute and graphics applications stats can be queried. Monitoring applications stats can't be
- *         queried since they don't contribute to GPU utilization.
- * @note In case of pid collision stats of only the latest process (that terminated last) will be reported
- *
- * @warning On Kepler devices per process statistics are accurate only if there's one process running on a GPU.
- * 
- * @param device                               The identifier of the target device
- * @param pid                                  Process Id of the target process to query stats for
- * @param stats                                Reference in which to return the process's accounting stats
- *
- * @return 
- *         - \ref NVML_SUCCESS                 if stats have been successfully retrieved
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a stats are NULL
- *         - \ref NVML_ERROR_NOT_FOUND         if process stats were not found
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device doesn't support this feature or accounting mode is disabled
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- *
- * @see nvmlDeviceGetAccountingBufferSize
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetAccountingStats(nvmlDevice_t device, unsigned int pid, nvmlAccountingStats_t *stats);
-
-/**
- * Queries list of processes that can be queried for accounting stats.
- *
- * For Tesla &tm; and Quadro &reg; products from the Kepler family.
- *
- * To just query the number of processes ready to be queried, call this function with *count = 0 and
- * pids=NULL. The return code will be NVML_ERROR_INSUFFICIENT_SIZE, or NVML_SUCCESS if list is empty.
- * 
- * For more details see \ref nvmlDeviceGetAccountingStats.
- *
- * @note In case of PID collision some processes might not be accessible before the circular buffer is full.
- *
- * @param device                               The identifier of the target device
- * @param count                                Reference in which to provide the \a pids array size, and
- *                                               to return the number of elements ready to be queried
- * @param pids                                 Reference in which to return list of process ids
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if pids were successfully retrieved
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a count is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device doesn't support this feature or accounting mode is disabled
- *         - \ref NVML_ERROR_INSUFFICIENT_SIZE if \a count is too small (\a count is set to
- *                                                 expected value)
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- *
- * @see nvmlDeviceGetAccountingBufferSize
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetAccountingPids(nvmlDevice_t device, unsigned int *count, unsigned int *pids);
-
-/**
- * Returns the number of processes that the circular buffer with accounting pids can hold.
- *
- * For Tesla &tm; and Quadro &reg; products from the Kepler family.
- *
- * This is the maximum number of processes that accounting information will be stored for before information
- * about oldest processes will get overwritten by information about new processes.
- *
- * @param device                               The identifier of the target device
- * @param bufferSize                           Reference in which to provide the size (in number of elements)
- *                                               of the circular buffer for accounting stats.
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if buffer size was successfully retrieved
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a bufferSize is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device doesn't support this feature or accounting mode is disabled
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- * 
- * @see nvmlDeviceGetAccountingStats
- * @see nvmlDeviceGetAccountingPids
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetAccountingBufferSize(nvmlDevice_t device, unsigned int *bufferSize);
-
-/** @} */
-
-/** @addtogroup nvmlDeviceQueries
- *  @{
- */
-
-/**
- * Returns the list of retired pages by source, including pages that are pending retirement
- * The address information provided from this API is the hardware address of the page that was retired.  Note
- * that this does not match the virtual address used in CUDA, but will match the address information in XID 63
- * 
- * For Tesla &tm; K20 products
- *
- * @param device                            The identifier of the target device
- * @param cause                             Filter page addresses by cause of retirement
- * @param pageCount                         Reference in which to provide the \a addresses buffer size, and
- *                                          to return the number of retired pages that match \a cause
- *                                          Set to 0 to query the size without allocating an \a addresses buffer
- * @param addresses                         Buffer to write the page addresses into
- * 
- * @return
- *         - \ref NVML_SUCCESS                 if \a pageCount was populated and \a addresses was filled
- *         - \ref NVML_ERROR_INSUFFICIENT_SIZE if \a pageCount indicates the buffer is not large enough to store all the
- *                                             matching page addresses.  \a pageCount is set to the needed size.
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid, \a pageCount is NULL, \a cause is invalid, or 
- *                                             \a addresses is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device doesn't support this feature
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetRetiredPages(nvmlDevice_t device, nvmlPageRetirementCause_t cause,
-    unsigned int *pageCount, unsigned long long *addresses);
-
-/**
- * Check if any pages are pending retirement and need a reboot to fully retire.
- *
- * For Tesla &tm; K20 products
- *
- * @param device                            The identifier of the target device
- * @param isPending                         Reference in which to return the pending status
- * 
- * @return
- *         - \ref NVML_SUCCESS                 if \a isPending was populated
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a isPending is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device doesn't support this feature
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetRetiredPagesPendingStatus(nvmlDevice_t device, nvmlEnableState_t *isPending);
-
-/** @} */
-
-/***************************************************************************************************/
-/** @defgroup nvmlUnitCommands Unit Commands
- *  This chapter describes NVML operations that change the state of the unit. For S-class products.
- *  Each of these requires root/admin access. Non-admin users will see an NVML_ERROR_NO_PERMISSION
- *  error code when invoking any of these methods.
- *  @{
- */
-/***************************************************************************************************/
-
-/**
- * Set the LED state for the unit. The LED can be either green (0) or amber (1).
- *
- * For S-class products.
- * Requires root/admin permissions.
- *
- * This operation takes effect immediately.
- * 
- *
- * <b>Current S-Class products don't provide unique LEDs for each unit. As such, both front 
- * and back LEDs will be toggled in unison regardless of which unit is specified with this command.</b>
- *
- * See \ref nvmlLedColor_t for available colors.
- *
- * @param unit                                 The identifier of the target unit
- * @param color                                The target LED color
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if the LED color has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a unit or \a color is invalid
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if this is not an S-class product
- *         - \ref NVML_ERROR_NO_PERMISSION     if the user doesn't have permission to perform this operation
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- * 
- * @see nvmlUnitGetLedState()
- */
-nvmlReturn_t DECLDIR nvmlUnitSetLedState(nvmlUnit_t unit, nvmlLedColor_t color);
-
-/** @} */
-
-/***************************************************************************************************/
-/** @defgroup nvmlDeviceCommands Device Commands
- *  This chapter describes NVML operations that change the state of the device.
- *  Each of these requires root/admin access. Non-admin users will see an NVML_ERROR_NO_PERMISSION
- *  error code when invoking any of these methods.
- *  @{
- */
-/***************************************************************************************************/
-
-/**
- * Set the persistence mode for the device.
- *
- * For all CUDA-capable products.
- * For Linux only.
- * Requires root/admin permissions.
- *
- * The persistence mode determines whether the GPU driver software is torn down after the last client
- * exits.
- *
- * This operation takes effect immediately. It is not persistent across reboots. After each reboot the
- * persistence mode is reset to "Disabled".
- *
- * See \ref nvmlEnableState_t for available modes.
- *
- * @param device                               The identifier of the target device
- * @param mode                                 The target persistence mode
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if the persistence mode was set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a mode is invalid
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not support this feature
- *         - \ref NVML_ERROR_NO_PERMISSION     if the user doesn't have permission to perform this operation
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- *
- * @see nvmlDeviceGetPersistenceMode()
- */
-nvmlReturn_t DECLDIR nvmlDeviceSetPersistenceMode(nvmlDevice_t device, nvmlEnableState_t mode);
-
-/**
- * Set the compute mode for the device.
- *
- * For all CUDA-capable products.
- * Requires root/admin permissions.
- *
- * The compute mode determines whether a GPU can be used for compute operations and whether it can
- * be shared across contexts.
- *
- * This operation takes effect immediately. Under Linux it is not persistent across reboots and
- * always resets to "Default". Under windows it is persistent.
- *
- * Under windows compute mode may only be set to DEFAULT when running in WDDM
- *
- * See \ref nvmlComputeMode_t for details on available compute modes.
- *
- * @param device                               The identifier of the target device
- * @param mode                                 The target compute mode
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if the compute mode was set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a mode is invalid
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not support this feature
- *         - \ref NVML_ERROR_NO_PERMISSION     if the user doesn't have permission to perform this operation
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- *
- * @see nvmlDeviceGetComputeMode()
- */
-nvmlReturn_t DECLDIR nvmlDeviceSetComputeMode(nvmlDevice_t device, nvmlComputeMode_t mode);
-
-/**
- * Set the ECC mode for the device.
- *
- * For Tesla &tm; and Quadro &reg; products from the Fermi and Kepler families.
- * Requires \a NVML_INFOROM_ECC version 1.0 or higher.
- * Requires root/admin permissions.
- *
- * The ECC mode determines whether the GPU enables its ECC support.
- *
- * This operation takes effect after the next reboot.
- *
- * See \ref nvmlEnableState_t for details on available modes.
- *
- * @param device                               The identifier of the target device
- * @param ecc                                  The target ECC mode
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if the ECC mode was set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a ecc is invalid
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not support this feature
- *         - \ref NVML_ERROR_NO_PERMISSION     if the user doesn't have permission to perform this operation
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- *
- * @see nvmlDeviceGetEccMode()
- */
-nvmlReturn_t DECLDIR nvmlDeviceSetEccMode(nvmlDevice_t device, nvmlEnableState_t ecc);  
-
-/**
- * Clear the ECC error and other memory error counts for the device.
- *
- * For Tesla &tm; and Quadro &reg; products from the Fermi and Kepler families.
- * Requires \a NVML_INFOROM_ECC version 2.0 or higher to clear aggregate location-based ECC counts.
- * Requires \a NVML_INFOROM_ECC version 1.0 or higher to clear all other ECC counts.
- * Requires root/admin permissions.
- * Requires ECC Mode to be enabled.
- *
- * Sets all of the specified ECC counters to 0, including both detailed and total counts.
- *
- * This operation takes effect immediately.
- *
- * See \ref nvmlMemoryErrorType_t for details on available counter types.
- *
- * @param device                               The identifier of the target device
- * @param counterType                          Flag that indicates which type of errors should be cleared.
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if the error counts were cleared
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a counterType is invalid
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not support this feature
- *         - \ref NVML_ERROR_NO_PERMISSION     if the user doesn't have permission to perform this operation
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- *
- * @see 
- *      - nvmlDeviceGetDetailedEccErrors()
- *      - nvmlDeviceGetTotalEccErrors()
- */
-nvmlReturn_t DECLDIR nvmlDeviceClearEccErrorCounts(nvmlDevice_t device, nvmlEccCounterType_t counterType);
-
-/**
- * Set the driver model for the device.
- *
- * For Tesla &tm; and Quadro &reg; products from the Fermi and Kepler families.
- * For windows only.
- * Requires root/admin permissions.
- *
- * On Windows platforms the device driver can run in either WDDM or WDM (TCC) mode. If a display is attached
- * to the device it must run in WDDM mode.  
- *
- * It is possible to force the change to WDM (TCC) while the display is still attached with a force flag (nvmlFlagForce).
- * This should only be done if the host is subsequently powered down and the display is detached from the device
- * before the next reboot. 
- *
- * This operation takes effect after the next reboot.
- * 
- * Windows driver model may only be set to WDDM when running in DEFAULT compute mode.
- *
- * Change driver model to WDDM is not supported when GPU doesn't support graphics acceleration or 
- * will not support it after reboot. See \ref nvmlDeviceSetGpuOperationMode.
- *
- * See \ref nvmlDriverModel_t for details on available driver models.
- * See \ref nvmlFlagDefault and \ref nvmlFlagForce
- *
- * @param device                               The identifier of the target device
- * @param driverModel                          The target driver model
- * @param flags                                Flags that change the default behavior
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if the driver model has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a driverModel is invalid
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the platform is not windows or the device does not support this feature
- *         - \ref NVML_ERROR_NO_PERMISSION     if the user doesn't have permission to perform this operation
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- * 
- * @see nvmlDeviceGetDriverModel()
- */
-nvmlReturn_t DECLDIR nvmlDeviceSetDriverModel(nvmlDevice_t device, nvmlDriverModel_t driverModel, unsigned int flags);
-
-/**
- * Set clocks that applications will lock to.
- *
- * Sets the clocks that compute and graphics applications will be running at.
- * e.g. CUDA driver requests these clocks during context creation which means this property 
- * defines clocks at which CUDA applications will be running unless some overspec event
- * occurs (e.g. over power, over thermal or external HW brake).
- *
- * Can be used as a setting to request constant performance.
- *
- * For Tesla &tm; products from the Kepler family.
- * Requires root/admin permissions. 
- *
- * See \ref nvmlDeviceGetSupportedMemoryClocks and \ref nvmlDeviceGetSupportedGraphicsClocks 
- * for details on how to list available clocks combinations.
- *
- * After system reboot or driver reload applications clocks go back to their default value.
- * See \ref nvmlDeviceResetApplicationsClocks.
- *
- * @param device                               The identifier of the target device
- * @param memClockMHz                          Requested memory clock in MHz
- * @param graphicsClockMHz                     Requested graphics clock in MHz
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if new settings were successfully set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a memClockMHz and \a graphicsClockMHz 
- *                                                 is not a valid clock combination
- *         - \ref NVML_ERROR_NO_PERMISSION     if the user doesn't have permission to perform this operation 
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device doesn't support this feature
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlDeviceSetApplicationsClocks(nvmlDevice_t device, unsigned int memClockMHz, unsigned int graphicsClockMHz);
-
-/**
- * Set new power limit of this device.
- * 
- * For Tesla &tm; and Quadro &reg; products from the Kepler family.
- * Requires root/admin permissions.
- *
- * See \ref nvmlDeviceGetPowerManagementLimitConstraints to check the allowed ranges of values.
- *
- * \note Limit is not persistent across reboots or driver unloads.
- * Enable persistent mode to prevent driver from unloading when no application is using the device.
- *
- * @param device                               The identifier of the target device
- * @param limit                                Power management limit in milliwatts to set
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a limit has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a defaultLimit is out of range
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not support this feature
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- *
- * @see nvmlDeviceGetPowerManagementLimitConstraints
- * @see nvmlDeviceGetPowerManagementDefaultLimit
- */
-nvmlReturn_t DECLDIR nvmlDeviceSetPowerManagementLimit(nvmlDevice_t device, unsigned int limit);
-
-/**
- * Sets new GOM. See \a nvmlGpuOperationMode_t for details.
- *
- * For GK110 M-class and X-class Tesla &tm; products from the Kepler family.
- * Not supported on Quadro &reg; and Tesla &tm; C-class products.
- * Requires root/admin permissions.
- * 
- * Changing GOMs requires a reboot. 
- * The reboot requirement might be removed in the future.
- *
- * Compute only GOMs don't support graphics acceleration. Under windows switching to these GOMs when
- * pending driver model is WDDM is not supported. See \ref nvmlDeviceSetDriverModel.
- * 
- * @param device                               The identifier of the target device
- * @param mode                                 Target GOM
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if \a mode has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a mode incorrect
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not support GOM or specific mode
- *         - \ref NVML_ERROR_NO_PERMISSION     if the user doesn't have permission to perform this operation
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- *
- * @see nvmlGpuOperationMode_t
- * @see nvmlDeviceGetGpuOperationMode
- */
-nvmlReturn_t DECLDIR nvmlDeviceSetGpuOperationMode(nvmlDevice_t device, nvmlGpuOperationMode_t mode);
-
-/**
- * Changes the root/admin restructions on certain APIs. See \a nvmlRestrictedAPI_t for the list of supported APIs.
- * This method can be used by a root/admin user to give non-root/admin access to certain otherwise-restricted APIs.
- * The new setting lasts for the lifetime of the NVIDIA driver; it is not persistent. See \a nvmlDeviceGetAPIRestriction
- * to query the current restriction settings.
- * 
- * For Tesla and Quadro &tm products from the Kepler+ family.
- * Requires root/admin permissions.
- *
- * @param device                               The identifier of the target device
- * @param apiType                              Target API type for this operation
- * @param isRestricted                         The target restriction
- *
- * @return
- *         - \ref NVML_SUCCESS                 if \a isRestricted has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device is invalid or \a apiType incorrect
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device does not support changing API restrictions
- *         - \ref NVML_ERROR_NO_PERMISSION     if the user doesn't have permission to perform this operation
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- *
- * @see nvmlRestrictedAPI_t
- */
-nvmlReturn_t DECLDIR nvmlDeviceSetAPIRestriction(nvmlDevice_t device, nvmlRestrictedAPI_t apiType, nvmlEnableState_t isRestricted);
-
-/**
- * @}
- */
- 
-/** @addtogroup nvmlAccountingStats
- *  @{
- */
-
-/**
- * Enables or disables per process accounting.
- *
- * For Tesla &tm; and Quadro &reg; products from the Kepler family.
- * Requires root/admin permissions.
- *
- * @note This setting is not persistent and will default to disabled after driver unloads.
- *       Enable persistence mode to be sure the setting doesn't switch off to disabled.
- * 
- * @note Enabling accounting mode has no negative impact on the GPU performance.
- *
- * @note Disabling accounting clears all accounting pids information.
- *
- * See \ref nvmlDeviceGetAccountingMode
- * See \ref nvmlDeviceGetAccountingStats
- * See \ref nvmlDeviceClearAccountingPids
- *
- * @param device                               The identifier of the target device
- * @param mode                                 The target accounting mode
- *
- * @return 
- *         - \ref NVML_SUCCESS                 if the new mode has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device or \a mode are invalid
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device doesn't support this feature
- *         - \ref NVML_ERROR_NO_PERMISSION     if the user doesn't have permission to perform this operation
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlDeviceSetAccountingMode(nvmlDevice_t device, nvmlEnableState_t mode);
-
-/**
- * Clears accounting information about all processes that have already terminated.
- *
- * For Tesla &tm; and Quadro &reg; products from the Kepler family.
- * Requires root/admin permissions.
- *
- * See \ref nvmlDeviceGetAccountingMode
- * See \ref nvmlDeviceGetAccountingStats
- * See \ref nvmlDeviceSetAccountingMode
- *
- * @param device                               The identifier of the target device
- *
- * @return 
- *         - \ref NVML_SUCCESS                 if accounting information has been cleared 
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a device are invalid
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the device doesn't support this feature
- *         - \ref NVML_ERROR_NO_PERMISSION     if the user doesn't have permission to perform this operation
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- */
-nvmlReturn_t DECLDIR nvmlDeviceClearAccountingPids(nvmlDevice_t device);
-
-/** @} */
-
-/***************************************************************************************************/
-/** @defgroup nvmlEvents Event Handling Methods
- * This chapter describes methods that NVML can perform against each device to register and wait for 
- * some event to occur.
- *  @{
- */
-/***************************************************************************************************/
-
-/**
- * Create an empty set of events.
- * Event set should be freed by \ref nvmlEventSetFree
- *
- * @param set                                  Reference in which to return the event handle
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if the event has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a set is NULL
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- * 
- * @see nvmlEventSetFree
- */
-nvmlReturn_t DECLDIR nvmlEventSetCreate(nvmlEventSet_t *set);
-
-/**
- * Starts recording of events on a specified devices and add the events to specified \ref nvmlEventSet_t
- *
- * For Tesla &tm; and Quadro &reg; products from the Fermi and Kepler families.
- * Ecc events are available only on ECC enabled devices (see \ref nvmlDeviceGetTotalEccErrors)
- * Power capping events are available only on Power Management enabled devices (see \ref nvmlDeviceGetPowerManagementMode)
- *
- * For Linux only.
- *
- * \b IMPORTANT: Operations on \a set are not thread safe
- *
- * This call starts recording of events on specific device.
- * All events that occurred before this call are not recorded.
- * Checking if some event occurred can be done with \ref nvmlEventSetWait
- *
- * If function reports NVML_ERROR_UNKNOWN, event set is in undefined state and should be freed.
- * If function reports NVML_ERROR_NOT_SUPPORTED, event set can still be used. None of the requested eventTypes
- *     are registered in that case.
- *
- * @param device                               The identifier of the target device
- * @param eventTypes                           Bitmask of \ref nvmlEventType to record
- * @param set                                  Set to which add new event types
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if the event has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a eventTypes is invalid or \a set is NULL
- *         - \ref NVML_ERROR_NOT_SUPPORTED     if the platform does not support this feature or some of requested event types
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- * 
- * @see nvmlEventType
- * @see nvmlDeviceGetSupportedEventTypes
- * @see nvmlEventSetWait
- * @see nvmlEventSetFree
- */
-nvmlReturn_t DECLDIR nvmlDeviceRegisterEvents(nvmlDevice_t device, unsigned long long eventTypes, nvmlEventSet_t set);
-
-/**
- * Returns information about events supported on device
- *
- * For all products.
- *
- * Events are not supported on Windows. So this function returns an empty mask in \a eventTypes on Windows.
- *
- * @param device                               The identifier of the target device
- * @param eventTypes                           Reference in which to return bitmask of supported events
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if the eventTypes has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a eventType is NULL
- *         - \ref NVML_ERROR_GPU_IS_LOST       if the target GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- * 
- * @see nvmlEventType
- * @see nvmlDeviceRegisterEvents
- */
-nvmlReturn_t DECLDIR nvmlDeviceGetSupportedEventTypes(nvmlDevice_t device, unsigned long long *eventTypes);
-
-/**
- * Waits on events and delivers events
- *
- * For Tesla &tm; and Quadro &reg; products from the Fermi and Kepler families.
- *
- * If some events are ready to be delivered at the time of the call, function returns immediately.
- * If there are no events ready to be delivered, function sleeps till event arrives 
- * but not longer than specified timeout. This function in certain conditions can return before
- * specified timeout passes (e.g. when interrupt arrives)
- * 
- * In case of xid error, the function returns the most recent xid error type seen by the system. If there are multiple
- * xid errors generated before nvmlEventSetWait is invoked then the last seen xid error type is returned for all
- * xid error events.
- * 
- * @param set                                  Reference to set of events to wait on
- * @param data                                 Reference in which to return event data
- * @param timeoutms                            Maximum amount of wait time in milliseconds for registered event
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if the data has been set
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_INVALID_ARGUMENT  if \a data is NULL
- *         - \ref NVML_ERROR_TIMEOUT           if no event arrived in specified timeout or interrupt arrived
- *         - \ref NVML_ERROR_GPU_IS_LOST       if a GPU has fallen off the bus or is otherwise inaccessible
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- * 
- * @see nvmlEventType
- * @see nvmlDeviceRegisterEvents
- */
-nvmlReturn_t DECLDIR nvmlEventSetWait(nvmlEventSet_t set, nvmlEventData_t * data, unsigned int timeoutms);
-
-/**
- * Releases events in the set
- *
- * For Tesla &tm; and Quadro &reg; products from the Fermi and Kepler families.
- *
- * @param set                                  Reference to events to be released 
- * 
- * @return 
- *         - \ref NVML_SUCCESS                 if the event has been successfully released
- *         - \ref NVML_ERROR_UNINITIALIZED     if the library has not been successfully initialized
- *         - \ref NVML_ERROR_UNKNOWN           on any unexpected error
- * 
- * @see nvmlDeviceRegisterEvents
- */
-nvmlReturn_t DECLDIR nvmlEventSetFree(nvmlEventSet_t set);
-
-/** @} */
-
-/**
- * NVML API versioning support
- */
-#if defined(__NVML_API_VERSION_INTERNAL)
-#undef nvmlDeviceGetPciInfo
-#undef nvmlDeviceGetCount
-#undef nvmlDeviceGetHandleByIndex
-#undef nvmlDeviceGetHandleByPciBusId
-#undef nvmlInit
-#endif
-
-#ifdef __cplusplus
-}
-#endif
-
-#endif

From 8241c5b2edddb8f86ad69b860612d6af0c8fb906 Mon Sep 17 00:00:00 2001
From: Frank Seide <fseide@microsoft.com>
Date: Mon, 18 May 2015 22:04:54 -0700
Subject: [PATCH 33/49] changed the Linux and Documentation Visual Studio
 "Projects" to Solution Folders (which they should have been all along)

---
 CNTK.sln                                    | 412 ++++++++++++--------
 Documentation/Documentation.vcxproj         | 117 ------
 Documentation/Documentation.vcxproj.filters | 159 --------
 Linux/Linux.vcxproj                         |  76 ----
 Linux/Linux.vcxproj.filters                 |  10 -
 5 files changed, 244 insertions(+), 530 deletions(-)
 delete mode 100644 Documentation/Documentation.vcxproj
 delete mode 100644 Documentation/Documentation.vcxproj.filters
 delete mode 100644 Linux/Linux.vcxproj
 delete mode 100644 Linux/Linux.vcxproj.filters

diff --git a/CNTK.sln b/CNTK.sln
index 0d4780cd0..8fbbf9482 100644
--- a/CNTK.sln
+++ b/CNTK.sln
@@ -1,168 +1,244 @@
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deleted file mode 100644
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@@ -1,159 +0,0 @@
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From 87a504dd6c709b3c377501eb2d5b5dec817628c2 Mon Sep 17 00:00:00 2001
From: Frank Seide <fseide@microsoft.com>
Date: Mon, 18 May 2015 22:28:28 -0700
Subject: [PATCH 34/49] renamed -Node.h to -Nodes.h since that's what they
 represent--collections of node types

---
 MachineLearning/CNTK/CNTK.vcxproj              |  6 +++---
 MachineLearning/CNTK/CNTK.vcxproj.filters      | 18 +++++++++---------
 ...ationNode.h => CompositeComputationNodes.h} |  4 ++--
 MachineLearning/CNTK/ComputationNetwork.h      |  6 +++---
 MachineLearning/CNTK/ComputationNode.cpp       |  8 ++++----
 ...terionNode.h => EvaluationCriterionNodes.h} |  2 +-
 .../CNTK/NetworkDescriptionLanguage.h          |  6 +++---
 ...riterionNode.h => TrainingCriterionNodes.h} |  2 +-
 8 files changed, 26 insertions(+), 26 deletions(-)
 rename MachineLearning/CNTK/{CompositeComputationNode.h => CompositeComputationNodes.h} (99%)
 rename MachineLearning/CNTK/{EvaluationCriterionNode.h => EvaluationCriterionNodes.h} (99%)
 rename MachineLearning/CNTK/{TrainingCriterionNode.h => TrainingCriterionNodes.h} (97%)

diff --git a/MachineLearning/CNTK/CNTK.vcxproj b/MachineLearning/CNTK/CNTK.vcxproj
index 7f7ca8291..27d277457 100644
--- a/MachineLearning/CNTK/CNTK.vcxproj
+++ b/MachineLearning/CNTK/CNTK.vcxproj
@@ -163,11 +163,11 @@
     <ClInclude Include="..\..\Common\Include\minibatchsourcehelpers.h" />
     <ClInclude Include="..\..\Common\Include\nvml.h" />
     <ClInclude Include="..\..\Common\Include\TimerUtility.h" />
-    <ClInclude Include="CompositeComputationNode.h" />
+    <ClInclude Include="CompositeComputationNodes.h" />
     <ClInclude Include="ComputationNetwork.h" />
     <ClInclude Include="ComputationNetworkHelper.h" />
     <ClInclude Include="ComputationNode.h" />
-    <ClInclude Include="EvaluationCriterionNode.h" />
+    <ClInclude Include="EvaluationCriterionNodes.h" />
     <ClInclude Include="IComputationNetBuilder.h" />
     <ClInclude Include="IExecutionEngine.h" />
     <ClInclude Include="ModelEditLanguage.h" />
@@ -181,7 +181,7 @@
     <ClInclude Include="stdafx.h" />
     <ClInclude Include="SynchronousExecutionEngine.h" />
     <ClInclude Include="targetver.h" />
-    <ClInclude Include="TrainingCriterionNode.h" />
+    <ClInclude Include="TrainingCriterionNodes.h" />
   </ItemGroup>
   <ItemGroup>
     <ClCompile Include="..\..\Common\BestGpu.cpp" />
diff --git a/MachineLearning/CNTK/CNTK.vcxproj.filters b/MachineLearning/CNTK/CNTK.vcxproj.filters
index b0bce29ee..882ad557d 100644
--- a/MachineLearning/CNTK/CNTK.vcxproj.filters
+++ b/MachineLearning/CNTK/CNTK.vcxproj.filters
@@ -76,15 +76,9 @@
     <ClInclude Include="ModelEditLanguage.h">
       <Filter>Model Editing</Filter>
     </ClInclude>
-    <ClInclude Include="CompositeComputationNode.h">
-      <Filter>Nodes</Filter>
-    </ClInclude>
     <ClInclude Include="ComputationNode.h">
       <Filter>Nodes</Filter>
     </ClInclude>
-    <ClInclude Include="EvaluationCriterionNode.h">
-      <Filter>Nodes</Filter>
-    </ClInclude>
     <ClInclude Include="NDLNetworkBuilder.h">
       <Filter>Network</Filter>
     </ClInclude>
@@ -109,9 +103,6 @@
     <ClInclude Include="SynchronousExecutionEngine.h">
       <Filter>Execution Engine</Filter>
     </ClInclude>
-    <ClInclude Include="TrainingCriterionNode.h">
-      <Filter>Nodes</Filter>
-    </ClInclude>
     <ClInclude Include="stdafx.h">
       <Filter>Misc</Filter>
     </ClInclude>
@@ -136,6 +127,15 @@
     <ClInclude Include="..\..\Common\Include\BestGpu.h">
       <Filter>Common\Include</Filter>
     </ClInclude>
+    <ClInclude Include="CompositeComputationNodes.h">
+      <Filter>Nodes</Filter>
+    </ClInclude>
+    <ClInclude Include="EvaluationCriterionNodes.h">
+      <Filter>Nodes</Filter>
+    </ClInclude>
+    <ClInclude Include="TrainingCriterionNodes.h">
+      <Filter>Nodes</Filter>
+    </ClInclude>
   </ItemGroup>
   <ItemGroup>
     <Text Include="modelEditor.txt">
diff --git a/MachineLearning/CNTK/CompositeComputationNode.h b/MachineLearning/CNTK/CompositeComputationNodes.h
similarity index 99%
rename from MachineLearning/CNTK/CompositeComputationNode.h
rename to MachineLearning/CNTK/CompositeComputationNodes.h
index 7ebc83777..34b6e08e4 100644
--- a/MachineLearning/CNTK/CompositeComputationNode.h
+++ b/MachineLearning/CNTK/CompositeComputationNodes.h
@@ -1,5 +1,5 @@
 //
-// <copyright file="CompositeComputationNode.h" company="Microsoft">
+// <copyright file="CompositeComputationNodes.h" company="Microsoft">
 //     Copyright (c) Microsoft Corporation.  All rights reserved.
 // </copyright>
 //
@@ -12,7 +12,7 @@
 #include <stdexcept>
 #include <list>
 #include "ComputationNode.h"
-#include "TrainingCriterionNode.h"
+#include "TrainingCriterionNodes.h"
 #include <iostream> 
 
 #define TWO_PI 6.283185307f
diff --git a/MachineLearning/CNTK/ComputationNetwork.h b/MachineLearning/CNTK/ComputationNetwork.h
index e99983612..9e20f9065 100644
--- a/MachineLearning/CNTK/ComputationNetwork.h
+++ b/MachineLearning/CNTK/ComputationNetwork.h
@@ -18,9 +18,9 @@
 #include <sstream>
 #include <stdlib.h>
 #include "ComputationNode.h"
-#include "TrainingCriterionNode.h"
-#include "CompositeComputationNode.h"
-#include "EvaluationCriterionNode.h"
+#include "TrainingCriterionNodes.h"
+#include "CompositeComputationNodes.h"
+#include "EvaluationCriterionNodes.h"
 #include "File.h"
 #include "Matrix.h"
 #include "commandArgUtil.h"
diff --git a/MachineLearning/CNTK/ComputationNode.cpp b/MachineLearning/CNTK/ComputationNode.cpp
index df3851866..93dab5d38 100644
--- a/MachineLearning/CNTK/ComputationNode.cpp
+++ b/MachineLearning/CNTK/ComputationNode.cpp
@@ -11,14 +11,14 @@
 #include "IComputationNetBuilder.h"
 #include "SGD.h"
 
-namespace Microsoft {
-    namespace MSR {
-        namespace CNTK {
+namespace Microsoft { namespace MSR { namespace CNTK {
+
+    // instantiate the core class templates
 
     typedef Matrix<float> FloatMatrix;
     typedef Matrix<double> DoubleMatrix;
 
-    template<> atomic_ullong ComputationNode<float>::s_timeStampCounter=ATOMIC_VAR_INIT(0);
+    template<> atomic_ullong ComputationNode<float>::s_timeStampCounter = ATOMIC_VAR_INIT(0);
     template<> atomic_ullong ComputationNode<double>::s_timeStampCounter = ATOMIC_VAR_INIT(0);
 
     template<> std::map<size_t, std::map<size_t, FloatMatrix*>> ComputationNode<float>::s_constOnes{};
diff --git a/MachineLearning/CNTK/EvaluationCriterionNode.h b/MachineLearning/CNTK/EvaluationCriterionNodes.h
similarity index 99%
rename from MachineLearning/CNTK/EvaluationCriterionNode.h
rename to MachineLearning/CNTK/EvaluationCriterionNodes.h
index faa873920..ea5c99d89 100644
--- a/MachineLearning/CNTK/EvaluationCriterionNode.h
+++ b/MachineLearning/CNTK/EvaluationCriterionNodes.h
@@ -1,5 +1,5 @@
 //
-// <copyright file="EvaluationCriterionNode.h" company="Microsoft">
+// <copyright file="EvaluationCriterionNodes.h" company="Microsoft">
 //     Copyright (c) Microsoft Corporation.  All rights reserved.
 // </copyright>
 //
diff --git a/MachineLearning/CNTK/NetworkDescriptionLanguage.h b/MachineLearning/CNTK/NetworkDescriptionLanguage.h
index cf158d785..91e56b271 100644
--- a/MachineLearning/CNTK/NetworkDescriptionLanguage.h
+++ b/MachineLearning/CNTK/NetworkDescriptionLanguage.h
@@ -6,9 +6,9 @@
 #pragma once
 #include "commandArgUtil.h"
 #include "ComputationNode.h"
-#include "TrainingCriterionNode.h"
-#include "CompositeComputationNode.h"
-#include "EvaluationCriterionNode.h"
+#include "TrainingCriterionNodes.h"
+#include "CompositeComputationNodes.h"
+#include "EvaluationCriterionNodes.h"
 #include "ComputationNetwork.h"
 #include <stdarg.h>
 
diff --git a/MachineLearning/CNTK/TrainingCriterionNode.h b/MachineLearning/CNTK/TrainingCriterionNodes.h
similarity index 97%
rename from MachineLearning/CNTK/TrainingCriterionNode.h
rename to MachineLearning/CNTK/TrainingCriterionNodes.h
index 89a65152a..00fe81739 100644
--- a/MachineLearning/CNTK/TrainingCriterionNode.h
+++ b/MachineLearning/CNTK/TrainingCriterionNodes.h
@@ -1,5 +1,5 @@
 //
-// <copyright file="TrainingCriterionNode.h" company="Microsoft">
+// <copyright file="TrainingCriterionNodes.h" company="Microsoft">
 //     Copyright (c) Microsoft Corporation.  All rights reserved.
 // </copyright>
 //

From 81508e60b85f029c76e480cc2cd1b375de0fb427 Mon Sep 17 00:00:00 2001
From: Dong Yu <dongyu@microsoft.com>
Date: Tue, 19 May 2015 13:53:25 +0800
Subject: [PATCH 35/49] update CNTK-book to reflect the cn->cntk change

---
 .../CNTK-TechReport/lyx/CNTKBook-master.lyx   |     3 +-
 .../CNTK-TechReport/lyx/CNTKBook-master.pdf   | 28709 ++++++++++++++++
 .../lyx/CNTKBook_CNTK_Adv_Chapter.lyx         |   153 +-
 .../lyx/CNTKBook_CNTK_Chapter.lyx             |    25 +-
 .../lyx/CNTKBook_Introduction.lyx             |     4 +-
 5 files changed, 28801 insertions(+), 93 deletions(-)
 create mode 100644 Documentation/CNTK-TechReport/lyx/CNTKBook-master.pdf

diff --git a/Documentation/CNTK-TechReport/lyx/CNTKBook-master.lyx b/Documentation/CNTK-TechReport/lyx/CNTKBook-master.lyx
index 3b23ea12f..1e463c9b3 100644
--- a/Documentation/CNTK-TechReport/lyx/CNTKBook-master.lyx
+++ b/Documentation/CNTK-TechReport/lyx/CNTKBook-master.lyx
@@ -115,8 +115,7 @@ Jie Gao, Avner May, Baolin Peng, Andreas Stolcke, Malcolm Slaney
 \end_layout
 
 \begin_layout Date
-MSR-TR-2014-112 (DRAFT v0.7: March.
- 19, 2015)
+MSR-TR-2014-112 (DRAFT v0.8: May 19, 2015)
 \end_layout
 
 \begin_layout Standard
diff --git a/Documentation/CNTK-TechReport/lyx/CNTKBook-master.pdf b/Documentation/CNTK-TechReport/lyx/CNTKBook-master.pdf
new file mode 100644
index 000000000..1075d157f
--- /dev/null
+++ b/Documentation/CNTK-TechReport/lyx/CNTKBook-master.pdf
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+trailer
+<< /Size 4475
+/Root 4473 0 R
+/Info 4474 0 R
+/ID [<901F54E3AD1552C266E9C0639A4DD8F9> <901F54E3AD1552C266E9C0639A4DD8F9>] >>
+startxref
+1424359
+%%EOF
diff --git a/Documentation/CNTK-TechReport/lyx/CNTKBook_CNTK_Adv_Chapter.lyx b/Documentation/CNTK-TechReport/lyx/CNTKBook_CNTK_Adv_Chapter.lyx
index bf9ecd7e8..5c0b2b799 100644
--- a/Documentation/CNTK-TechReport/lyx/CNTKBook_CNTK_Adv_Chapter.lyx
+++ b/Documentation/CNTK-TechReport/lyx/CNTKBook_CNTK_Adv_Chapter.lyx
@@ -1464,17 +1464,7 @@ instead.
 \end_layout
 
 \begin_layout Subsubsection
-Input
-\begin_inset Index idx
-status open
-
-\begin_layout Plain Layout
-Input
-\end_layout
-
-\end_inset
-
-, InputValue
+InputValue
 \begin_inset Index idx
 status open
 
@@ -1484,7 +1474,17 @@ InputValue
 
 \end_inset
 
+ or Input
+\begin_inset Index idx
+status open
 
+\begin_layout Plain Layout
+Input
+\end_layout
+
+\end_inset
+
+ 
 \end_layout
 
 \begin_layout Standard
@@ -1502,12 +1502,12 @@ status open
 
 \begin_layout Plain Layout
 
-Input(rows, [cols=1], {tag=feature|label})
+InputValue(rows, [cols=1], {tag=feature|label})
 \end_layout
 
 \begin_layout Plain Layout
 
-InputValue(rows, [cols=1])
+Input(rows, [cols=1], {tag=feature|label})  #deprecated
 \end_layout
 
 \end_inset
@@ -1542,7 +1542,7 @@ ImageInput
 
 \end_inset
 
-, Image
+ or Image
 \begin_inset Index idx
 status open
 
@@ -1586,7 +1586,7 @@ Image(width, height, channels, [numImages=1],
 
 \begin_layout Plain Layout
 
-          {tag=feature|label})
+          {tag=feature|label}) #deprecated
 \end_layout
 
 \end_inset
@@ -1629,17 +1629,7 @@ CNTK uses column-major (similar to matlab) to store the matrices.
 \end_layout
 
 \begin_layout Subsubsection
-Parameter
-\begin_inset Index idx
-status open
-
-\begin_layout Plain Layout
-Parameter
-\end_layout
-
-\end_inset
-
-, LearnableParameter
+LearnableParameter
 \begin_inset Index idx
 status open
 
@@ -1647,6 +1637,16 @@ status open
 LearnableParameter
 \end_layout
 
+\end_inset
+
+ or Parameter
+\begin_inset Index idx
+status open
+
+\begin_layout Plain Layout
+Parameter
+\end_layout
+
 \end_inset
 
 
@@ -1668,21 +1668,6 @@ status open
 
 \begin_layout Plain Layout
 
-Parameter(row, [cols=1], {needGradient=true|false, 
-\end_layout
-
-\begin_layout Plain Layout
-
-          init=fixedValue|Uniform|Gaussian|fromFile, 
-\end_layout
-
-\begin_layout Plain Layout
-
-          value=0, initValueScale=number})
-\end_layout
-
-\begin_layout Plain Layout
-
 LearnableParameter(row, [cols=1], 
 \end_layout
 
@@ -1701,6 +1686,21 @@ LearnableParameter(row, [cols=1],
          value=0, initValueScale=number})
 \end_layout
 
+\begin_layout Plain Layout
+
+Parameter(row, [cols=1], {needGradient=true|false, 
+\end_layout
+
+\begin_layout Plain Layout
+
+          init=fixedValue|Uniform|Gaussian|fromFile, 
+\end_layout
+
+\begin_layout Plain Layout
+
+          value=0, initValueScale=number}) #deprecated
+\end_layout
+
 \end_inset
 
 
@@ -1782,7 +1782,7 @@ Constant
 
 \end_inset
 
-, Const
+ or Const
 \begin_inset Index idx
 status open
 
@@ -1813,7 +1813,7 @@ Constant(value, [rows=1, cols=1])
 
 \begin_layout Plain Layout
 
-Const(value, [rows=1, cols=1])
+Const(value, [rows=1, cols=1])  #deprecated
 \end_layout
 
 \end_inset
@@ -1845,7 +1845,7 @@ RectifiedLinear
 
 \end_inset
 
-, ReLU
+ or ReLU
 \begin_inset Index idx
 status open
 
@@ -1908,7 +1908,7 @@ RectifiedLinear(m)
 
 \begin_layout Plain Layout
 
-ReLU(m)
+ReLU(m) #deprecated
 \end_layout
 
 \begin_layout Plain Layout
@@ -2355,7 +2355,7 @@ KhatriRaoProduct
 
 \end_inset
 
-, ColumnwiseCrossProduct
+ or ColumnwiseCrossProduct
 \begin_inset Index idx
 status open
 
@@ -2388,7 +2388,7 @@ KhatriRaoProduct(m1, m2)
 
 \begin_layout Plain Layout
 
-ColumnwiseCrossProduct(m1, m2)
+ColumnwiseCrossProduct(m1, m2) #deprecated
 \end_layout
 
 \end_inset
@@ -2412,7 +2412,7 @@ GMMLogLikelihood
 
 \end_inset
 
-, GMMLL
+ or GMMLL
 \begin_inset Index idx
 status open
 
@@ -2447,7 +2447,7 @@ GMMLogLikelihood(UnnormedPrior, Means, LogStddev, FeatureValues)
 
 \begin_layout Plain Layout
 
-GMMLL(UnnormedPrior, Means, LogStddev, FeatureValues)
+GMMLL(UnnormedPrior, Means, LogStddev, FeatureValues) #deprecated
 \end_layout
 
 \end_inset
@@ -2497,7 +2497,7 @@ SquareError
 
 \end_inset
 
-, SE
+ or SE
 \begin_inset Index idx
 status open
 
@@ -2530,7 +2530,7 @@ SquareError(m1, m2)
 
 \begin_layout Plain Layout
 
-SE(m1, m2)
+SE(m1, m2) #deprecated
 \end_layout
 
 \end_inset
@@ -2554,7 +2554,7 @@ CrossEntropyWithSoftmax
 
 \end_inset
 
-, CEWithSM
+ or CEWithSM
 \begin_inset Index idx
 status open
 
@@ -2588,7 +2588,7 @@ CrossEntropyWithSoftmax(labels, matrix)
 
 \begin_layout Plain Layout
 
-CEWithSM(labels, matrix)
+CEWithSM(labels, matrix) #deprecated
 \end_layout
 
 \end_inset
@@ -2615,7 +2615,7 @@ ClassBasedCrossEntropyWithSoftmax
 
 \end_inset
 
-, CBCEWithSM
+ or CBCEWithSM
 \begin_inset Index idx
 status open
 
@@ -2649,7 +2649,8 @@ ClassBasedCrossEntropyWithSoftmax(labels, matrix)
 
 \begin_layout Plain Layout
 
-CBCEWithSM(labels, mainInputInfo, mainWeight, classProbBeforeSoftmax)
+CBCEWithSM(labels, mainInputInfo, mainWeight, classProbBeforeSoftmax) #deprecate
+d
 \end_layout
 
 \end_inset
@@ -2698,7 +2699,7 @@ ErrorPrediction
 
 \end_inset
 
-, ClassificationError
+ or ClassificationError
 \begin_inset Index idx
 status open
 
@@ -2761,7 +2762,7 @@ CosDistance
 
 \end_inset
 
-, CosDist
+ or CosDist
 \begin_inset Index idx
 status open
 
@@ -2792,7 +2793,7 @@ CosDistance(m1, m2)
 
 \begin_layout Plain Layout
 
-CosDist(m1, m2)
+CosDist(m1, m2) #deprecated
 \end_layout
 
 \end_inset
@@ -2816,7 +2817,7 @@ CosDistanceWithNegativeSamples
 
 \end_inset
 
-, CosWithNegSamples
+ or CosWithNegSamples
 \begin_inset Index idx
 status open
 
@@ -2862,7 +2863,7 @@ CosDistanceWithNegativeSamples(m1, m2, numShifts, numNegSamples)
 
 \begin_layout Plain Layout
 
-CosWithNegSamples(m1, m2, numShifts, numNegSamples)
+CosWithNegSamples(m1, m2, numShifts, numNegSamples) #deprecated
 \end_layout
 
 \end_inset
@@ -2895,7 +2896,7 @@ MatrixL1Reg
 
 \end_inset
 
-, L1Reg
+ or L1Reg
 \begin_inset Index idx
 status open
 
@@ -2915,7 +2916,7 @@ MatrixL2Reg
 
 \end_inset
 
-, L2Reg
+ or L2Reg
 \begin_inset Index idx
 status open
 
@@ -2948,7 +2949,7 @@ MatrixL1Reg(m)
 
 \begin_layout Plain Layout
 
-L1Reg(m)
+L1Reg(m) #deprecated
 \end_layout
 
 \begin_layout Plain Layout
@@ -2958,7 +2959,7 @@ MatrixL2Reg(m)
 
 \begin_layout Plain Layout
 
-L2Reg(m)
+L2Reg(m) #deprecated
 \end_layout
 
 \end_inset
@@ -3063,7 +3064,7 @@ PerDimMeanVarNormalization
 
 \end_inset
 
-, PerDimMVNorm
+ or PerDimMVNorm
 \begin_inset Index idx
 status open
 
@@ -3095,7 +3096,7 @@ PerDimMeanVarNormalization(m, mean, invStdDev)
 
 \begin_layout Plain Layout
 
-PerDimMVNorm(m, mean, invStdDev)
+PerDimMVNorm(m, mean, invStdDev) #deprecated
 \end_layout
 
 \end_inset
@@ -3128,7 +3129,7 @@ PerDimMeanVarDeNormalization
 
 \end_inset
 
-, PerDimMVDeNorm
+ or PerDimMVDeNorm
 \begin_inset Index idx
 status open
 
@@ -3163,7 +3164,7 @@ PerDimMeanVarDeNormalization(m, mean, invStdDev)
 
 \begin_layout Plain Layout
 
-PerDimMVDeNorm(m, mean, invStdDev)
+PerDimMVDeNorm(m, mean, invStdDev) #deprecated
 \end_layout
 
 \end_inset
@@ -3249,7 +3250,7 @@ Convolution
 
 \end_inset
 
-, Convolve
+ or Convolve
 \begin_inset Index idx
 status open
 
@@ -3311,7 +3312,7 @@ Convolve(w, image, kernelWidth, kernelHeight,
 
 \begin_layout Plain Layout
 
-            maxTempMemSizeInSamples=0])
+            maxTempMemSizeInSamples=0]) #deprecated
 \end_layout
 
 \end_inset
@@ -5266,7 +5267,7 @@ SetInput
 
 \end_inset
 
-, SetNodeInput
+ or SetNodeInput
 \begin_inset Index idx
 status open
 
@@ -5326,7 +5327,7 @@ SetInputs
 
 \end_inset
 
-, SetNodeInputs
+ or SetNodeInputs
 \begin_inset Index idx
 status open
 
@@ -5592,7 +5593,7 @@ Remove
 
 \end_inset
 
-, RemoveNode
+ or RemoveNode
 \begin_inset Index idx
 status open
 
@@ -5612,7 +5613,7 @@ Delete
 
 \end_inset
 
-, DeleteNode
+ or DeleteNode
 \begin_inset Index idx
 status open
 
@@ -5638,12 +5639,12 @@ status open
 
 \begin_layout Plain Layout
 
-Remove(node, [node2, node3])
+Remove(node, [node2, node3]) #deprecated
 \end_layout
 
 \begin_layout Plain Layout
 
-Delete(node, [node2, node3])
+Delete(node, [node2, node3]) #deprecated
 \end_layout
 
 \begin_layout Plain Layout
diff --git a/Documentation/CNTK-TechReport/lyx/CNTKBook_CNTK_Chapter.lyx b/Documentation/CNTK-TechReport/lyx/CNTKBook_CNTK_Chapter.lyx
index 9c91fcba5..9779be49f 100644
--- a/Documentation/CNTK-TechReport/lyx/CNTKBook_CNTK_Chapter.lyx
+++ b/Documentation/CNTK-TechReport/lyx/CNTKBook_CNTK_Chapter.lyx
@@ -125,7 +125,7 @@ status open
 
 \begin_layout Plain Layout
 
-cn.exe configFile=yourExp.config
+cntk configFile=yourExp.config
 \end_layout
 
 \end_inset
@@ -5454,7 +5454,7 @@ status open
 
 \begin_layout Plain Layout
 
-cn.exe configFile=yourExp.config
+cntk configFile=yourExp.config
 \end_layout
 
 \end_inset
@@ -5574,7 +5574,7 @@ status open
 
 \begin_layout Plain Layout
 
-cn.exe configFile=yourExp.config stderr=c:
+cntk configFile=yourExp.config stderr=c:
 \backslash
 temp
 \backslash
@@ -5602,7 +5602,7 @@ status open
 
 \begin_layout Plain Layout
 
-cn.exe configFile=yourExp.config mnistTrain=[minibatchSize=256] 
+cntk configFile=yourExp.config mnistTrain=[minibatchSize=256] 
 \end_layout
 
 \end_inset
@@ -5617,7 +5617,7 @@ status open
 
 \begin_layout Plain Layout
 
-cn.exe configFile=yourExp.config mnistTrain=[reader=[file=mynewfile.txt]] 
+cntk configFile=yourExp.config mnistTrain=[reader=[file=mynewfile.txt]] 
 \end_layout
 
 \end_inset
@@ -5662,12 +5662,12 @@ status open
 
 \begin_layout Plain Layout
 
-cn.exe configFile=yourExp1.config+yourExp2.config 
+cntk configFile=yourExp1.config+yourExp2.config 
 \end_layout
 
 \begin_layout Plain Layout
 
-cn.exe configFile=yourExp1.config configFile=yourExp2.config 
+cntk configFile=yourExp1.config configFile=yourExp2.config 
 \end_layout
 
 \end_inset
@@ -5687,8 +5687,7 @@ status open
 
 \begin_layout Plain Layout
 
-cn.exe configFile=yourExp1.config mnistTrain=[reader=[file=mynewfile.txt]]
- 
+cntk configFile=yourExp1.config mnistTrain=[reader=[file=mynewfile.txt]] 
 \end_layout
 
 \end_inset
@@ -5711,8 +5710,8 @@ status open
 
 \begin_layout Plain Layout
 
-cn.exe configFile=yourExp1.config+yourExp2.config var1=value configFile=yourExp3.con
-fig 
+cntk configFile=yourExp1.config+yourExp2.config var1=value configFile=yourExp3.conf
+ig 
 \end_layout
 
 \end_inset
@@ -5753,7 +5752,7 @@ status open
 
 \begin_layout Plain Layout
 
-cn.exe configFile=yourExp2.config
+cntk configFile=yourExp2.config
 \end_layout
 
 \end_inset
@@ -5768,7 +5767,7 @@ status open
 
 \begin_layout Plain Layout
 
-cn.exe configFile=yourExp1.config+yourExp2.config
+cntk configFile=yourExp1.config+yourExp2.config
 \end_layout
 
 \end_inset
diff --git a/Documentation/CNTK-TechReport/lyx/CNTKBook_Introduction.lyx b/Documentation/CNTK-TechReport/lyx/CNTKBook_Introduction.lyx
index 0432ad6b0..4831fd9e8 100644
--- a/Documentation/CNTK-TechReport/lyx/CNTKBook_Introduction.lyx
+++ b/Documentation/CNTK-TechReport/lyx/CNTKBook_Introduction.lyx
@@ -819,7 +819,7 @@ status open
 
 \begin_layout Plain Layout
 
-cn.exe configFile=Simple.config 
+cntk configFile=Simple.config 
 \end_layout
 
 \end_inset
@@ -838,7 +838,7 @@ status open
 
 \begin_layout Plain Layout
 
-cn configFile=Simple.config 
+cntk configFile=Simple.config 
 \end_layout
 
 \end_inset

From 0eac6ef3fcd70d9ffc20a4625ada5ff280cbbcc5 Mon Sep 17 00:00:00 2001
From: Dong Yu <dongyu@microsoft.com>
Date: Tue, 19 May 2015 14:10:45 +0800
Subject: [PATCH 36/49] change cn.exe to cntk in examples setups, demos,
 tutorials, and check-in suites.

fix the bug in TimitGetFiles.py
---
 CheckInSuites/ASR/config/README.txt           |   4 ++--
 CheckInSuites/ASR/config/runall.bat           |  16 ++++++++--------
 CheckInSuites/SLU/README                      |   4 ++--
 Demos/Speech/TimitGetFiles.py                 |   4 ++--
 .../Tutorial/CNTK-Tutorial-ICASSP2015.pdf     | Bin 2556196 -> 2555953 bytes
 ExampleSetups/ASR/TIMIT/config/README.txt     |   2 +-
 ExampleSetups/SLU/README.txt                  |   4 ++--
 7 files changed, 17 insertions(+), 17 deletions(-)

diff --git a/CheckInSuites/ASR/config/README.txt b/CheckInSuites/ASR/config/README.txt
index 8c1720bdd..e610ee4db 100644
--- a/CheckInSuites/ASR/config/README.txt
+++ b/CheckInSuites/ASR/config/README.txt
@@ -4,7 +4,7 @@ These scripts are similar to those in the TIMIT folder of the ExampleSetups exce
 The globals_cpu.config and globals_gpu.config differ only in which device they use and where the results are stored. 
 
 To test on CPU:
-cn.exe configFile=globals_cpu.config+<DesiredConfigFile>
+cntk configFile=globals_cpu.config+<DesiredConfigFile>
 
 To test on GPU:
-cn.exe configFile=globals_gpu.config+<DesiredConfigFile>
+cntk configFile=globals_gpu.config+<DesiredConfigFile>
diff --git a/CheckInSuites/ASR/config/runall.bat b/CheckInSuites/ASR/config/runall.bat
index 03de434ea..ea9fc2b05 100644
--- a/CheckInSuites/ASR/config/runall.bat
+++ b/CheckInSuites/ASR/config/runall.bat
@@ -1,14 +1,14 @@
 set cnpath=d:\gitroot\cntk\CNTKSolution\x64\Release
 set proc=%1
 echo on
-%cnpath%\cn.exe configFile=globals_%proc%.config+TIMIT_TrainSimpleNetwork.config
-%cnpath%\cn.exe configFile=globals_%proc%.config+TIMIT_TrainNDLNetwork.config
-%cnpath%\cn.exe configFile=globals_%proc%.config+TIMIT_TrainAutoEncoder.config
-%cnpath%\cn.exe configFile=globals_%proc%.config+TIMIT_TrainMultiInput.config
-%cnpath%\cn.exe configFile=globals_%proc%.config+TIMIT_TrainMultiTask.config
-%cnpath%\cn.exe configFile=globals_%proc%.config+TIMIT_EvalSimpleNetwork.config
-%cnpath%\cn.exe configFile=globals_%proc%.config+TIMIT_WriteScaledLogLike.config
-%cnpath%\cn.exe configFile=globals_%proc%.config+TIMIT_WriteBottleneck.config
+%cnpath%\cntk configFile=globals_%proc%.config+TIMIT_TrainSimpleNetwork.config
+%cnpath%\cntk configFile=globals_%proc%.config+TIMIT_TrainNDLNetwork.config
+%cnpath%\cntk configFile=globals_%proc%.config+TIMIT_TrainAutoEncoder.config
+%cnpath%\cntk configFile=globals_%proc%.config+TIMIT_TrainMultiInput.config
+%cnpath%\cntk configFile=globals_%proc%.config+TIMIT_TrainMultiTask.config
+%cnpath%\cntk configFile=globals_%proc%.config+TIMIT_EvalSimpleNetwork.config
+%cnpath%\cntk configFile=globals_%proc%.config+TIMIT_WriteScaledLogLike.config
+%cnpath%\cntk configFile=globals_%proc%.config+TIMIT_WriteBottleneck.config
 
 
 
diff --git a/CheckInSuites/SLU/README b/CheckInSuites/SLU/README
index 48812f89b..fca69479c 100644
--- a/CheckInSuites/SLU/README
+++ b/CheckInSuites/SLU/README
@@ -1,4 +1,4 @@
-C:\dev\cntk3\CNTKSolution\x64\Release\cn.exe configFile=globals.config+rnnlu.config
+C:\dev\cntk3\CNTKSolution\x64\Release\cntk configFile=globals.config+rnnlu.config
 
 
 # expected results, which has a copy at Expected.log is 
@@ -11,6 +11,6 @@ Finished Epoch[3]: [Training Set] Train Loss Per Sample = 3.6568716    EvalErr P
 Finished Epoch[3]: [Validation Set] Train Loss Per Sample = 2.6959986  EvalErr Per Sample = 2.6959986
 
 del /q c:\temp\exp\atis
-C:\dev\cntk3\CNTKSolution\x64\Release\cn.exe configFile=globals.config+rnnlu.ndl.config
+C:\dev\cntk3\CNTKSolution\x64\Release\cntk configFile=globals.config+rnnlu.ndl.config
 #should have the same output as above using simple network builder. 
 
diff --git a/Demos/Speech/TimitGetFiles.py b/Demos/Speech/TimitGetFiles.py
index ffe7f9b8f..c97b6cda0 100644
--- a/Demos/Speech/TimitGetFiles.py
+++ b/Demos/Speech/TimitGetFiles.py
@@ -41,8 +41,8 @@ fileCount = 0
 fileList = 'TimitSubjectList.txt'
 fileListFp = open(fileList)
 
-if !hcopyScript or !cnScriptFp or !cnOutputScriptFp or !fileListFp:
-	print "Can't open the necessary output files.
+if !hcopyScriptFp or !cnScriptFp or !cnOutputScriptFp or !fileListFp:
+	print "Can't open the necessary output files."
 	sys.exit(0)
 
 for origFile in fileListFp:
diff --git a/Documentation/Tutorial/CNTK-Tutorial-ICASSP2015.pdf b/Documentation/Tutorial/CNTK-Tutorial-ICASSP2015.pdf
index 2d78497faf97ad7fd5dcb06ce006c12f35c1ff27..0489f979766de101c604b85a2d8f61e592c51ff9 100644
GIT binary patch
delta 411756
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diff --git a/ExampleSetups/ASR/TIMIT/config/README.txt b/ExampleSetups/ASR/TIMIT/config/README.txt
index b6553b497..6fd15308c 100644
--- a/ExampleSetups/ASR/TIMIT/config/README.txt
+++ b/ExampleSetups/ASR/TIMIT/config/README.txt
@@ -12,7 +12,7 @@ Modify the following files:
 * all SCP files (lists of files) in "lib/scp" to point to your feature files
 
 Run the command line with both globals.config and the desired config, separated by a +
-* for example: cn.exe configFile=globals.config+TIMIT_TrainSimpleNetwork.config
+* for example: cntk configFile=globals.config+TIMIT_TrainSimpleNetwork.config
 * note that full paths to config files need to be provided if you are not inside the config directory
 
 Path Definitions:
diff --git a/ExampleSetups/SLU/README.txt b/ExampleSetups/SLU/README.txt
index 899455b07..b8bbb1b35 100644
--- a/ExampleSetups/SLU/README.txt
+++ b/ExampleSetups/SLU/README.txt
@@ -12,11 +12,11 @@ Modify the following files:
 * all SCP files (lists of files) in "lib/scp" to point to your feature files
 
 Run the command line with both globals.config and the desired config, separated by a +
-* for example: cn.exe configFile=globals.config+rnnlu.config
+* for example: cntk configFile=globals.config+rnnlu.config
 
 * note that full paths to config files need to be provided if you are not inside the config directory
 * for example 
-* C:\dev\cntk5\CNTKSolution\x64\Release\cn.exe configFile=C:\dev\cntk5\ExampleSetups\SLU\globals.config+C:\dev\cntk5\ExampleSetups\SLU\rnnlu.config
+* C:\dev\cntk5\CNTKSolution\x64\Release\cntk configFile=C:\dev\cntk5\ExampleSetups\SLU\globals.config+C:\dev\cntk5\ExampleSetups\SLU\rnnlu.config
 
 Scoring
 * ./score.sh 

From 2aea026dda5a05d64eae23df23faf6b491d97d3b Mon Sep 17 00:00:00 2001
From: Dong Yu <dongyu@microsoft.com>
Date: Tue, 19 May 2015 14:19:05 +0800
Subject: [PATCH 37/49] rename CNTKbook to include date.

---
 .../CNTK-TechReport/lyx/CNTKBook-20150513.pdf | 28692 ----------------
 ...KBook-master.pdf => CNTKBook-20150518.pdf} |     0
 2 files changed, 28692 deletions(-)
 delete mode 100644 Documentation/CNTK-TechReport/lyx/CNTKBook-20150513.pdf
 rename Documentation/CNTK-TechReport/lyx/{CNTKBook-master.pdf => CNTKBook-20150518.pdf} (100%)

diff --git a/Documentation/CNTK-TechReport/lyx/CNTKBook-20150513.pdf b/Documentation/CNTK-TechReport/lyx/CNTKBook-20150513.pdf
deleted file mode 100644
index 1d8c9d00c..000000000
--- a/Documentation/CNTK-TechReport/lyx/CNTKBook-20150513.pdf
+++ /dev/null
@@ -1,28692 +0,0 @@
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-trailer
-<< /Size 4474
-/Root 4472 0 R
-/Info 4473 0 R
-/ID [<077796DE00BBBDC9B4E1858B2190B91D> <077796DE00BBBDC9B4E1858B2190B91D>] >>
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diff --git a/Documentation/CNTK-TechReport/lyx/CNTKBook-master.pdf b/Documentation/CNTK-TechReport/lyx/CNTKBook-20150518.pdf
similarity index 100%
rename from Documentation/CNTK-TechReport/lyx/CNTKBook-master.pdf
rename to Documentation/CNTK-TechReport/lyx/CNTKBook-20150518.pdf

From ec4de72b7e135483655df318dd6b7126ba5c8c10 Mon Sep 17 00:00:00 2001
From: Frank Seide <fseide@microsoft.com>
Date: Mon, 18 May 2015 23:40:48 -0700
Subject: [PATCH 38/49] split ComputationNode.h off into 5 additional headers
 (InputAndParam, LinearAlgebra, Nonlinearity, Recurrent, Convolutional),
 grouped by nature of their function (but no code change other than moving
 classes in this check-in); sorted #includes in many places (system #includes
 first), and removed some unnecessary #includes; TWO_PI moved into Basics.h;
 fixed an unused-argument warning in GPUMatrix.cu

---
 Common/Include/Basics.h                       |    5 +-
 MachineLearning/CNTK/CNTK.vcxproj             |    5 +
 MachineLearning/CNTK/CNTK.vcxproj.filters     |   15 +
 .../CNTK/CompositeComputationNodes.h          | 1391 +-----
 MachineLearning/CNTK/ComputationNetwork.h     |   21 +-
 .../CNTK/ComputationNetworkHelper.h           |   11 +-
 MachineLearning/CNTK/ComputationNode.cpp      |    4 +-
 MachineLearning/CNTK/ComputationNode.h        | 4378 +----------------
 MachineLearning/CNTK/ConvolutionalNodes.h     |  945 ++++
 MachineLearning/CNTK/InputAndParamNodes.h     |  504 ++
 MachineLearning/CNTK/LinearAlgebraNodes.h     | 2360 +++++++++
 .../CNTK/NetworkDescriptionLanguage.cpp       |    6 +-
 .../CNTK/NetworkDescriptionLanguage.h         |    7 +-
 MachineLearning/CNTK/NonlinearityNodes.h      | 1617 ++++++
 MachineLearning/CNTK/RecurrentNodes.h         |  378 ++
 MachineLearning/CNTK/SimpleEvaluator.h        |   10 +-
 MachineLearning/CNTK/SimpleNetworkBuilder.cpp |    6 +
 MachineLearning/CNTK/SimpleNetworkBuilder.h   |   14 +-
 MachineLearning/CNTK/tests.cpp                |   10 +-
 MachineLearning/CNTKEval/CNTKEval.cpp         |    3 +-
 MachineLearning/CNTKEval/CNTKEval.h           |    5 +-
 Math/Math/GPUMatrix.cu                        |    2 +-
 22 files changed, 5929 insertions(+), 5768 deletions(-)
 create mode 100644 MachineLearning/CNTK/ConvolutionalNodes.h
 create mode 100644 MachineLearning/CNTK/InputAndParamNodes.h
 create mode 100644 MachineLearning/CNTK/LinearAlgebraNodes.h
 create mode 100644 MachineLearning/CNTK/NonlinearityNodes.h
 create mode 100644 MachineLearning/CNTK/RecurrentNodes.h

diff --git a/Common/Include/Basics.h b/Common/Include/Basics.h
index 48695d669..2cf3f1447 100644
--- a/Common/Include/Basics.h
+++ b/Common/Include/Basics.h
@@ -8,8 +8,9 @@
 #define _BASICS_H_
 
 #include "basetypes.h"  // TODO: gradually move over here all that's needed of basetypes.h, then remove basetypes.h.
-
-
+
+#define TWO_PI 6.283185307f // TODO: find the official standards-confirming definition of this and use it instead
+
 // ===========================================================================
 // emulation of some MSVC proprietary CRT
 // ===========================================================================
diff --git a/MachineLearning/CNTK/CNTK.vcxproj b/MachineLearning/CNTK/CNTK.vcxproj
index 27d277457..bb76f801c 100644
--- a/MachineLearning/CNTK/CNTK.vcxproj
+++ b/MachineLearning/CNTK/CNTK.vcxproj
@@ -167,13 +167,18 @@
     <ClInclude Include="ComputationNetwork.h" />
     <ClInclude Include="ComputationNetworkHelper.h" />
     <ClInclude Include="ComputationNode.h" />
+    <ClInclude Include="ConvolutionalNodes.h" />
     <ClInclude Include="EvaluationCriterionNodes.h" />
     <ClInclude Include="IComputationNetBuilder.h" />
     <ClInclude Include="IExecutionEngine.h" />
+    <ClInclude Include="InputAndParamNodes.h" />
+    <ClInclude Include="LinearAlgebraNodes.h" />
     <ClInclude Include="ModelEditLanguage.h" />
     <ClInclude Include="NDLNetworkBuilder.h" />
     <ClInclude Include="NDLUtil.h" />
     <ClInclude Include="NetworkDescriptionLanguage.h" />
+    <ClInclude Include="NonlinearityNodes.h" />
+    <ClInclude Include="RecurrentNodes.h" />
     <ClInclude Include="SimpleEvaluator.h" />
     <ClInclude Include="SimpleOutputWriter.h" />
     <ClInclude Include="SGD.h" />
diff --git a/MachineLearning/CNTK/CNTK.vcxproj.filters b/MachineLearning/CNTK/CNTK.vcxproj.filters
index 882ad557d..a183ca3d6 100644
--- a/MachineLearning/CNTK/CNTK.vcxproj.filters
+++ b/MachineLearning/CNTK/CNTK.vcxproj.filters
@@ -136,6 +136,21 @@
     <ClInclude Include="TrainingCriterionNodes.h">
       <Filter>Nodes</Filter>
     </ClInclude>
+    <ClInclude Include="NonlinearityNodes.h">
+      <Filter>Nodes</Filter>
+    </ClInclude>
+    <ClInclude Include="LinearAlgebraNodes.h">
+      <Filter>Nodes</Filter>
+    </ClInclude>
+    <ClInclude Include="ConvolutionalNodes.h">
+      <Filter>Nodes</Filter>
+    </ClInclude>
+    <ClInclude Include="RecurrentNodes.h">
+      <Filter>Nodes</Filter>
+    </ClInclude>
+    <ClInclude Include="InputAndParamNodes.h">
+      <Filter>Nodes</Filter>
+    </ClInclude>
   </ItemGroup>
   <ItemGroup>
     <Text Include="modelEditor.txt">
diff --git a/MachineLearning/CNTK/CompositeComputationNodes.h b/MachineLearning/CNTK/CompositeComputationNodes.h
index 34b6e08e4..53d27c606 100644
--- a/MachineLearning/CNTK/CompositeComputationNodes.h
+++ b/MachineLearning/CNTK/CompositeComputationNodes.h
@@ -7,17 +7,15 @@
 
 //The basic idea of this implementation is learned from Brian Guenter <bguenter@microsoft.com>
 
+#include "ComputationNode.h"
+#include "TrainingCriterionNodes.h"
+
 #include <map>
 #include <string>
 #include <stdexcept>
 #include <list>
-#include "ComputationNode.h"
-#include "TrainingCriterionNodes.h"
 #include <iostream> 
 
-#define TWO_PI 6.283185307f
-
-
 //this file will contain computation nodes that require several atomic computation.
 //composite nodes can save memory, computation, or both
 namespace Microsoft { namespace MSR { namespace CNTK {
@@ -692,1389 +690,6 @@ namespace Microsoft { namespace MSR { namespace CNTK {
     template class PerDimMeanVarDeNormalizationNode<double>;
 
 
-    // convolution parameters structure, to make it easier to pass these around all these parameters
-    struct ConvolutionParams
-    {
-        size_t inputWidth, inputHeight, inputChannels;
-        size_t kernelWidth, kernelHeight;
-        size_t horizontalSubsample, verticalSubsample;
-        size_t outputWidth, outputHeight, outputChannels;
-        size_t maxTempMemSizeInSamples;
-        bool zeroPadding;
-    };
-
-    //convolutional network 
-    //follow "high performance convolutional neural networks for document processing" by Kumar chellapilla, Sidde Puri, and Patrice Simard
-    //assume each column is an input sample. Each sample is stored in [channel, row, col]  (r00, g00, b00, r01, g01, b01, r10, g10, b10, r11, g11, b11)
-    template<class ElemType>
-    class ConvolutionNode : public ComputationNode<ElemType>
-    {
-        UsingComputationNodeMembers;
-    public:
-        ConvolutionNode(const size_t kernelWidth, const size_t kernelHeight, const size_t outputChannels, 
-                        const size_t horizontalSubsample, const size_t verticalSubsample, 
-                        const bool zeroPadding = false, 
-                        const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"",
-                        const size_t maxTempMemSizeInSamples = 0)
-                        : ComputationNode<ElemType>(deviceId), m_tempMatrix(deviceId),
-                          m_kernelWidth(kernelWidth), m_kernelHeight(kernelHeight), 
-                          m_horizontalSubsample(horizontalSubsample), m_verticalSubsample(verticalSubsample),
-                          m_zeroPadding(zeroPadding), m_maxTempMemSizeInSamples(maxTempMemSizeInSamples)
-        {
-            m_outputChannels = outputChannels;
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            m_deviceId = deviceId;
-            MoveMatricesToDevice(deviceId);
-            InitRecurrentNode();
-        }
-
-        ConvolutionNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") 
-            : ComputationNode<ElemType>(deviceId), m_tempMatrix(deviceId)
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            LoadFromFile(fstream, modelVersion, deviceId);
-        }
-                
-        virtual void SaveToFile(File& fstream) const
-        {
-            ComputationNode<ElemType>::SaveToFile(fstream);
-
-            fstream <<  m_kernelWidth << m_kernelHeight << m_horizontalSubsample << m_verticalSubsample; 
-            fstream << m_outputChannels << m_zeroPadding << m_maxTempMemSizeInSamples; 
-        }
-
-        virtual void LoadFromFile(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX)
-        {
-            ComputationNode<ElemType>::LoadFromFile(fstream, modelVersion, deviceId);
-
-            fstream >>  m_kernelWidth >> m_kernelHeight >> m_horizontalSubsample >> m_verticalSubsample; 
-            fstream >> m_outputChannels >> m_zeroPadding >> m_maxTempMemSizeInSamples; 
-        }
-
-        virtual void CopyTo(const ComputationNodePtr nodeP, const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            ComputationNode<ElemType>::CopyTo(nodeP, newName, flags);
-            ConvolutionNode<ElemType>* node = (ConvolutionNode<ElemType>*) nodeP;
-
-            if (flags & CopyNodeFlags::copyNodeValue)
-            {
-                node->m_kernelWidth = m_kernelWidth;
-                node->m_kernelHeight = m_kernelHeight;
-
-                node->m_horizontalSubsample = m_horizontalSubsample;
-                node->m_verticalSubsample = m_verticalSubsample;
-
-                node->m_zeroPadding = m_zeroPadding;
-
-                node->m_maxTempMemSizeInSamples = m_maxTempMemSizeInSamples;
-
-                node->m_tempMatrix = m_tempMatrix;
-            }
-        }
-
-        // copy constructor
-        ConvolutionNode(const ConvolutionNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags) 
-            : ComputationNode<ElemType>(node->m_deviceId), m_tempMatrix(node->m_deviceId)
-        {
-            node->CopyTo(this, newName, flags);
-        }
-
-        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            const std::wstring& name = (newName == L"")?NodeName():newName;
-                
-            ComputationNodePtr node = new ConvolutionNode<ElemType>(this, name, flags);
-            return node;
-        }
-
-        virtual const std::wstring OperationName() const {return TypeName();}
-        static const std::wstring TypeName() {return L"Convolution";} 
-
-        ConvolutionParams GetConvolutionParams() const
-        {
-            ConvolutionParams convParam;
-            convParam.inputWidth = m_inputWidth;
-            convParam.inputHeight = m_inputHeight;
-            convParam.inputChannels = m_inputChannels;
-
-            convParam.kernelWidth = m_kernelWidth;
-            convParam.kernelHeight = m_kernelHeight;
-
-            convParam.horizontalSubsample = m_horizontalSubsample;
-            convParam.verticalSubsample = m_verticalSubsample;
-
-            convParam.outputWidth = m_outputWidth;
-            convParam.outputHeight = m_outputHeight;
-            convParam.outputChannels = m_outputChannels;
-
-            convParam.zeroPadding = m_zeroPadding;
-
-            convParam.maxTempMemSizeInSamples = m_maxTempMemSizeInSamples;
-            return convParam;
-        }
-
-        virtual void ComputeInputPartial(const size_t inputIndex) 
-        {
-            if (inputIndex > 1)
-                throw std::invalid_argument("Convolution operation only takes two inputs.");
-
-            if (inputIndex == 0)  //derivative with regard to the weight matrix
-            {
-                ComputeInputPartialOverWeight(this, GradientValues(), Inputs(0)->GradientValues(), Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues(), m_tempMatrix, true);
-            }
-            else  // derivative with regard to the input feature
-            {
-                ComputeInputPartialOverInputFeature(this, GradientValues(), Inputs(1)->GradientValues(), Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues(), m_tempMatrix);
-            }
-        }
-
-        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq) 
-        {
-            if (inputIndex > 1)
-                throw std::invalid_argument("Convolution operation only takes two inputs.");
-
-            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            if (inputIndex == 0)  //derivative with regard to the weight matrix
-            {
-                ComputeInputPartialOverWeight(this, sliceOutputGrad, Inputs(0)->GradientValues(), Inputs(0)->FunctionValues(), sliceInput1Value, m_tempMatrix);
-            }
-            else  // derivative with regard to the input feature
-            {
-                Matrix<ElemType> sliceInput1Grad = Inputs(1)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-                ComputeInputPartialOverInputFeature(this, sliceOutputGrad, sliceInput1Grad, Inputs(0)->FunctionValues(), sliceInput1Value, m_tempMatrix);
-            }
-        }
-
-        virtual void EvaluateThisNode()  
-        {
-            EvaluateThisNodeS(this, FunctionValues(), Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues(), m_tempMatrix);
-        }
-
-        virtual void EvaluateThisNode(const size_t timeIdxInSeq) 
-        {
-            Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            EvaluateThisNodeS(this, sliceOutputValue, Inputs(0)->FunctionValues(), sliceInput1Value, m_tempMatrix);
-        }
-
-        static void WINAPI EvaluateThisNodeS(const ConvolutionNode<ElemType>* pConv, Matrix<ElemType> &functionValues, const Matrix<ElemType> &input0, 
-            const Matrix<ElemType> &input1, Matrix<ElemType> &tempMatrix)
-        {
-#if NANCHECK
-            input0.HasNan("Convolution-input0");
-            input1.HasNan("Convolution-input1");
-#endif
-            ConvolutionParams convParam = pConv->GetConvolutionParams();
-
-            size_t packedInputRows = convParam.kernelWidth * convParam.kernelHeight * convParam.inputChannels;
-            size_t packedInputColsPerSample = convParam.outputWidth * convParam.outputHeight;
-            size_t outputSizePerChannel = packedInputColsPerSample;
-            //size_t packedInputDim = packedInputRows * packedInputColsPerSample; // size of each packed input sample
-            //size_t inputDim = convParam.inputWidth * convParam.inputHeight * convParam.inputChannels;  //size of each input sample
-
-            long batchSize = (long)input1.GetNumCols();  //right child is the input sample
-
-            long maxTempMemSizeInSamples = (long)(convParam.maxTempMemSizeInSamples == 0? batchSize : convParam.maxTempMemSizeInSamples);
-
-            const Matrix<ElemType> & weightMatrix = input0;
-            assert(weightMatrix.GetNumCols() == packedInputRows && weightMatrix.GetNumRows() == convParam.outputChannels);
-            functionValues.Resize(convParam.outputChannels, outputSizePerChannel * batchSize);
-
-            long subBatchSize = (long)min(batchSize, maxTempMemSizeInSamples); 
-            long numSubBatches = (batchSize+subBatchSize-1)/subBatchSize; 
-
-            for (long i=0; i<numSubBatches; i++) 
-            {
-                long startSampleID = i*subBatchSize; 
-                long endSampleID = min(batchSize, startSampleID + subBatchSize); 
-                long smallBatchSize = endSampleID-startSampleID; 
-
-                tempMatrix.Resize(packedInputRows, packedInputColsPerSample * smallBatchSize);
-                Matrix<ElemType>  inputSubBatch = input1.ColumnSlice(startSampleID, smallBatchSize);
-                tempMatrix.AssignPackedConvolutionInput(inputSubBatch, 
-                                                                 convParam.inputWidth, convParam.inputHeight, convParam.inputChannels,
-                                                                 convParam.outputWidth, convParam.outputHeight, convParam.outputChannels,
-                                                                 convParam.kernelWidth, convParam.kernelHeight, convParam.horizontalSubsample, convParam.verticalSubsample, 
-                                                                 convParam.zeroPadding); 
-
-                Matrix<ElemType>  outputSubBatch = functionValues.ColumnSlice(outputSizePerChannel * startSampleID, outputSizePerChannel * smallBatchSize);
-                Matrix<ElemType>::Multiply(weightMatrix, false, tempMatrix, false, outputSubBatch);
-            }
-
-            functionValues.Reshape(convParam.outputChannels * outputSizePerChannel, batchSize);  //each sample becomes a column
-
-#if NANCHECK
-            functionValues.HasNan("Convolution");
-#endif
-        }
-
-        virtual void Validate()
-        {
-            PrintSelfBeforeValidation();
-
-            if (m_children.size() != 2) 
-                throw std::logic_error("ConvolutionNode requires two inputs.");
-
-            //we may want to remove this check in the future if we want to support the case that the weight itself is result of some computation 
-            //if (Inputs(0)->OperationName() != LearnableParameter<ElemType>::TypeName())
-            //    throw std::logic_error("ConvolutionNode requires the first input to be LearnableParameter type.");
-
-            if (m_horizontalSubsample > m_kernelWidth || m_verticalSubsample > m_kernelHeight)
-                throw std::invalid_argument("In ConvolutionNode horizontalSubsample must <= kernelWidth and verticalSubsample must <= kernelHeight.");
-
-            CopyImageSizeFromInputs();
-
-            size_t weightCols = m_kernelWidth * m_kernelHeight * m_inputChannels;
-
-            if (Inputs(0)->OperationName() == LearnableParameter<ElemType>::TypeName() && Inputs(0)->FunctionValues().GetNumElements() == 0)
-            {
-                Inputs(0)->FunctionValues().Resize(m_outputChannels, weightCols);
-            }
-
-            if (m_children[0]->FunctionValues().GetNumCols() != weightCols || m_children[0]->FunctionValues().GetNumRows() != m_outputChannels)
-            {
-                msra::strfun::strprintf msg("convolutionWeight matrix %ls should have dimension [%d, %d] which is [outputChannels, kernelWidth * kernelHeight * inputChannels]", 
-                    m_children[0]->NodeName().c_str(), m_outputChannels, weightCols);
-                throw std::logic_error(msg.c_str());            
-            }
-
-            size_t inputDim = m_inputWidth * m_inputHeight * m_inputChannels;
-            if (Inputs(1)->OperationName() == LearnableParameter<ElemType>::TypeName() && Inputs(1)->FunctionValues().GetNumRows() == 0)
-            {
-                Inputs(1)->FunctionValues().Resize(inputDim, Inputs(1)->FunctionValues().GetNumCols());
-            }
-
-            if (m_children[1]->FunctionValues().GetNumRows() != inputDim)
-            {
-                msra::strfun::strprintf msg("each column of input to the convolution node %ls is a sample and should have dimension %d, which is inputWidth * inputHeight * inputChannels", 
-                    NodeName().c_str(), inputDim);
-                throw std::logic_error(msg.c_str());            
-            }
-
-            if (Inputs(0)->FunctionValues().GetNumElements() == 0 || Inputs(1)->FunctionValues().GetNumElements() == 0 )
-                throw std::logic_error("Convolution operation: one of the operants has 0 element.");
-            
-            size_t outputDim = m_outputWidth * m_outputHeight * m_outputChannels;
-            FunctionValues().Resize(outputDim, m_children[1]->FunctionValues().GetNumCols());
-        }
-
-        virtual void CopyImageSizeFromInputs()
-        {
-            CopyImageSizeFromInput(1, false);
-
-            if (m_inputWidth < m_kernelWidth || m_inputHeight < m_kernelHeight)
-                throw std::invalid_argument("inputWidth must >= kernelWidth and inputHeight must >= kernelHeight.");
-
-            if (m_zeroPadding)
-            {
-                const int kernelWidthCenter = m_kernelWidth % 2;
-                const int kernelHeightCenter = m_kernelHeight % 2;
-                m_outputWidth = (m_inputWidth-kernelWidthCenter)/m_horizontalSubsample + 1;
-                m_outputHeight = (m_inputHeight-kernelHeightCenter)/m_verticalSubsample + 1;
-            }
-            else
-            {
-                m_outputWidth = (m_inputWidth-m_kernelWidth)/m_horizontalSubsample + 1;
-                m_outputHeight = (m_inputHeight-m_kernelHeight)/m_verticalSubsample + 1;
-            }    
-        }
-
-        virtual void AttachInputs(const ComputationNodePtr convolutionWeight, const ComputationNodePtr inputFeature) 
-        {
-            m_children.resize(2);
-            m_children[0] = convolutionWeight;
-            m_children[1] = inputFeature;
-        }
-
-        virtual void MoveMatricesToDevice(const DEVICEID_TYPE deviceId)
-        {
-            ComputationNode<ElemType>::MoveMatricesToDevice(deviceId);
-
-            if (deviceId != AUTOPLACEMATRIX)
-            {
-                if (m_tempMatrix.GetDeviceId() != deviceId)
-                    m_tempMatrix.TransferFromDeviceToDevice(m_tempMatrix.GetDeviceId(), deviceId);
-            }
-        }
-
-        virtual void DumpNodeInfo(const bool printValues, File& fstream) const
-        {
-            ComputationNode<ElemType>::DumpNodeInfo(printValues, fstream);
-
-            char str[4096];
-            sprintf(str, "Input[Width:%lu, Height:%lu, Channels:%lu]  \n", m_inputWidth, m_inputHeight, m_inputChannels);
-            fstream << string(str);
-            sprintf(str, "Kernel[Width:%lu, Height:%lu]  SubSample[Horizontal:%lu, Vertical:%lu]\n", m_kernelWidth, m_kernelHeight, m_horizontalSubsample, m_verticalSubsample);
-            fstream << string(str);
-            sprintf(str, "Output[Width:%lu, Height:%lu, Channels:%lu]  \n", m_outputWidth, m_outputHeight, m_outputChannels);
-            fstream << string(str);
-            sprintf(str, "ZeroPadding=%ls  maxTempMemSizeInSamples=%lu\n", m_zeroPadding? L"true" : L"false", m_maxTempMemSizeInSamples);
-            fstream << string(str);
-        }
-
-        void SetmMaxTempMemSizeInSamples(const size_t maxTempMemSizeInSamples)
-        {
-            m_maxTempMemSizeInSamples = maxTempMemSizeInSamples;
-        }
-
-    private:
-        static void WINAPI ComputeInputPartialOverWeight(const ConvolutionNode<ElemType>* pConv, Matrix<ElemType> &gradientValues, 
-            Matrix<ElemType> &inputGradientValues, const Matrix<ElemType> &/*input0*/, const Matrix<ElemType> &input1, Matrix<ElemType> &tempMatrix, const bool inLoop=false)
-        {
-            ConvolutionParams convParam = pConv->GetConvolutionParams();
-
-            size_t packedInputRows = convParam.kernelWidth * convParam.kernelHeight * convParam.inputChannels;
-            size_t packedInputColsPerSample = convParam.outputWidth * convParam.outputHeight;
-            size_t outputSizePerChannel = packedInputColsPerSample;
-            //size_t packedInputDim = packedInputRows * packedInputColsPerSample; // size of each packed input sample
-            //size_t inputDim = convParam.inputWidth * convParam.inputHeight * convParam.inputChannels;  //size of each input sample
-
-            long batchSize = (long) input1.GetNumCols(); //right child is the input sample
-
-            long maxTempMemSizeInSamples = (long) (convParam.maxTempMemSizeInSamples == 0? batchSize : convParam.maxTempMemSizeInSamples);
-
-            //const Matrix<ElemType> & weightMatrix = input0;
-            //inputGradientValues.Resize(weightMatrix.GetNumRows(), weightMatrix.GetNumCols()); //should have been resized when preparing gradient computation
-
-            gradientValues.Reshape(convParam.outputChannels,  outputSizePerChannel * batchSize);  //reshape to match the longernal operation
-
-            long subBatchSize = min(batchSize, maxTempMemSizeInSamples); 
-            long numSubBatches = (batchSize+subBatchSize-1)/subBatchSize; 
-
-            if (numSubBatches == 1 && !inLoop)  //reuse packed input from evaluation step if it's not changed by either subbatch or recurrent steps.
-            {
-                Matrix<ElemType>::MultiplyAndAdd(gradientValues, false, tempMatrix, true, inputGradientValues);
-            }
-            else
-            {
-                for (long i=0; i<numSubBatches; i++) 
-                {
-                    long startSampleID = i*subBatchSize; 
-                    long endSampleID = min(batchSize, startSampleID + subBatchSize); 
-                    long smallBatchSize = endSampleID-startSampleID; 
-
-                    tempMatrix.Resize(packedInputRows, packedInputColsPerSample * smallBatchSize);
-                    Matrix<ElemType> inputSubBatch = input1.ColumnSlice(startSampleID, smallBatchSize);
-                    tempMatrix.AssignPackedConvolutionInput(inputSubBatch, 
-                                                                     convParam.inputWidth, convParam.inputHeight, convParam.inputChannels,
-                                                                     convParam.outputWidth, convParam.outputHeight, convParam.outputChannels,
-                                                                     convParam.kernelWidth, convParam.kernelHeight, convParam.horizontalSubsample, convParam.verticalSubsample, 
-                                                                     convParam.zeroPadding); 
-
-                    Matrix<ElemType> outputGradientSubBatch = gradientValues.ColumnSlice(startSampleID * outputSizePerChannel, smallBatchSize * outputSizePerChannel);
-                    Matrix<ElemType>::MultiplyAndAdd(outputGradientSubBatch, false, tempMatrix, true, inputGradientValues);
-                }
-            }
-
-            gradientValues.Reshape(convParam.outputChannels * outputSizePerChannel, batchSize);  //change back
-        }
-
-        //compute gradient over the packed input and then convert the result to the original input
-        static void WINAPI ComputeInputPartialOverInputFeature(const ConvolutionNode<ElemType>* pConv, Matrix<ElemType> &gradientValues, const Matrix<ElemType> &inputGradientValues, const Matrix<ElemType> &input0, const Matrix<ElemType> &input1, Matrix<ElemType> &tempMatrix)
-        {
-            
-            ConvolutionParams convParam = pConv->GetConvolutionParams();
-            size_t packedInputRows = convParam.kernelWidth * convParam.kernelHeight * convParam.inputChannels;
-            size_t packedInputColsPerSample = convParam.outputWidth * convParam.outputHeight;
-            size_t outputSizePerChannel = packedInputColsPerSample;
-            //size_t packedInputDim = packedInputRows * packedInputColsPerSample; // size of each packed input sample
-            //size_t inputDim = convParam.inputWidth * convParam.inputHeight * convParam.inputChannels;  //size of each input sample
-
-            long batchSize = (long) input1.GetNumCols(); //right child is the input sample
-
-            long maxTempMemSizeInSamples = (long) (convParam.maxTempMemSizeInSamples == 0? batchSize : convParam.maxTempMemSizeInSamples);
-
-            const Matrix<ElemType> & weightMatrix = input0;
-
-            gradientValues.Reshape(convParam.outputChannels,  outputSizePerChannel * batchSize);  //reshape to match the longernal operation
-
-            long subBatchSize = min(batchSize, maxTempMemSizeInSamples); 
-            long numSubBatches = (batchSize+subBatchSize-1)/subBatchSize; 
-
-            for (long i=0; i<numSubBatches; i++) 
-            {
-                long startSampleID = i*subBatchSize; 
-                long endSampleID = min(batchSize, startSampleID + subBatchSize); 
-                long smallBatchSize = endSampleID-startSampleID; 
-
-                tempMatrix.Resize(packedInputRows, packedInputColsPerSample * smallBatchSize);
-                Matrix<ElemType> outputGradientSubBatch = gradientValues.ColumnSlice(startSampleID * outputSizePerChannel, smallBatchSize * outputSizePerChannel);
-                Matrix<ElemType>::Multiply(weightMatrix, true, outputGradientSubBatch, false,  tempMatrix);
-
-                Matrix<ElemType> inputGradientSubBatch = inputGradientValues.ColumnSlice(startSampleID, smallBatchSize);
-                tempMatrix.UnpackConvolutionInput(inputGradientSubBatch, 
-                                                                 convParam.inputWidth, convParam.inputHeight, convParam.inputChannels,
-                                                                 convParam.outputWidth, convParam.outputHeight, convParam.outputChannels,
-                                                                 convParam.kernelWidth, convParam.kernelHeight, convParam.horizontalSubsample, convParam.verticalSubsample, 
-                                                                 convParam.zeroPadding); 
-            }
-
-            gradientValues.Reshape(convParam.outputChannels * outputSizePerChannel, batchSize);  //change back
-        }
-        
-
-    private:
-        size_t m_kernelWidth, m_kernelHeight;
-        size_t m_horizontalSubsample, m_verticalSubsample;
-        bool m_zeroPadding;
-
-        Matrix<ElemType> m_tempMatrix; 
-        size_t m_maxTempMemSizeInSamples; // can change during runtime
-    };
-
-    template class ConvolutionNode<float>; 
-    template class ConvolutionNode<double>;
-
-    struct PoolParams
-    {
-        size_t inputWidth, inputHeight, inputChannels;
-        size_t windowWidth, windowHeight;
-        size_t horizontalSubsample, verticalSubsample;
-        size_t outputWidth, outputHeight, outputChannels;
-        size_t inputSizePerSample, outputSizePerSample;
-    };
-
-    //Max Pooling: support multi channel
-    //assume each column is an input sample. Each sample is stored in  (r00, g00, b00, r01, g01, b01, r10, g10, b10, r11, g11, b11)
-    template<class ElemType>
-    class MaxPoolingNode : public ComputationNode<ElemType>
-    {
-        UsingComputationNodeMembers;
-    public:
-        MaxPoolingNode( const size_t windowWidth, const size_t windowHeight, 
-                        const size_t horizontalSubsample, const size_t verticalSubsample, 
-                        const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId),
-                          m_windowWidth(windowWidth), m_windowHeight(windowHeight),
-                          m_horizontalSubsample(horizontalSubsample), m_verticalSubsample(verticalSubsample)                       
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            m_deviceId = deviceId;
-            MoveMatricesToDevice(deviceId);
-            InitRecurrentNode();
-        }
-                
-        MaxPoolingNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            LoadFromFile(fstream, modelVersion, deviceId);
-        }
-                
-        virtual void SaveToFile(File& fstream) const
-        {
-            ComputationNode<ElemType>::SaveToFile(fstream);
-
-            fstream << m_windowWidth << m_windowHeight << m_horizontalSubsample << m_verticalSubsample; 
-        }
-
-        virtual void LoadFromFile(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX)
-        {
-            ComputationNode<ElemType>::LoadFromFile(fstream, modelVersion, deviceId);
-
-            fstream >> m_windowWidth >> m_windowHeight >> m_horizontalSubsample >> m_verticalSubsample; 
-        }
-
-        virtual void CopyTo(const ComputationNodePtr nodeP, const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            ComputationNode<ElemType>::CopyTo(nodeP, newName, flags);
-            MaxPoolingNode<ElemType>* node = (MaxPoolingNode<ElemType>*) nodeP;
-
-            if (flags & CopyNodeFlags::copyNodeValue)
-            {
-                node->m_inputWidth = m_inputWidth;
-                node->m_inputHeight = m_inputHeight;
-                node->m_inputChannels = m_inputChannels;
-
-                node->m_windowWidth = m_windowWidth;
-                node->m_windowHeight = m_windowHeight;
-
-                node->m_horizontalSubsample = m_horizontalSubsample;
-                node->m_verticalSubsample = m_verticalSubsample;
-
-                node->m_outputWidth = m_outputWidth;
-                node->m_outputHeight = m_outputHeight;
-                node->m_outputChannels = m_outputChannels;
-
-                node->m_inputSizePerSample = m_inputSizePerSample;
-                node->m_outputSizePerSample = m_outputSizePerSample;
-            }
-        }
-        // copy constructor
-        MaxPoolingNode(const MaxPoolingNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags) : ComputationNode<ElemType>(node->m_deviceId)
-        {
-            node->CopyTo(this, newName, flags);
-        }
-
-        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            const std::wstring& name = (newName == L"")?NodeName():newName;
-                
-            ComputationNodePtr node = new MaxPoolingNode<ElemType>(this, name, flags);
-            return node;
-        }
-
-        virtual const std::wstring OperationName() const {return TypeName();}
-        static const std::wstring TypeName() {return L"MaxPooling";}
-
-        PoolParams GetPoolParams() const
-        {
-            PoolParams poolParams;
-            poolParams.inputWidth = m_inputWidth;
-            poolParams.inputHeight = m_inputHeight;
-            poolParams.inputChannels = m_inputChannels;
-
-            poolParams.windowWidth = m_windowWidth;
-            poolParams.windowHeight = m_windowHeight;
-
-            poolParams.horizontalSubsample = m_horizontalSubsample;
-            poolParams.verticalSubsample = m_verticalSubsample;
-
-            poolParams.outputWidth = m_outputWidth;
-            poolParams.outputHeight = m_outputHeight;
-            poolParams.outputChannels = m_outputChannels;
-
-            poolParams.inputSizePerSample = m_inputSizePerSample;
-            poolParams.outputSizePerSample = m_outputSizePerSample;
-            return poolParams;
-        }
-
-        virtual void ComputeInputPartial(const size_t inputIndex)
-        {
-            if (inputIndex > 0)
-                throw std::invalid_argument("MaxPooling operation only takes one inputs.");
-
-            ComputeInputPartialS(this, GradientValues(), Inputs(0)->GradientValues(), Inputs(0)->FunctionValues(), FunctionValues());
-        }
-
-        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq) 
-        {
-            if (inputIndex > 0)
-                throw std::invalid_argument("MaxPooling operation only takes one inputs.");
-
-            Matrix<ElemType> sliceInput0Grad = Inputs(0)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            Matrix<ElemType> sliceInput0Value = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            ComputeInputPartialS(this, sliceOutputGrad, sliceInput0Grad, sliceInput0Value, sliceOutputValue);
-        }
-
-        static void WINAPI ComputeInputPartialS(const MaxPoolingNode<ElemType>* ppool, const Matrix<ElemType> &gradientValues, Matrix<ElemType> &inputGradientValues, const Matrix<ElemType> &input0, const Matrix<ElemType> &functionValues)
-        {
-            PoolParams poolParams = ppool->GetPoolParams();
-
-            inputGradientValues.AddMaxPoolingGradient(gradientValues, input0, functionValues, poolParams.inputChannels,
-                                                    poolParams.inputWidth, poolParams.inputHeight, poolParams.inputSizePerSample, 
-                                                    poolParams.outputWidth, poolParams.outputHeight, poolParams.outputSizePerSample, 
-                                                    poolParams.windowWidth, poolParams.windowHeight, poolParams.horizontalSubsample, poolParams.verticalSubsample);
-        }
-
-        virtual void EvaluateThisNode()  
-        {
-#if NANCHECK
-            Inputs(0)->FunctionValues().HasNan("MaxPooling-input0");
-#endif
-            EvaluateThisNodeS(this, FunctionValues(), Inputs(0)->FunctionValues());
-#if NANCHECK
-            m_functionValues.HasNan("MaxPooling");
-#endif
-        }
-
-        virtual void EvaluateThisNode(const size_t timeIdxInSeq) 
-        {
-            Matrix<ElemType> sliceInput0Value = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            EvaluateThisNodeS(this, sliceOutputValue, sliceInput0Value);
-        }
-
-        static void WINAPI EvaluateThisNodeS(const MaxPoolingNode<ElemType>* ppool, Matrix<ElemType> &functionValues, const Matrix<ElemType> &input0)
-        {
-            PoolParams poolParams = ppool->GetPoolParams();
-            functionValues.AssignMaxPoolingResult(input0, poolParams.inputChannels,
-                                                 poolParams.inputWidth, poolParams.inputHeight, poolParams.inputSizePerSample, 
-                                                 poolParams.outputWidth, poolParams.outputHeight, poolParams.outputSizePerSample, 
-                                                 poolParams.windowWidth, poolParams.windowHeight, poolParams.horizontalSubsample, poolParams.verticalSubsample);
-        }
-
-        virtual void Validate()
-        {
-            PrintSelfBeforeValidation();
-
-            if (m_children.size() != 1) 
-                throw std::logic_error("MaxPoolingNode requires one input.");
-
-            if (m_horizontalSubsample > m_windowWidth || m_verticalSubsample > m_windowHeight)
-                throw std::invalid_argument("MaxPoolingNode: horizontalSubsample must <= windowWidth and verticalSubsample must <= windowHeight.");
-
-            CopyImageSizeFromInputs();
-
-            m_inputSizePerSample = m_inputWidth * m_inputHeight * m_inputChannels;
-            m_outputSizePerSample = m_outputWidth * m_outputHeight * m_outputChannels;
-
-            if (Inputs(0)->OperationName() == LearnableParameter<ElemType>::TypeName() && Inputs(0)->FunctionValues().GetNumRows() == 0)
-            {
-                Inputs(0)->FunctionValues().Resize(m_inputSizePerSample, Inputs(0)->FunctionValues().GetNumCols());
-            }
-
-            if (m_children[0]->FunctionValues().GetNumRows() != m_inputSizePerSample)
-            {
-                msra::strfun::strprintf msg("each column of input to the MaxPooling node %ls is a sample and should have dimension %d, which is inputWidth * inputHeight * inputChannels", 
-                    NodeName().c_str(), m_inputSizePerSample);
-                throw std::logic_error(msg.c_str());            
-            }
-            
-            if (Inputs(0)->FunctionValues().GetNumElements() == 0)
-                throw std::logic_error("MaxPoolingNode operation: the input node has 0 element.");
-
-            m_functionValues.Resize(m_outputSizePerSample, m_children[0]->FunctionValues().GetNumCols());
-        }
-
-        virtual void CopyImageSizeFromInputs()
-        {
-            CopyImageSizeFromInput(0, false);
-
-            if (m_inputWidth < m_windowWidth || m_inputHeight < m_windowHeight)
-                throw std::invalid_argument("MaxPoolingNode: inputWidth must >= windowWidth and inputHeight must >= windowHeight.");
-
-            m_outputWidth = (m_inputWidth-m_windowWidth)/m_horizontalSubsample + 1;
-            m_outputHeight = (m_inputHeight-m_windowHeight)/m_verticalSubsample + 1;
-            m_outputChannels = m_inputChannels;
-        }
-
-        virtual void AttachInputs(const ComputationNodePtr inputFeature) 
-        {
-            m_children.resize(1);
-            m_children[0] = inputFeature;
-        }
-
-        virtual void DumpNodeInfo(const bool printValues, File& fstream) const
-        {
-            ComputationNode<ElemType>::DumpNodeInfo(printValues, fstream);
-
-            char str[4096];
-            sprintf(str, "Input[Width:%lu, Height:%lu, Channels:%lu]  \n", m_inputWidth, m_inputHeight, m_inputChannels);
-            fstream << string(str);
-            sprintf(str, "PoolingWindow[Width:%lu, Height:%lu]  SubSampling[Horizontal:%lu, Vertical:%lu]\n", m_windowWidth, m_windowHeight, m_horizontalSubsample, m_verticalSubsample);
-            fstream << string(str);
-            sprintf(str, "Output[Width:%lu, Height:%lu, Channels:%lu]  \n", m_outputWidth, m_outputHeight, m_outputChannels);
-            fstream << string(str);
-            sprintf(str, "TotalSizePerSample[Input:%lu, Output:%lu]  \n", m_inputSizePerSample, m_outputSizePerSample);
-            fstream << string(str);
-        }
-
-    private:
-        size_t m_windowWidth, m_windowHeight;
-        size_t m_horizontalSubsample, m_verticalSubsample;
-        size_t m_inputSizePerSample, m_outputSizePerSample;
-    };
-
-    template class MaxPoolingNode<float>; 
-    template class MaxPoolingNode<double>;    
-
-    //Average Pooling: support multi channel
-    //assume each column is an input sample. Each sample is stored in  (r00, g00, b00, r01, g01, b01, r10, g10, b10, r11, g11, b11)
-    template<class ElemType>
-    class AveragePoolingNode : public ComputationNode<ElemType>
-    {
-        UsingComputationNodeMembers;
-    public:
-        AveragePoolingNode(const size_t windowWidth, const size_t windowHeight, 
-                        const size_t horizontalSubsample, const size_t verticalSubsample, 
-                        const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId),
-                          m_windowWidth(windowWidth), m_windowHeight(windowHeight),
-                          m_horizontalSubsample(horizontalSubsample), m_verticalSubsample(verticalSubsample)                     
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            m_deviceId = deviceId;
-            MoveMatricesToDevice(deviceId);
-            InitRecurrentNode();
-        }
-
-        AveragePoolingNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            LoadFromFile(fstream, modelVersion, deviceId);
-        }                
-                
-        virtual void SaveToFile(File& fstream) const
-        {
-            ComputationNode<ElemType>::SaveToFile(fstream);
-
-            fstream << m_windowWidth << m_windowHeight << m_horizontalSubsample << m_verticalSubsample; 
-        }
-
-        virtual void LoadFromFile(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX)
-        {
-            ComputationNode<ElemType>::LoadFromFile(fstream, modelVersion, deviceId);
-
-            fstream >> m_windowWidth >> m_windowHeight >> m_horizontalSubsample >> m_verticalSubsample; 
-        }
-
-        virtual void CopyTo(const ComputationNodePtr nodeP, const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            ComputationNode<ElemType>::CopyTo(nodeP, newName, flags);
-            AveragePoolingNode<ElemType>* node = (AveragePoolingNode<ElemType>*) nodeP;
-
-            if (flags & CopyNodeFlags::copyNodeValue)
-            {
-                node->m_inputWidth = m_inputWidth;
-                node->m_inputHeight = m_inputHeight;
-                node->m_inputChannels = m_inputChannels;
-
-                node->m_windowWidth = m_windowWidth;
-                node->m_windowHeight = m_windowHeight;
-
-                node->m_horizontalSubsample = m_horizontalSubsample;
-                node->m_verticalSubsample = m_verticalSubsample;
-
-                node->m_outputWidth = m_outputWidth;
-                node->m_outputHeight = m_outputHeight;
-                node->m_outputChannels = m_outputChannels;
-
-                node->m_inputSizePerSample = m_inputSizePerSample;
-                node->m_outputSizePerSample = m_outputSizePerSample;
-            }
-        }
-
-        // copy constructor
-        AveragePoolingNode(const AveragePoolingNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags) : ComputationNode<ElemType>(node->m_deviceId)
-        {
-            node->CopyTo(this, newName, flags);
-        }
-
-        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            const std::wstring& name = (newName == L"")?NodeName():newName;
-                
-            ComputationNodePtr node = new AveragePoolingNode<ElemType>(this, name, flags);
-            return node;
-        }
-
-        virtual const std::wstring OperationName() const {return TypeName();}
-        static const std::wstring TypeName() {return L"AveragePooling";}
-        PoolParams GetPoolParams() const
-        {
-            PoolParams poolParams;
-            poolParams.inputWidth = m_inputWidth;
-            poolParams.inputHeight = m_inputHeight;
-            poolParams.inputChannels = m_inputChannels;
-
-            poolParams.windowWidth = m_windowWidth;
-            poolParams.windowHeight = m_windowHeight;
-
-            poolParams.horizontalSubsample = m_horizontalSubsample;
-            poolParams.verticalSubsample = m_verticalSubsample;
-
-            poolParams.outputWidth = m_outputWidth;
-            poolParams.outputHeight = m_outputHeight;
-            poolParams.outputChannels = m_outputChannels;
-
-            poolParams.inputSizePerSample = m_inputSizePerSample;
-            poolParams.outputSizePerSample = m_outputSizePerSample;
-            return poolParams;
-        }
-
-        virtual void ComputeInputPartial(const size_t inputIndex)
-        {
-            if (inputIndex > 0)
-                throw std::invalid_argument("AveragePooling operation only takes one inputs.");
-
-            ComputeInputPartialS(this, GradientValues(), Inputs(0)->GradientValues());
-        }
-
-        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq) 
-        {
-            if (inputIndex > 0)
-                throw std::invalid_argument("AveragePooling operation only takes one inputs.");
-
-            Matrix<ElemType> sliceInput0Grad = Inputs(0)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            ComputeInputPartialS(this, sliceOutputGrad, sliceInput0Grad);
-        }
-
-        static void WINAPI ComputeInputPartialS(const AveragePoolingNode<ElemType>* ppool, const Matrix<ElemType> &gradientValues, Matrix<ElemType> &inputGradientValues)
-        {
-            PoolParams poolParams = ppool->GetPoolParams();
-
-            inputGradientValues.AddAveragePoolingGradient(gradientValues, poolParams.inputChannels,
-                                                    poolParams.inputWidth, poolParams.inputHeight, poolParams.inputSizePerSample, 
-                                                    poolParams.outputWidth, poolParams.outputHeight, poolParams.outputSizePerSample, 
-                                                    poolParams.windowWidth, poolParams.windowHeight, poolParams.horizontalSubsample, poolParams.verticalSubsample);
-        }
-
-        virtual void EvaluateThisNode()  
-        {
-#if NANCHECK
-            Inputs(0)->FunctionValues().HasNan("AveragePooling-input0");
-#endif
-            EvaluateThisNodeS(this, FunctionValues(), Inputs(0)->FunctionValues());
-#if NANCHECK
-            m_functionValues.HasNan("AveragePooling");
-#endif
-        }
-
-        virtual void EvaluateThisNode(const size_t timeIdxInSeq) 
-        {
-            Matrix<ElemType> sliceInput0Value = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            EvaluateThisNodeS(this, sliceOutputValue, sliceInput0Value);
-        }
-
-        static void WINAPI EvaluateThisNodeS(const AveragePoolingNode<ElemType>* ppool, Matrix<ElemType> &functionValues, const Matrix<ElemType> &input0)
-        {
-            PoolParams poolParams = ppool->GetPoolParams();
-            
-            functionValues.AssignAveragePoolingResult(input0, poolParams.inputChannels,
-                                                 poolParams.inputWidth, poolParams.inputHeight, poolParams.inputSizePerSample, 
-                                                 poolParams.outputWidth, poolParams.outputHeight, poolParams.outputSizePerSample, 
-                                                 poolParams.windowWidth, poolParams.windowHeight, poolParams.horizontalSubsample, poolParams.verticalSubsample);
-        }
-
-        virtual void Validate()
-        {
-            PrintSelfBeforeValidation();
-
-            if (m_children.size() != 1) 
-                throw std::logic_error("AveragePoolingNode requires one input.");
-
-            if (m_horizontalSubsample > m_windowWidth || m_verticalSubsample > m_windowHeight)
-                throw std::invalid_argument("AveragePoolingNode: horizontalSubsample must <= windowWidth and verticalSubsample must <= windowHeight.");
-
-            CopyImageSizeFromInputs();
-
-            m_inputSizePerSample = m_inputWidth * m_inputHeight * m_inputChannels;
-            m_outputSizePerSample = m_outputWidth * m_outputHeight * m_outputChannels;
-
-            if (Inputs(0)->OperationName() == LearnableParameter<ElemType>::TypeName() && Inputs(0)->FunctionValues().GetNumRows() == 0)
-            {
-                Inputs(0)->FunctionValues().Resize(m_inputSizePerSample, Inputs(0)->FunctionValues().GetNumCols());
-            }
-
-            if (m_children[0]->FunctionValues().GetNumRows() != m_inputSizePerSample)
-            {
-                msra::strfun::strprintf msg("each column of input to the AveragePooling node %ls is a sample and should have dimension %d, which is inputWidth * inputHeight * inputChannels", 
-                    NodeName().c_str(), m_inputSizePerSample);
-                throw std::logic_error(msg.c_str());            
-            }
-                        
-            if (Inputs(0)->FunctionValues().GetNumElements() == 0)
-                throw std::logic_error("AveragePoolingNode operation: the input node has 0 element.");
-
-            FunctionValues().Resize(m_outputSizePerSample, m_children[0]->FunctionValues().GetNumCols());
-        }
-
-        virtual void CopyImageSizeFromInputs()
-        {
-            CopyImageSizeFromInput(0, false);
-
-            if (m_inputWidth < m_windowWidth || m_inputHeight < m_windowHeight)
-                throw std::invalid_argument("AveragePoolingNode: inputWidth must >= windowWidth and inputHeight must >= windowHeight.");
-
-            m_outputWidth = (m_inputWidth-m_windowWidth)/m_horizontalSubsample + 1;
-            m_outputHeight = (m_inputHeight-m_windowHeight)/m_verticalSubsample + 1;
-            m_outputChannels = m_inputChannels;
-        }
-
-        virtual void AttachInputs(const ComputationNodePtr inputFeature) 
-        {
-            m_children.resize(1);
-            m_children[0] = inputFeature;
-        }
-
-        virtual void DumpNodeInfo(const bool printValues, File& fstream) const
-        {
-            ComputationNode<ElemType>::DumpNodeInfo(printValues, fstream);
-
-            char str[4096];
-            sprintf(str, "Input[Width:%lu, Height:%lu, Channels:%lu]  \n", m_inputWidth, m_inputHeight, m_inputChannels);
-            fstream << string(str);
-            sprintf(str, "PoolingWindow[Width:%lu, Height:%lu]  SubSample[Horizontal:%lu, Vertical:%lu]\n", m_windowWidth, m_windowHeight, m_horizontalSubsample, m_verticalSubsample);
-            fstream << string(str);
-            sprintf(str, "Output[Width:%lu, Height:%lu, Channels:%lu]  \n", m_outputWidth, m_outputHeight, m_outputChannels);
-            fstream << string(str);
-            sprintf(str, "TotalSizePerSample[Input:%lu, Output:%lu]\n", m_inputSizePerSample, m_outputSizePerSample);
-            fstream << string(str);
-        }
-
-    private:
-        size_t m_windowWidth, m_windowHeight;
-        size_t m_horizontalSubsample, m_verticalSubsample;
-        size_t m_inputSizePerSample, m_outputSizePerSample;
-    };
-
-    template class AveragePoolingNode<float>; 
-    template class AveragePoolingNode<double>;    
-
-    //calculates: the log likelihood of a feature given GMM parameters
-    template<class ElemType>
-    class GMMLogLikelihoodNode : public ComputationNode<ElemType>
-    {
-        UsingComputationNodeMembers;
-    public:
-        GMMLogLikelihoodNode(const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX, const std::wstring name = L"")
-            : ComputationNode<ElemType>(deviceId), m_prior(deviceId), m_normedDeviation(deviceId), m_normedDeviationVectors(deviceId), m_stddev(deviceId), m_posterior(deviceId), m_temp(deviceId)
-        {
-            m_nodeName = (name == L"" ? CreateUniqNodeName() : name);
-            m_deviceId = deviceId;
-            MoveMatricesToDevice(deviceId);
-            InitRecurrentNode();
-        }
-
-        GMMLogLikelihoodNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX, const std::wstring name = L"")
-            : ComputationNode<ElemType>(deviceId), m_prior(deviceId), m_normedDeviation(deviceId), m_normedDeviationVectors(deviceId), m_stddev(deviceId), m_posterior(deviceId), m_temp(deviceId)
-        {
-            m_nodeName = (name == L"" ? CreateUniqNodeName() : name);
-            LoadFromFile(fstream, modelVersion, deviceId);
-        }
-
-        // copy constructor
-        GMMLogLikelihoodNode(const GMMLogLikelihoodNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags)
-            : ComputationNode<ElemType>(node->m_deviceId), m_prior(node->m_deviceId), m_normedDeviation(node->m_deviceId), m_normedDeviationVectors(node->m_deviceId),
-            m_stddev(node->m_deviceId), m_posterior(node->m_deviceId), m_temp(m_deviceId)
-        {
-            node->CopyTo(this, newName, flags);
-        }
-
-        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            const std::wstring& name = (newName == L"") ? NodeName() : newName;
-
-            ComputationNodePtr node = new GMMLogLikelihoodNode<ElemType>(this, name, flags);
-            return node;
-        }
-
-        virtual const std::wstring OperationName() const { return TypeName(); }
-        static const std::wstring TypeName() { return L"GMMLogLikelihood"; }
-
-        virtual void ComputeInputPartial(const size_t inputIndex)
-        {
-            switch (inputIndex)
-            {
-            case 0:
-                ComputeInputPartialUnnormedPrior(Inputs(0)->GradientValues(), m_gradientValues, m_prior, m_posterior, m_temp);
-                break;
-            case 1:
-                ComputeInputPartialMean(Inputs(1)->GradientValues(), m_gradientValues, m_normedDeviationVectors, m_posterior, m_temp);
-                break;
-            case 2:
-                ComputeInputPartialLogStddev(Inputs(2)->GradientValues(), m_gradientValues, m_normedDeviation, m_posterior, m_temp);
-                break;
-            case 3:
-                ComputeInputPartialFeature(Inputs(3)->GradientValues(), m_gradientValues, m_normedDeviationVectors, m_posterior, m_temp);
-                break;
-            default:
-                throw std::invalid_argument("GMMLogLikelihoodNode only takes four inputs.");
-            }
-        }
-
-        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
-        {
-            //get the right slice 
-            size_t startIndex = timeIdxInSeq * m_samplesInRecurrentStep;
-
-            size_t colsPrior = Inputs(0)->FunctionValues().GetNumCols();
-
-            Matrix<ElemType> sliceGradientValue = m_gradientValues.ColumnSlice(startIndex, m_samplesInRecurrentStep);
-            Matrix<ElemType> slicePosterior = m_posterior.ColumnSlice(startIndex, m_samplesInRecurrentStep);
-                
-            switch (inputIndex)
-            {
-            case 0:
-                {
-                    if (colsPrior == 1)
-                        ComputeInputPartialUnnormedPrior(Inputs(0)->GradientValues(), sliceGradientValue, m_prior, slicePosterior, m_temp);
-                    else
-                    {
-                        Matrix<ElemType> sliceUnnormedPriorGradient = Inputs(0)->GradientValues().ColumnSlice(startIndex, m_samplesInRecurrentStep);
-                        Matrix<ElemType> slicePrior = m_prior.ColumnSlice(startIndex, m_samplesInRecurrentStep);
-                        ComputeInputPartialUnnormedPrior(sliceUnnormedPriorGradient, sliceGradientValue, slicePrior, slicePosterior, m_temp);
-                    }
-                }
-                break;
-            case 1:
-                {
-                      Matrix<ElemType> sliceNormedDeviationVectors = m_normedDeviationVectors.ColumnSlice(startIndex, m_samplesInRecurrentStep);
-                      if (colsPrior == 1)
-                        ComputeInputPartialMean(Inputs(1)->GradientValues(), sliceGradientValue, sliceNormedDeviationVectors, slicePosterior, m_temp);
-                    else
-                    {
-                        Matrix<ElemType> sliceMeanGradient = Inputs(1)->GradientValues().ColumnSlice(startIndex, m_samplesInRecurrentStep);
-                        ComputeInputPartialMean(sliceMeanGradient, sliceGradientValue, sliceNormedDeviationVectors, slicePosterior, m_temp);
-                    }
-                }
-                break;
-            case 2:
-                {
-                    Matrix<ElemType> sliceNormedDeviation = m_normedDeviation.ColumnSlice(startIndex, m_samplesInRecurrentStep);
-                    if (colsPrior == 1)
-                        ComputeInputPartialLogStddev(Inputs(2)->GradientValues(), sliceGradientValue, sliceNormedDeviation, slicePosterior, m_temp);
-                    else
-                    {
-                        Matrix<ElemType> sliceLotStddevGradient = Inputs(2)->GradientValues().ColumnSlice(startIndex, m_samplesInRecurrentStep);
-                        ComputeInputPartialLogStddev(sliceLotStddevGradient, sliceGradientValue, sliceNormedDeviation, slicePosterior, m_temp);
-                    }
-                }
-                break;
-            case 3:
-                {
-                    Matrix<ElemType> sliceNormedDeviationVectors = m_normedDeviationVectors.ColumnSlice(startIndex, m_samplesInRecurrentStep);
-                    Matrix<ElemType> sliceFeatureGradient = Inputs(3)->GradientValues().ColumnSlice(startIndex, m_samplesInRecurrentStep);
-                    ComputeInputPartialFeature(sliceFeatureGradient, sliceGradientValue, sliceNormedDeviationVectors, slicePosterior, m_temp);
-                }
-                break;
-            default:
-                throw std::invalid_argument("GMMLogLikelihoodNode criterion only takes four inputs.");
-            }
-        }
-
-        static void WINAPI ComputeInputPartialUnnormedPrior(Matrix<ElemType>& unnormedPriorGradientValues, const Matrix<ElemType>& gradientValues,
-            const Matrix<ElemType>& prior, const Matrix<ElemType>& posterior, Matrix<ElemType>& temp)
-        {
-            temp.AssignDifferenceOf(posterior, prior);
-            temp.RowElementMultiplyWith(gradientValues);
-            if (prior.GetNumCols() == posterior.GetNumCols())
-            {
-                unnormedPriorGradientValues += temp; 
-            }
-            else if (prior.GetNumCols() == 1)
-            {
-                Matrix<ElemType>::MultiplyAndAdd(temp, false, ConstOnes(posterior.GetNumCols(), 1, unnormedPriorGradientValues.GetDeviceId()), false, unnormedPriorGradientValues);
-            }
-            else
-            {
-                throw std::runtime_error("GMMLogLikelihoodNode: UnnormedPrior should either have same number of columns as the features or have only one column.");
-            }
-        }
-
-        static void WINAPI ComputeInputPartialMean(Matrix<ElemType>& meanGradientValues, const Matrix<ElemType>& gradientValues, const Matrix<ElemType>& normedDeviationVectors,
-            Matrix<ElemType>& posterior, Matrix<ElemType>& temp)
-        {
-            size_t numComponent = posterior.GetNumRows(); 
-            size_t numSamples = posterior.GetNumCols();
-            size_t featureSize = normedDeviationVectors.GetNumRows() / numComponent;
-
-            temp.SetValue(normedDeviationVectors); //recall normedDeviationVectors <-- (x-u_c)/(stddev^2)
-            temp.Reshape(featureSize, numSamples* numComponent);
-
-            posterior.Reshape(1, numSamples* numComponent);
-            temp.RowElementMultiplyWith(posterior); //temp <-- posterior * (x-u_c)/(stddev^2)
-
-            posterior.Reshape(numComponent, numSamples);  //reshape back
-            temp.Reshape(featureSize * numComponent, numSamples); //reshape back
-
-            temp.RowElementMultiplyWith(gradientValues);
-
-            if (numSamples == meanGradientValues.GetNumCols())
-            {
-                meanGradientValues += temp;
-            }
-            else if (meanGradientValues.GetNumCols() == 1)
-            {
-                Matrix<ElemType>::MultiplyAndAdd(temp, false, ConstOnes(numSamples, 1, meanGradientValues.GetDeviceId()), false, meanGradientValues);
-            }
-            else
-            {
-                throw std::runtime_error("GMMLogLikelihoodNode: stddev should either have same number of columns as the features or have only one column.");
-            }
-        }
-
-        static void WINAPI ComputeInputPartialLogStddev(Matrix<ElemType>& logStddevGradientValues, const Matrix<ElemType>& gradientValues, const Matrix<ElemType>& normedDeviation,
-            const Matrix<ElemType>& posterior, Matrix<ElemType>& temp)
-        {
-            size_t numComponent = posterior.GetNumRows();
-            size_t numSamples = posterior.GetNumCols();
-
-            temp.AssignDifferenceOf(normedDeviation, (ElemType)numComponent);
-            temp.ElementMultiplyWith(posterior);
-            temp.RowElementMultiplyWith(gradientValues);
-            if (logStddevGradientValues.GetNumCols() == numSamples)
-            {
-                logStddevGradientValues += temp;
-            }
-            else if (logStddevGradientValues.GetNumCols() == 1)
-            {
-                Matrix<ElemType>::MultiplyAndAdd(temp, false, ConstOnes(numSamples, 1, logStddevGradientValues.GetDeviceId()), false, logStddevGradientValues);
-            }
-            else
-            {
-                throw std::runtime_error("GMMLogLikelihoodNode: stddev should either have same number of columns as the features or have only one column.");
-            }
-        }
-
-        static void WINAPI ComputeInputPartialFeature(Matrix<ElemType>& featureGradientValues, const Matrix<ElemType>& gradientValues, const Matrix<ElemType>& normedDeviationVectors,
-            Matrix<ElemType>& posterior, Matrix<ElemType>& temp)
-        {
-            size_t numComponent = posterior.GetNumRows();
-            size_t numSamples = posterior.GetNumCols();
-            size_t featureSize = normedDeviationVectors.GetNumRows() / numComponent;
-
-            temp.SetValue(normedDeviationVectors);
-            temp *= -1;
-            temp.Reshape(featureSize, numSamples* numComponent);
-            posterior.Reshape(1, numSamples* numComponent);
-            temp.RowElementMultiplyWith(posterior);
-
-            posterior.Reshape(numComponent, numSamples);
-            temp.Reshape(featureSize * numComponent, numSamples);
-            temp.RowElementMultiplyWith(gradientValues);
-
-            for (int i = 0; i < numComponent; i++)
-                featureGradientValues.AddWithRowSliceValuesOf(temp, i*featureSize, featureSize);
-        }
-
-        virtual void SetFunctionAndGradientSize(const int numSamples)
-        {
-            ComputationNode<ElemType>::SetFunctionAndGradientSize(numSamples);
-
-            size_t numComponents = Inputs(0)->FunctionValues().GetNumRows();
-            size_t colsPrior = Inputs(0)->FunctionValues().GetNumCols();
-            //size_t numSamples = Inputs(3)->FunctionValues().GetNumCols();
-            size_t featureSize = Inputs(3)->FunctionValues().GetNumRows();
-
-            m_prior.Resize(numComponents, colsPrior);
-            m_stddev.Resize(numComponents, colsPrior);
-            m_normedDeviation.Resize(numComponents, numSamples);
-            m_normedDeviationVectors.Resize(numComponents * featureSize, numSamples);
-            m_posterior.Resize(numComponents, numSamples);
-        }
-
-        //input0=unnormedPrior, input1=mean, input2=logstddev, input3=feature
-        virtual void EvaluateThisNode()
-        {
-            // all internal matrices will be automatically resized since all of them are assigned to a value so no resize is needed here.
-            EvaluateThisNodeS(FunctionValues(), Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues(), Inputs(2)->FunctionValues(), Inputs(3)->FunctionValues(), 
-                m_prior, m_stddev, m_normedDeviationVectors, m_normedDeviation, m_posterior, m_temp);
-        }
-
-        //input0=unnormedPrior, input1=mean, input2=logstddev, input3=feature
-        virtual void EvaluateThisNode(const size_t timeIdxInSeq)
-        {
-            size_t colsPrior = Inputs(0)->FunctionValues().GetNumCols();
-            size_t numSamples = Inputs(3)->FunctionValues().GetNumCols();
-
-            //get the right slice 
-            size_t startIndex = timeIdxInSeq * m_samplesInRecurrentStep;
-
-            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(startIndex, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceFeature = Inputs(3)->FunctionValues().ColumnSlice(startIndex, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceNormedDeviation = m_normedDeviation.ColumnSlice(startIndex, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceNormedDeviationVectors = m_normedDeviationVectors.ColumnSlice(startIndex, m_samplesInRecurrentStep);
-            Matrix<ElemType> slicePosterior = m_posterior.ColumnSlice(startIndex, m_samplesInRecurrentStep);
-
-            if (colsPrior == 1)
-            {
-                EvaluateThisNodeS(sliceOutputValue, Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues(), Inputs(2)->FunctionValues(), sliceFeature,
-                    m_prior, m_stddev, sliceNormedDeviationVectors, sliceNormedDeviation, slicePosterior, m_temp);
-            }
-            else if (colsPrior == numSamples)
-            {
-                Matrix<ElemType> sliceUnnormedPrior = Inputs(0)->FunctionValues().ColumnSlice(startIndex, m_samplesInRecurrentStep);
-                Matrix<ElemType> sliceMean = Inputs(1)->FunctionValues().ColumnSlice(startIndex, m_samplesInRecurrentStep);
-                Matrix<ElemType> sliceLogstddev = Inputs(2)->FunctionValues().ColumnSlice(startIndex, m_samplesInRecurrentStep);
-
-                Matrix<ElemType> slicePrior = m_prior.ColumnSlice(startIndex, m_samplesInRecurrentStep);
-                Matrix<ElemType> sliceStddev = m_stddev.ColumnSlice(startIndex, m_samplesInRecurrentStep);
-
-                EvaluateThisNodeS(sliceOutputValue, sliceUnnormedPrior, sliceMean, sliceLogstddev, sliceFeature,
-                    slicePrior, sliceStddev, sliceNormedDeviationVectors, sliceNormedDeviation, slicePosterior, m_temp);
-            }
-            else  //should not reach the code since validation should fail already
-            {
-                throw std::runtime_error("GMMLogLikelihoodNode: UnnormedPrior should either have same number of columns as the features or have only one column.");
-            }
-
-        }
-
-        //input0=unnormedPrior, input1=mean, input2=logstddev, input3=feature
-        //If we want to speed up we need to replace following code with a several specialized GPU functions
-        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, const Matrix<ElemType>& unnormedPrior, const Matrix<ElemType>& mean,  Matrix<ElemType>& logstddev,
-            const Matrix<ElemType>& feature, Matrix<ElemType>& prior, Matrix<ElemType>& stddev, Matrix<ElemType>& normedDeviationVectors,
-            Matrix<ElemType>& normedDeviation, Matrix<ElemType>& posterior, Matrix<ElemType>& temp)
-        {
-            int numComponent = unnormedPrior.GetNumRows();
-            size_t numSamples = feature.GetNumCols();
-            size_t featureDim = feature.GetNumRows();
-
-            //compute prior which is softmax of unnormedPrior
-            prior.AssignLogSoftmaxOf(unnormedPrior, true);  //log prior
-
-            prior.InplaceExp();
-
-            //compute stddev
-            stddev.AssignExpOf(logstddev);
-
-#if DUMPOUTPUT
-            unnormedPrior.Print("unnormedPrior", 0, min(5, unnormedPrior.GetNumRows() - 1), 0, min(10, unnormedPrior.GetNumCols() - 1));
-            mean.Print("mean", 0, min(5, mean.GetNumRows() - 1), 0, min(10, mean.GetNumCols() - 1));
-            logstddev.Print("logstddev", 0, min(5, logstddev.GetNumRows() - 1), 0, min(10, logstddev.GetNumCols() - 1));
-
-            prior.Print("prior", 0, min(5, prior.GetNumRows() - 1), 0, min(10, prior.GetNumCols() - 1));
-            stddev.Print("stddev", 0, min(5, stddev.GetNumRows() - 1), 0, min(10, stddev.GetNumCols() - 1));
-#endif
-
-            //compute normedDeviation <-- ||x-u_c||^2/(stddev^2)
-            normedDeviationVectors.AssignRepeatOf(feature, numComponent, 1);
-            normedDeviationVectors -= mean; //each column of the mean has multiple mean components
-            normedDeviationVectors.Reshape(featureDim, numSamples* numComponent);  //now each column is feature-mean_i
-
-            normedDeviation.AssignVectorNorm2Of(normedDeviationVectors, true);
-            normedDeviation ^= 2;
-            temp.AssignRepeatOf(stddev, 1, numSamples / stddev.GetNumCols());  //stddev.GetNumCols() is either 1 or =numSamples
-            temp.Reshape(1, temp.GetNumElements());  //one stddev value for each component for each sample
-            temp ^= 2;
-            normedDeviation.ElementDivideBy(temp);  //normedDeviation and temp have same dim (1, numSamples* numComponent)
-
-            //compute  normedDeviationVectors <-- (x-u_c)/(stddev^2)
-            normedDeviationVectors.RowElementDivideBy(temp);  //divide twice
-            normedDeviationVectors.Reshape(featureDim*numComponent, numSamples);  //reshape back
-
-            //compute per-component likelihood
-            posterior.AssignProductOf(-0.5f, normedDeviation); //posterior  <-- -||x-u_c||^2/(stddev^2)/2 and in (1, numSamples* numComponent) dim
-            temp.InplaceLog();
-            temp *= ((ElemType)numComponent / 2.0f); //temp <-- stddev^c and in (1, numSamples* numComponent) dim
-            posterior -= temp;  // posterior  <-- exp[-||x-u_c||^2/(stddev^2)/2]/(stddev^c)
-            posterior -= (ElemType)(numComponent / 2.0f*log(TWO_PI)); //likelihood for each component and sample is now computed and stored in posterior
-            posterior.InplaceExp(); //posterior  <-- exp(-||x-u_c||^2/(stddev^2)/2)
-
-            normedDeviation.Reshape(numComponent, numSamples);  //reshape back
-            posterior.Reshape(numComponent, numSamples);  //reshape back
-
-            //compute posterior <-- prior_i * likelihood_i
-            if (unnormedPrior.GetNumCols() == numSamples)  //each sample has different prior
-                posterior.ElementMultiplyWith(prior);
-            else  //all samples share the same prior
-                posterior.ColumnElementMultiplyWith(prior);
-
-            //compute GMM log-likelihood
-            Matrix<ElemType>::Multiply(ConstOnes(1, numComponent, posterior.GetDeviceId()), false, posterior, false, functionValues);  //functionValues <-- total likelihood
-            posterior.RowElementDivideBy(functionValues); //posterior <-- per-comp likelihood / total likelihood
-            functionValues.InplaceLog(); //log likelihood
-
-#if DUMPOUTPUT
-            temp.Print("temp", 0, min(5, temp.GetNumRows() - 1), 0, min(10, temp.GetNumCols() - 1));
-            normedDeviation.Print("normedDeviation", 0, min(5, normedDeviation.GetNumRows() - 1), 0, min(10, normedDeviation.GetNumCols() - 1));
-
-            posterior.Print("posterior", 0, min(5, posterior.GetNumRows() - 1), 0, min(10, posterior.GetNumCols() - 1));
-            functionValues.Print("functionValues", 0, min(5, functionValues.GetNumRows() - 1), 0, min(10, functionValues.GetNumCols() - 1));
-
-            functionValues.Print("GMMLogLikelihoodNode");
-#endif
-
-#if NANCHECK
-            functionValues.HasNan("GMMLogLikelihood");
-#endif
-        }
-
-        virtual void Validate()
-        {
-            PrintSelfBeforeValidation();
-
-            if (m_children.size() != 4)
-                throw std::logic_error("GMMLogLikelihoodNode requires four inputs.");
-
-            size_t rows[4], cols[4];
-            for (int i = 0; i < 4; i++)
-            {
-                rows[i] = Inputs(i)->FunctionValues().GetNumRows();
-                cols[i] = Inputs(i)->FunctionValues().GetNumCols();
-            }
-
-            if (cols[0] != cols[1] || cols[0] != cols[2])
-                throw std::logic_error("GMMLogLikelihoodNode: UnnormedPrior (first input), mean (second input), and logStddev (third input) should have same number of columns.");
-
-            if (cols[0] != 1 && cols[0] != cols[3])
-                throw std::logic_error("GMMLogLikelihoodNode: UnnormedPrior (first input) should either have same number of columns as the features (fourth input) or have only one column.");
-
-            if (rows[0] != rows[2])
-                throw std::logic_error("GMMLogLikelihoodNode: UnnormedPrior (first input) should have same dimension as logStddev (third input), i.e., all dimensions in each Gaussian component share the same stddev.");
-
-            if (rows[1] != rows[0]*rows[3])
-                throw std::logic_error("GMMLogLikelihoodNode: the number of rows in mean (second input) should equal rows(unnormedPrior(first input) * rows(feature(fourth input)).");
-
-            FunctionValues().Resize(1, cols[3]);
-            CopyImageSizeFromInputs();
-        }
-
-        virtual void CopyImageSizeFromInputs()
-        {
-            CopyImageSizeFromInput(3, false);
-
-            m_outputChannels = 1;
-            m_outputWidth = 1;
-            m_outputHeight = 1;
-        }
-
-        //leftNode should be the empirical
-        virtual void AttachInputs(const ComputationNodePtr unnormedPrior, const ComputationNodePtr mean, const ComputationNodePtr logStddev, const ComputationNodePtr feature)
-        {
-            m_children.resize(4);
-            m_children[0] = unnormedPrior;
-            m_children[1] = mean;
-            m_children[2] = logStddev;
-            m_children[3] = feature;
-        }
-
-        virtual void MoveMatricesToDevice(const DEVICEID_TYPE deviceId)
-        {
-            ComputationNode<ElemType>::MoveMatricesToDevice(deviceId);
-
-            if (deviceId != AUTOPLACEMATRIX)
-            {
-                if (m_prior.GetDeviceId() != deviceId)
-                {
-                    m_prior.TransferFromDeviceToDevice(m_prior.GetDeviceId(), deviceId, true);
-                }
-                if (m_normedDeviation.GetDeviceId() != deviceId)
-                {
-                    m_normedDeviation.TransferFromDeviceToDevice(m_normedDeviation.GetDeviceId(), deviceId, true);
-                }
-                if (m_normedDeviationVectors.GetDeviceId() != deviceId)
-                {
-                    m_normedDeviationVectors.TransferFromDeviceToDevice(m_normedDeviationVectors.GetDeviceId(), deviceId, true);
-                }
-                if (m_stddev.GetDeviceId() != deviceId)
-                {
-                    m_stddev.TransferFromDeviceToDevice(m_stddev.GetDeviceId(), deviceId, true);
-                }
-                if (m_posterior.GetDeviceId() != deviceId)
-                {
-                    m_posterior.TransferFromDeviceToDevice(m_posterior.GetDeviceId(), deviceId, true);
-                }
-            }
-        }
-
-        virtual void CopyTo(const ComputationNodePtr nodeP, const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            ComputationNode<ElemType>::CopyTo(nodeP, newName, flags);
-            GMMLogLikelihoodNode<ElemType>* node = (GMMLogLikelihoodNode<ElemType>*) nodeP;
-
-            if (flags & CopyNodeFlags::copyNodeValue)
-            {
-                node->m_prior = m_prior;
-                node->m_normedDeviation = m_normedDeviation;
-                node->m_normedDeviationVectors = m_normedDeviationVectors;
-                node->m_stddev = m_stddev;
-                node->m_posterior = m_posterior;
-            }
-        }
-
-    protected:
-        Matrix<ElemType> m_prior;
-        Matrix<ElemType> m_normedDeviation;
-        Matrix<ElemType> m_normedDeviationVectors;
-        Matrix<ElemType> m_stddev;
-        Matrix<ElemType> m_posterior;
-        Matrix<ElemType> m_temp;
-    };
-
-    template class GMMLogLikelihoodNode<float>;
-    template class GMMLogLikelihoodNode<double>;
-
     /**
     BatchModeNode is a derivative of ComputationNode.
     It additionally check if needs to process data in batch before processing its parent
diff --git a/MachineLearning/CNTK/ComputationNetwork.h b/MachineLearning/CNTK/ComputationNetwork.h
index 9e20f9065..db4ba007b 100644
--- a/MachineLearning/CNTK/ComputationNetwork.h
+++ b/MachineLearning/CNTK/ComputationNetwork.h
@@ -17,17 +17,24 @@
 #include <fstream>
 #include <sstream>
 #include <stdlib.h>
-#include "ComputationNode.h"
-#include "TrainingCriterionNodes.h"
-#include "CompositeComputationNodes.h"
-#include "EvaluationCriterionNodes.h"
-#include "File.h"
-#include "Matrix.h"
-#include "commandArgUtil.h"
 #include <iostream>
 #include <regex>
 #include <chrono>
 
+#include "File.h"
+#include "Matrix.h"
+#include "commandArgUtil.h" // for nocase_compare
+
+#include "ComputationNode.h"
+#include "InputAndParamNodes.h"
+#include "LinearAlgebraNodes.h"
+#include "NonlinearityNodes.h"
+#include "ConvolutionalNodes.h"
+#include "RecurrentNodes.h"
+#include "TrainingCriterionNodes.h"
+#include "CompositeComputationNodes.h"
+#include "EvaluationCriterionNodes.h"
+
 namespace Microsoft { namespace MSR { namespace CNTK {
     template<class ElemType>
     class ComputationNetwork
diff --git a/MachineLearning/CNTK/ComputationNetworkHelper.h b/MachineLearning/CNTK/ComputationNetworkHelper.h
index f0973cac4..5bec06c2c 100644
--- a/MachineLearning/CNTK/ComputationNetworkHelper.h
+++ b/MachineLearning/CNTK/ComputationNetworkHelper.h
@@ -5,17 +5,16 @@
 //
 #pragma once
 
-#include "ComputationNetwork.h"
-#include "DataReader.h"
 #include <vector>
 #include <string>
 #include <stdexcept>
+#include <fstream>
+
 #include "Basics.h"
 #include "fileutil.h"
-#include "commandArgUtil.h"
-//#include <Windows.h>
-//#include <WinBase.h>
-#include <fstream>
+
+#include "ComputationNetwork.h"
+#include "DataReader.h"
 
 using namespace std;
 
diff --git a/MachineLearning/CNTK/ComputationNode.cpp b/MachineLearning/CNTK/ComputationNode.cpp
index 93dab5d38..88c8b6f0f 100644
--- a/MachineLearning/CNTK/ComputationNode.cpp
+++ b/MachineLearning/CNTK/ComputationNode.cpp
@@ -7,9 +7,7 @@
 #define _CRT_SECURE_NO_WARNINGS // "secure" CRT not available on all platforms  --add this at the top of all CPP files that give "function or variable may be unsafe" warnings
 
 #include "ComputationNode.h"
-#include "SimpleEvaluator.h"
-#include "IComputationNetBuilder.h"
-#include "SGD.h"
+#include "InputAndParamNodes.h"
 
 namespace Microsoft { namespace MSR { namespace CNTK {
 
diff --git a/MachineLearning/CNTK/ComputationNode.h b/MachineLearning/CNTK/ComputationNode.h
index 42c76f827..9cd84b91b 100644
--- a/MachineLearning/CNTK/ComputationNode.h
+++ b/MachineLearning/CNTK/ComputationNode.h
@@ -14,11 +14,13 @@
 #include <memory>
 #include <algorithm>
 #include <assert.h>
-#include "Basics.h"
 #include <atomic>
 #include <sstream>
-#include <Matrix.h>
 #include <iostream>
+
+#include "Basics.h"
+#include "Matrix.h"
+
 //#define RNN_DEBUG 1
 #define DEFAULT_HIDDEN_ACTIVITY 0.1
 
@@ -273,15 +275,15 @@ namespace Microsoft { namespace MSR { namespace CNTK {
             return m_indexInLoop;
         }
 
-		std::wstring GetName() const
-		{
-			return m_nodeName;
-		}
+        std::wstring GetName() const
+        {
+            return m_nodeName;
+        }
 
-		std::vector<ComputationNodePtr>	GetChildren() const
-		{
-			return m_children;
-		}
+        std::vector<ComputationNodePtr>	GetChildren() const
+        {
+            return m_children;
+        }
 
         bool isVisisted()
         {
@@ -583,39 +585,38 @@ namespace Microsoft { namespace MSR { namespace CNTK {
             }
         }
 
-		//  [1/13/2015 erw] add to enumerate all the edges 
-		void EnumerateArcs(std::unordered_set<ComputationNodePtr>& vistied, std::list<ComputationArc>& arcs )
-			//  enumerate arcs that can be reached starting from the current node's children
-			//  [in/out] visited record already visited nodes 
-		{
-			std::list<ComputationNodePtr>	tovisit; 
+        //  [1/13/2015 erw] add to enumerate all the edges 
+        void EnumerateArcs(std::unordered_set<ComputationNodePtr>& vistied, std::list<ComputationArc>& arcs)
+            //  enumerate arcs that can be reached starting from the current node's children
+            //  [in/out] visited record already visited nodes 
+        {
+            std::list<ComputationNodePtr>	tovisit;
 
-			if (vistied.find(this) == vistied.end()) // only do when this node has not been visited before
-			{
-				tovisit.push_back(this);
+            if (vistied.find(this) == vistied.end()) // only do when this node has not been visited before
+            {
+                tovisit.push_back(this);
 
-				while (!tovisit.empty())
-				{
-					ComputationNodePtr curNode = tovisit.front();
-					tovisit.pop_front();
+                while (!tovisit.empty())
+                {
+                    ComputationNodePtr curNode = tovisit.front();
+                    tovisit.pop_front();
 
-					if (vistied.find(curNode) == vistied.end())
-					{
-						for (size_t i = 0; i < curNode->m_children.size(); i++)
-						{
-							arcs.push_back(ComputationArc(curNode, curNode->m_children[i]));	
+                    if (vistied.find(curNode) == vistied.end())
+                    {
+                        for (size_t i = 0; i < curNode->m_children.size(); i++)
+                        {
+                            arcs.push_back(ComputationArc(curNode, curNode->m_children[i]));
 
-							if (vistied.find(curNode->m_children[i]) == vistied.end()) // this children has not been visited before 
-							{
-								tovisit.push_front(curNode->m_children[i]);		// going to visit each of the children
-							}
-						}
-						vistied.insert(curNode);
-					}
-				}
-			}
-		}
-		
+                            if (vistied.find(curNode->m_children[i]) == vistied.end()) // this children has not been visited before 
+                            {
+                                tovisit.push_front(curNode->m_children[i]);		// going to visit each of the children
+                            }
+                        }
+                        vistied.insert(curNode);
+                    }
+                }
+            }
+        }
 
         // NOTE: we should reimplement this to be thread-safe and use a larger than requested initialized memory block
         // we can then just wrap that memory block in a matrix of the correct dimensions since it will be const no one can change it
@@ -722,8 +723,6 @@ namespace Microsoft { namespace MSR { namespace CNTK {
             return nodes;
         }
 
-
-
         std::wstring CreateUniqNodeName() const
         {
 #ifdef USE_GUID_AS_NAME
@@ -939,3311 +938,6 @@ protected:  \
 
 #pragma region derived operations
 
-    //used to represent weight Matrix<ElemType> and biases
-    template<class ElemType>
-    class LearnableParameter : public ComputationNode<ElemType>
-    {
-        UsingComputationNodeMembers;
-    public:
-        LearnableParameter(size_t rows, size_t cols, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)
-        {
-            //intentionally comment out so that we may support automatic dimention inference
-            //if (rows * cols == 0) 
-            //    throw std::logic_error("This LearnableParameter dimension is 0.");
-
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            m_needGradient = true;
-            m_deviceId = deviceId;
-            MoveMatricesToDevice(deviceId);
-            m_functionValues.Resize(rows, cols);
-
-            m_outputWidth = 1;
-            m_outputHeight = rows;
-            m_outputChannels = 1;
-
-            InitRecurrentNode();
-        }
-
-        LearnableParameter(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            LoadFromFile(fstream, modelVersion, deviceId);
-        }
-
-        virtual void SaveToFile(File& fstream) const
-        {
-            ComputationNode<ElemType>::SaveToFile(fstream);
-
-            fstream << NeedGradient();
-            fstream << FunctionValues().GetNumRows() << FunctionValues().GetNumCols(); 
-            fstream << FunctionValues();
-        }
-        
-        virtual void LoadFromFile(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX)
-        {
-            ComputationNode<ElemType>::LoadFromFile(fstream, modelVersion, deviceId);
-
-            size_t rows, cols;
-            fstream >> m_needGradient;
-            fstream >> rows >> cols;
-
-            //intentionally comment out to support automatic dimention inference
-            //if (rows * cols == 0) 
-            //    throw std::logic_error("This LearnableParameter dimension is 0.");
-
-            m_functionValues.Resize(rows, cols);
-            fstream >> m_functionValues;
-
-            m_outputWidth = 1;
-            m_outputHeight = rows;
-            m_outputChannels = 1;
-        }
-
-
-        virtual const std::wstring OperationName() const {return TypeName();}
-        virtual void ComputeInputPartial(const size_t /*inputIndex*/) {}
-        virtual void ComputeInputPartial(const size_t /*inputIndex*/, const size_t /*timeIdxInSeq*/) {}
-        virtual void EvaluateThisNode()  {}
-        virtual void EvaluateThisNode(const size_t /*timeIdxInSeq*/) {}
-        virtual void Validate() 
-        {
-            PrintSelfBeforeValidation();
-        }
-
-        static const std::wstring TypeName() {return L"LearnableParameter";} 
-
-        virtual void DumpNodeInfo(const bool printValues, File& fstream) const
-        {
-            ComputationNode<ElemType>::DumpNodeInfo(printValues, fstream);
-
-            char str[4096];
-            sprintf(str, "[%lu,%lu]  ", FunctionValues().GetNumRows(), FunctionValues().GetNumCols());
-            fstream << string(str);
-            sprintf(str, "NeedGradient=%s", NeedGradient()? "true" : "false");
-            fstream << string(str);
-
-            PrintNodeValuesToFile(printValues, fstream);
-        }
-
-        // copy constructor
-        LearnableParameter(const LearnableParameter<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags) : ComputationNode<ElemType>(node->m_deviceId)
-        {
-            node->CopyTo(this, newName, flags);
-        }
-
-        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            const std::wstring& name = (newName == L"")?NodeName():newName;
-                
-            ComputationNodePtr node = new LearnableParameter<ElemType>(this, name, flags);
-            return node;
-        }
-    };
-
-    //WARNING: Don't use SparseLearnableParameter yet since the current version assumes the parameter is dense instead of sparse
-    //WARNING: After the right implementation is put here we need to turn it on in NetworkDescriptionLangauge.cpp
-    template<class ElemType>
-    class SparseLearnableParameter : public LearnableParameter<ElemType>
-    {
-        UsingComputationNodeMembers;
-    public:
-        SparseLearnableParameter(size_t rows, size_t cols, const size_t size, const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX, const std::wstring name = L"")
-            : LearnableParameter<ElemType>(rows, cols, deviceId, name)
-        {
-            m_gradientValues.SwitchToMatrixType(MatrixType::SPARSE, matrixFormatSparseBlockCol, false);
-            m_gradientValues.Resize(rows, cols, size);
-        }
-
-        SparseLearnableParameter (File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX, const std::wstring name = L"") 
-            : LearnableParameter<ElemType>(fstream, modelVersion, deviceId, name)
-        {
-            m_gradientValues.SwitchToMatrixType(MatrixType::SPARSE, matrixFormatSparseBlockCol, false);
-            m_gradientValues.Resize(FunctionValues().GetNumRows(), FunctionValues().GetNumCols());
-        }
-
-        virtual void LoadFromFile(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX)
-        {
-            LearnableParameter<ElemType>::LoadFromFile(fstream,   modelVersion, deviceId);
-            m_gradientValues.SwitchToMatrixType(MatrixType::SPARSE, matrixFormatSparseBlockCol, false);
-            m_gradientValues.Resize(FunctionValues().GetNumRows(), FunctionValues().GetNumCols());
-        }
-
-        virtual const std::wstring OperationName() const {return TypeName();}
-        static const std::wstring TypeName() {return L"SparseLearnableParameter";} 
-
-        // copy constructor
-        SparseLearnableParameter (const SparseLearnableParameter <ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags) 
-            : LearnableParameter<ElemType>( node, newName, flags)
-        {
-        }
-
-        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            const std::wstring& name = (newName == L"")?NodeName():newName;
-                
-            ComputationNodePtr node = new SparseLearnableParameter<ElemType>(this, name, flags);
-            return node;
-        }
-    };
-
-    template class SparseLearnableParameter<float>; 
-    template class SparseLearnableParameter<double>;
-
-    template<class ElemType>
-    class InputValue : public ComputationNode<ElemType>
-    {
-        UsingComputationNodeMembers;
-    public:
-        InputValue(size_t rows, size_t cols, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId) 
-        {
-            if (rows * cols == 0) 
-                throw std::logic_error("This InputValue dimension is 0.");
-
-            m_outputWidth = 1;
-            m_outputHeight = rows;
-            m_outputChannels = 1;
-
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            m_deviceId = deviceId;
-            MoveMatricesToDevice(deviceId);
-            m_functionValues.Resize(rows, cols);
-            m_needGradient = false;
-            InitRecurrentNode();
-        }
-        
-        InputValue(size_t imageWidth, size_t imageHeight, size_t imageChannels, size_t numImages, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId) 
-        {
-            size_t rows = imageWidth * imageHeight * imageChannels;
-            size_t cols = numImages;
-
-            if (rows * cols == 0) 
-                throw std::logic_error("This InputValue dimension is 0.");
-
-            m_outputWidth = imageWidth;
-            m_outputHeight = imageHeight;
-            m_outputChannels = imageChannels;
-
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            m_deviceId = deviceId;
-            MoveMatricesToDevice(deviceId);
-            m_functionValues.Resize(rows, cols);
-            m_needGradient = false;
-            InitRecurrentNode();
-        }        
-
-        InputValue(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            LoadFromFile(fstream, modelVersion, deviceId);
-        }
-
-        virtual void SaveToFile(File& fstream) const
-        {
-            ComputationNode<ElemType>::SaveToFile(fstream);
-
-            fstream << FunctionValues().GetNumRows() << FunctionValues().GetNumCols(); 
-            fstream << m_outputWidth << m_outputHeight << m_outputChannels; 
-        }
-
-        virtual void LoadFromFile(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX)
-        {
-            ComputationNode<ElemType>::LoadFromFile(fstream, modelVersion, deviceId);
-
-            size_t rows, cols;
-            fstream >> rows >> cols;
-            if (rows * cols == 0) 
-                throw std::logic_error("This InputValue dimension is 0.");
-
-            fstream >> m_outputWidth >> m_outputHeight >> m_outputChannels; 
-
-            m_functionValues.Resize(rows, cols);
-            m_needGradient = false;
-        }
-
-        virtual const std::wstring OperationName() const {return TypeName();}
-        static const std::wstring TypeName() {return L"InputValue";} 
-
-        virtual void EvaluateThisNode()  {} 
-        virtual void EvaluateThisNode(const size_t /*timeIdxInSeq*/) {}
-        
-        virtual void ComputeInputPartial(const size_t /*inputIndex*/) {}
-        virtual void ComputeInputPartial(const size_t /*inputIndex*/, const size_t /*timeIdxInSeq*/) {}
-
-        virtual void Validate() 
-        {
-            PrintSelfBeforeValidation();
-            //CopyImageSizeFromInputs(); //not necessary since InputValue are leafs. put it here for consistent
-        }
-
-        virtual void DumpNodeInfo(const bool printValues, File& fstream) const
-        {
-            ComputationNode<ElemType>::DumpNodeInfo(printValues, fstream);
-
-            char str[4096];
-            sprintf(str, "[%lu,%lu]", FunctionValues().GetNumRows(), FunctionValues().GetNumCols());
-            fstream << string(str);        
-        }
-
-        // copy constructor
-        InputValue(const InputValue<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags) : ComputationNode<ElemType>(node->m_deviceId)
-        {
-            node->CopyTo(this, newName, flags);
-        }
-
-        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            const std::wstring& name = (newName == L"")?NodeName():newName;
-                
-            ComputationNodePtr node = new InputValue<ElemType>(this, name, flags);
-            return node;
-        }
-
-    };
-
-    template class InputValue<float>; 
-    template class InputValue<double>;
-
-    template<class ElemType>
-    class SparseInputValue : public InputValue<ElemType>
-    {
-        UsingComputationNodeMembers;
-    public:
-        SparseInputValue (size_t rows, size_t cols, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : InputValue<ElemType>(rows, cols, deviceId, name) 
-        {
-            ConvertToSparseMatrix();
-        }
-        
-        SparseInputValue (size_t imageWidth, size_t imageHeight, size_t imageChannels, size_t numImages, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") 
-            : InputValue<ElemType>(imageWidth, imageHeight, imageChannels, numImages, deviceId, name)
-        {
-                ConvertToSparseMatrix();
-        }
-
-        SparseInputValue (File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : InputValue<ElemType>(fstream, modelVersion, deviceId, name)
-        {
-            ConvertToSparseMatrix();
-        }
-
-        virtual void LoadFromFile(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX)
-        {
-            InputValue<ElemType>::LoadFromFile(fstream, modelVersion, deviceId);
-            ConvertToSparseMatrix();
-        }
-
-        virtual const std::wstring OperationName() const {return TypeName();}
-        static const std::wstring TypeName() {return L"SparseInputValue";} 
-
-        // copy constructor
-        SparseInputValue (const SparseInputValue <ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags) : InputValue<ElemType>(node, newName, flags)
-        {
-        }
-
-        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            const std::wstring& name = (newName == L"")?NodeName():newName;
-                
-            ComputationNodePtr node = new SparseInputValue<ElemType>(this, name, flags);
-            return node;
-        }
-
-    private:
-        void ConvertToSparseMatrix()
-        {
-            size_t rows = m_functionValues.GetNumRows();
-            size_t cols = m_functionValues.GetNumCols();
-            m_functionValues.SwitchToMatrixType(MatrixType::SPARSE, matrixFormatSparseCSC, false);
-            m_functionValues.Resize(rows, cols); //SwitchToMatrixType does not reserve information right now.
-        }
-
-    };
-
-
-    template class SparseInputValue<float>; 
-    template class SparseInputValue<double>;
-
-    template<class ElemType>
-    class NegateNode : public ComputationNode<ElemType>
-    {
-        UsingComputationNodeMembers;
-    public:
-        NegateNode(const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)  
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            m_deviceId = deviceId;
-            MoveMatricesToDevice(deviceId);
-            InitRecurrentNode();
-        }
-
-        NegateNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            LoadFromFile(fstream, modelVersion, deviceId);
-        }
-
-        // copy constructor
-        NegateNode(const NegateNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags) : ComputationNode<ElemType>(node->m_deviceId)
-        {
-            node->CopyTo(this, newName, flags);
-        }
-
-        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            const std::wstring& name = (newName == L"")?NodeName():newName;
-                
-            ComputationNodePtr node = new NegateNode<ElemType>(this, name, flags);
-            return node;
-        }
-
-        virtual const std::wstring OperationName() const {return TypeName();}
-        static const std::wstring TypeName() {return L"Negate";} 
-
-        virtual void ComputeInputPartial(const size_t inputIndex)
-        {
-            if (inputIndex != 0)
-                throw std::invalid_argument("Negate operation only has one input.");
-            ComputeInputPartialS(Inputs(0)->GradientValues(), GradientValues());
-        }
-
-        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
-        {
-            if (inputIndex != 0)
-                throw std::invalid_argument("Negate operation only has one input.");
-
-            Matrix<ElemType> sliceInputGrad = Inputs(0)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            ComputeInputPartialS(sliceInputGrad, sliceOutputGrad);
-        }
-
-        static void WINAPI ComputeInputPartialS(Matrix<ElemType>& childGradientValues, const Matrix<ElemType>& gradientValues)
-        {
-            childGradientValues -= gradientValues;
-        }
-
-        virtual void EvaluateThisNode()  
-        {
-            EvaluateThisNodeS(m_functionValues, Inputs(0)->FunctionValues());
-        }
-
-        virtual void EvaluateThisNode(const size_t timeIdxInSeq) 
-        {
-            Matrix<ElemType> sliceInputValue = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            EvaluateThisNodeS(sliceOutputValue, sliceInputValue);
-        }
-
-        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, const Matrix<ElemType>& input)  
-        {
-            functionValues.AssignDifferenceOf(0, input);
-#if NANCHECK
-            functionValues.HasNan("Negate");
-#endif
-        }
-
-        virtual void Validate()
-        {
-            PrintSelfBeforeValidation();
-
-            if (m_children.size() != 1) 
-                throw std::logic_error("Negate operation should have one input.");
-
-            if (Inputs(0)->FunctionValues().GetNumElements() == 0)
-                throw std::logic_error("Negate operation: the input node has 0 element.");
-
-            FunctionValues().Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(0)->FunctionValues().GetNumCols());
-            
-            CopyImageSizeFromInputs(); 
-        }
-
-        virtual void AttachInputs(const ComputationNodePtr singleInput) 
-        {
-            m_children.resize(1);
-            m_children[0] = singleInput;
-        }
-    };
-
-    template class NegateNode<float>; 
-    template class NegateNode<double>;
-
-    template<class ElemType>
-    class RectifiedLinearNode : public ComputationNode<ElemType>
-    {
-        UsingComputationNodeMembers;
-    public:
-        RectifiedLinearNode(const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"")  
-            : ComputationNode<ElemType>(deviceId), m_gradientOfRectifiedLinear(deviceId)
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            m_deviceId = deviceId;
-            MoveMatricesToDevice(deviceId);
-            InitRecurrentNode();
-        }
-
-        RectifiedLinearNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"")
-            : ComputationNode<ElemType>(deviceId), m_gradientOfRectifiedLinear(deviceId)
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            LoadFromFile(fstream, modelVersion, deviceId);
-        }
-
-        virtual const std::wstring OperationName() const {return TypeName();}
-
-        virtual void ComputeInputPartial(const size_t inputIndex)
-        {
-            if (inputIndex != 0)
-                throw std::invalid_argument("RectifiedLinear only has one input.");
-            ComputeInputPartialS(m_gradientOfRectifiedLinear, Inputs(0)->FunctionValues(), Inputs(0)->GradientValues(), GradientValues());
-        }
-
-        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
-        {
-            if (inputIndex != 0)
-                throw std::invalid_argument("RectifiedLinear only has one input.");
-
-            Matrix<ElemType> sliceInputGrad = Inputs(0)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            Matrix<ElemType> sliceInputValue = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            ComputeInputPartialS(m_gradientOfRectifiedLinear, sliceInputValue, sliceInputGrad, sliceOutputGrad);
-        }
-
-        static void WINAPI ComputeInputPartialS(Matrix<ElemType>& gradientOfRectifiedLinear, const Matrix<ElemType>& inputFunctionValues, Matrix<ElemType>& inputGradientValues, const Matrix<ElemType>& gradientValues)
-        {
-            gradientOfRectifiedLinear.AssignLinearRectifierDerivativeOf(inputFunctionValues);
-#if DUMPOUTPUT
-            inputGradientValues.Print("RecitifiedLinearNode-Partial-in");
-#endif
-            inputGradientValues.AddElementProductOf(gradientValues, gradientOfRectifiedLinear); 
-#if DUMPOUTPUT
-            inputGradientValues.Print("RecitifiedLinearNode-Partial-out");
-#endif
-        }
-
-        virtual void EvaluateThisNode()  
-        {
-            EvaluateThisNodeS(m_functionValues, Inputs(0)->FunctionValues());
-        }
-
-        virtual void EvaluateThisNode(const size_t timeIdxInSeq)
-        {
-            Matrix<ElemType> sliceInputValue = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            EvaluateThisNodeS(sliceOutputValue, sliceInputValue);
-        }
-
-        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, const Matrix<ElemType>& inputFunctionValues)  
-        {
-            functionValues.AssignTruncateBottomOf(inputFunctionValues, 0);
-#if NANCHECK
-            functionValues.HasNan("RectifiedLinear");
-#endif
-#if DUMPOUTPUT
-            functionValues.Print("RectifiedLinearNode");
-#endif
-        }
-
-        virtual void Validate()
-        {
-            PrintSelfBeforeValidation();
-
-            if (m_children.size() != 1) 
-                throw std::logic_error("RectifiedLinear operation should have one input.");
-
-            if (Inputs(0)->FunctionValues().GetNumElements() == 0)
-                throw std::logic_error("RectifiedLinear operation: the input node has 0 element.");
-
-            FunctionValues().Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(0)->FunctionValues().GetNumCols());
-            m_gradientOfRectifiedLinear.Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(0)->FunctionValues().GetNumCols());
-            CopyImageSizeFromInputs(); 
-        }
-
-        virtual void AttachInputs(const ComputationNodePtr singleInput) 
-        {
-            m_children.resize(1);
-            m_children[0] = singleInput;
-        }
-
-        virtual void MoveMatricesToDevice(const DEVICEID_TYPE deviceId)
-        {
-            ComputationNode<ElemType>::MoveMatricesToDevice(deviceId);
-
-            if (deviceId != AUTOPLACEMATRIX)
-            {
-                if (m_gradientOfRectifiedLinear.GetDeviceId() != deviceId)
-                    m_gradientOfRectifiedLinear.TransferFromDeviceToDevice(m_gradientOfRectifiedLinear.GetDeviceId(), deviceId);
-            }
-        }
-
-        static const std::wstring TypeName() {return L"RectifiedLinear";} 
-
-        virtual void CopyTo(const ComputationNodePtr nodeP, const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            ComputationNode<ElemType>::CopyTo(nodeP, newName, flags);
-            RectifiedLinearNode<ElemType>* node = (RectifiedLinearNode<ElemType>*) nodeP;
-
-            if (flags & CopyNodeFlags::copyNodeValue)
-            {
-                node->m_gradientOfRectifiedLinear = m_gradientOfRectifiedLinear;
-            }
-        }
-
-        // copy constructor
-        RectifiedLinearNode(const RectifiedLinearNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags)
-            : ComputationNode<ElemType>(node->m_deviceId), m_gradientOfRectifiedLinear(node->m_deviceId)
-        {
-            node->CopyTo(this, newName, flags);
-        }
-
-        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            const std::wstring& name = (newName == L"")?NodeName():newName;
-                
-            ComputationNodePtr node = new RectifiedLinearNode<ElemType>(this, name, flags);
-            return node;
-        }
-
-    private:
-        Matrix<ElemType> m_gradientOfRectifiedLinear;
-    };
-
-    template class RectifiedLinearNode<float>; 
-    template class RectifiedLinearNode<double>;
-
-    template<class ElemType>
-    class SigmoidNode : public ComputationNode<ElemType>
-    {
-        UsingComputationNodeMembers;
-    public:
-        SigmoidNode(const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"")  
-            : ComputationNode<ElemType>(deviceId), m_gradientOfSigmoid(deviceId)
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            m_deviceId = deviceId;
-            MoveMatricesToDevice(deviceId);
-            InitRecurrentNode();
-        }
-
-        SigmoidNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"")
-            : ComputationNode<ElemType>(deviceId), m_gradientOfSigmoid(deviceId)
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            LoadFromFile(fstream, modelVersion, deviceId);
-        }
-
-        virtual const std::wstring OperationName() const {return TypeName();}
-        static const std::wstring TypeName() {return L"Sigmoid";} 
-
-        virtual void ComputeInputPartial(const size_t inputIndex)
-        {
-            if (inputIndex != 0)
-                throw std::invalid_argument("Sigmoid only has one input.");
-            ComputeInputPartialS(m_gradientOfSigmoid, Inputs(0)->GradientValues(), GradientValues(), FunctionValues());  
-        }
-
-        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
-        {
-            if (inputIndex != 0)
-                throw std::invalid_argument("Sigmoid only has one input.");
-
-            Matrix<ElemType> sliceInputGrad = Inputs(0)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            ComputeInputPartialS(m_gradientOfSigmoid, sliceInputGrad, sliceOutputGrad, sliceOutputValue);  
-        }
-
-        static void WINAPI ComputeInputPartialS(Matrix<ElemType>& gradientOfSigmoid, Matrix<ElemType>& inputGradientValues, const Matrix<ElemType>& gradientValues, const Matrix<ElemType>& functionValues)  
-        {
-            gradientOfSigmoid.AssignSigmoidDerivativeOf(functionValues);
-
-            inputGradientValues.AddElementProductOf(gradientValues, gradientOfSigmoid);
-        }
-
-        virtual void EvaluateThisNode()  
-        {
-            EvaluateThisNodeS(m_functionValues, Inputs(0)->FunctionValues());
-        }
-
-        virtual void EvaluateThisNode(const size_t timeIdxInSeq)  
-        {
-            Matrix<ElemType> sliceInputValue = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            EvaluateThisNodeS(sliceOutputValue, sliceInputValue);
-        }
-
-        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, const Matrix<ElemType>& inputFunctionValues)  
-        {
-            functionValues.AssignSigmoidOf(inputFunctionValues);
-#if NANCHECK
-            functionValues.HasNan("Sigmoid");
-#endif
-        }
-
-        virtual void Validate()
-        {
-            PrintSelfBeforeValidation();
-
-            if (m_children.size() != 1) 
-                throw std::logic_error("Sigmoid operation should have one input.");
-
-            if (Inputs(0)->FunctionValues().GetNumElements() == 0)
-                throw std::logic_error("Sigmoid operation: the input node has 0 element.");
-
-            FunctionValues().Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(0)->FunctionValues().GetNumCols());
-            m_gradientOfSigmoid.Resize(FunctionValues().GetNumRows(), FunctionValues().GetNumCols());
-            CopyImageSizeFromInputs(); 
-        }
-
-        virtual void AttachInputs(const ComputationNodePtr singleInput) 
-        {
-            m_children.resize(1);
-            m_children[0] = singleInput;
-        }
-
-        virtual void MoveMatricesToDevice(const DEVICEID_TYPE deviceId)
-        {
-            ComputationNode<ElemType>::MoveMatricesToDevice(deviceId);
-
-            if (deviceId != AUTOPLACEMATRIX)
-            {
-                if (m_gradientOfSigmoid.GetDeviceId() != deviceId)
-                    m_gradientOfSigmoid.TransferFromDeviceToDevice(m_gradientOfSigmoid.GetDeviceId(), deviceId);
-            }
-        }
-
-        virtual void CopyTo(const ComputationNodePtr nodeP, const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            ComputationNode<ElemType>::CopyTo(nodeP, newName, flags);
-            SigmoidNode<ElemType>* node = (SigmoidNode<ElemType>*) nodeP;
-
-            if (flags & CopyNodeFlags::copyNodeValue)
-            {
-                node->m_gradientOfSigmoid = m_gradientOfSigmoid;
-            }
-        }
-
-        // copy constructor
-        SigmoidNode(const SigmoidNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags)
-            : ComputationNode<ElemType>(node->m_deviceId), m_gradientOfSigmoid(node->m_deviceId)
-        {
-            node->CopyTo(this, newName, flags);
-        }
-
-        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            const std::wstring& name = (newName == L"")?NodeName():newName;
-                
-            ComputationNodePtr node = new SigmoidNode<ElemType>(this, name, flags);
-            return node;
-        }
-
-    private:
-        Matrix<ElemType> m_gradientOfSigmoid;
-    };
-
-    template class SigmoidNode<float>; 
-    template class SigmoidNode<double>;
-
-    template<class ElemType>
-    class TanhNode : public ComputationNode<ElemType>
-    {
-        UsingComputationNodeMembers;
-    public:
-        TanhNode(const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"")  
-            : ComputationNode<ElemType>(deviceId), m_gradientOfTanh(deviceId)  
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            m_deviceId = deviceId;
-            MoveMatricesToDevice(deviceId);
-            InitRecurrentNode();
-        }
-
-        TanhNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"")
-            : ComputationNode<ElemType>(deviceId), m_gradientOfTanh(deviceId)
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            LoadFromFile(fstream, modelVersion, deviceId);
-        }
-
-        virtual const std::wstring OperationName() const {return TypeName();}
-        static const std::wstring TypeName() {return L"Tanh";} 
-
-        virtual void ComputeInputPartial(const size_t inputIndex)
-        {
-            if (inputIndex != 0)
-                throw std::invalid_argument("Tanh only has one input.");
-            ComputeInputPartialS(m_gradientOfTanh, Inputs(0)->GradientValues(), GradientValues(), FunctionValues());
-        }
-
-        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
-        {
-            if (inputIndex != 0)
-                throw std::invalid_argument("Tanh only has one input.");
-
-            Matrix<ElemType> sliceInputGrad = Inputs(0)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            ComputeInputPartialS(m_gradientOfTanh, sliceInputGrad, sliceOutputGrad, sliceOutputValue);
-        }
-
-        static void WINAPI ComputeInputPartialS(Matrix<ElemType>& gradientOfTanh, Matrix<ElemType>& inputGradientValues, const Matrix<ElemType>& gradientValues, const Matrix<ElemType>& functionValues)  
-        {
-            gradientOfTanh.AssignElementProductOf(functionValues, functionValues); // v .* v
-            gradientOfTanh.AssignDifferenceOf(1, gradientOfTanh); // 1-v^2
-
-            inputGradientValues.AddElementProductOf(gradientValues, gradientOfTanh); // += d .* ((1-v) .* v))
-        }
-
-
-        virtual void EvaluateThisNode()  
-        {
-            EvaluateThisNodeS(m_functionValues, Inputs(0)->FunctionValues());
-        }
-
-        virtual void EvaluateThisNode(const size_t timeIdxInSeq)  
-        {
-            Matrix<ElemType> sliceInputValue = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            EvaluateThisNodeS(sliceOutputValue, sliceInputValue);
-        }
-
-        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, const Matrix<ElemType>& inputFunctionValues)  
-        {
-            functionValues.AssignTanhOf(inputFunctionValues);
-#if NANCHECK
-            functionValues.HasNan("Tanh");
-#endif
-        }
-
-        virtual void Validate()
-        {
-            PrintSelfBeforeValidation();
-
-            if (m_children.size() != 1) 
-                throw std::logic_error("Tanh operation should have one input.");
-
-            if (Inputs(0)->FunctionValues().GetNumElements() == 0)
-                throw std::logic_error("Tanh operation: the input node has 0 element.");
-
-            FunctionValues().Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(0)->FunctionValues().GetNumCols());
-            m_gradientOfTanh.Resize(FunctionValues().GetNumRows(), FunctionValues().GetNumCols());
-            CopyImageSizeFromInputs(); 
-        }
-
-        virtual void AttachInputs(const ComputationNodePtr singleInput) 
-        {
-            m_children.resize(1);
-            m_children[0] = singleInput;
-        }
-
-        virtual void MoveMatricesToDevice(const DEVICEID_TYPE deviceId)
-        {
-            ComputationNode<ElemType>::MoveMatricesToDevice(deviceId);
-
-            if (deviceId != AUTOPLACEMATRIX)
-            {
-                if (m_gradientOfTanh.GetDeviceId() != deviceId)
-                    m_gradientOfTanh.TransferFromDeviceToDevice(m_gradientOfTanh.GetDeviceId(), deviceId);
-            }
-        }
-
-        virtual void CopyTo(const ComputationNodePtr nodeP, const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            ComputationNode<ElemType>::CopyTo(nodeP, newName, flags);
-            TanhNode<ElemType>* node = (TanhNode<ElemType>*) nodeP;
-
-            if (flags & CopyNodeFlags::copyNodeValue)
-            {
-                node->m_gradientOfTanh = m_gradientOfTanh;
-            }
-        }
-
-        // copy constructor
-        TanhNode(const TanhNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags)
-            : ComputationNode<ElemType>(node->m_deviceId), m_gradientOfTanh(node->m_deviceId)
-        {
-            node->CopyTo(this, newName, flags);
-        }
-
-        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            const std::wstring& name = (newName == L"")?NodeName():newName;
-                
-            ComputationNodePtr node = new TanhNode<ElemType>(this, name, flags);
-            return node;
-        }
-
-    private:
-        Matrix<ElemType> m_gradientOfTanh;
-    };
-
-    template class TanhNode<float>; 
-    template class TanhNode<double>;
-
-    template<class ElemType>
-    class LogNode : public ComputationNode<ElemType>
-    {
-                UsingComputationNodeMembers;
-        public:
-        LogNode(const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX, const std::wstring name = L"")
-            : ComputationNode<ElemType>(deviceId), m_gradientOfLog(deviceId)
-        {
-            m_nodeName = (name == L"" ? CreateUniqNodeName() : name);
-            m_deviceId = deviceId;
-            MoveMatricesToDevice(deviceId);
-            InitRecurrentNode();
-        }
-
-        LogNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX, const std::wstring name = L"")
-            : ComputationNode<ElemType>(deviceId), m_gradientOfLog(deviceId)
-        {
-            m_nodeName = (name == L"" ? CreateUniqNodeName() : name);
-            LoadFromFile(fstream, modelVersion, deviceId);
-        }
-
-        virtual const std::wstring OperationName() const { return TypeName(); }
-        static const std::wstring TypeName() { return L"Log"; }
-
-
-        virtual void ComputeInputPartial(const size_t inputIndex)
-        {
-            if (inputIndex != 0)
-                throw std::invalid_argument("Log only has one input.");
-            ComputeInputPartialS(m_gradientOfLog, Inputs(0)->GradientValues(), Inputs(0)->FunctionValues(), GradientValues());
-        }
-
-        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
-        {
-            if (inputIndex != 0)
-                throw std::invalid_argument("Log only has one input.");
-
-            Matrix<ElemType> sliceInputGrad = Inputs(0)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            Matrix<ElemType> sliceInputValue = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            ComputeInputPartialS(m_gradientOfLog, sliceInputGrad, sliceInputValue, sliceOutputGrad);
-        }
-
-        static void WINAPI ComputeInputPartialS(Matrix<ElemType>& gradientOfLog, Matrix<ElemType>& inputGradientValues, const Matrix<ElemType>& inputFunctionValues, const Matrix<ElemType>& gradientValues)
-        {
-            gradientOfLog.AssignElementInverseOf(inputFunctionValues); // 1/x (x is input to log(x))
-
-            inputGradientValues.AddElementProductOf(gradientValues, gradientOfLog);
-        }
-
-        virtual void EvaluateThisNode()
-        {
-            EvaluateThisNodeS(m_functionValues, Inputs(0)->FunctionValues());
-        }
-
-        virtual void EvaluateThisNode(const size_t timeIdxInSeq)
-        {
-            Matrix<ElemType> sliceInputValue = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            EvaluateThisNodeS(sliceOutputValue, sliceInputValue);
-        }
-
-        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, const Matrix<ElemType>& inputFunctionValues)
-        {
-            functionValues.AssignLogOf(inputFunctionValues);
-#if NANCHECK
-            functionValues.HasNan("Log");
-#endif
-        }
-
-        virtual void Validate()
-        {
-            PrintSelfBeforeValidation();
-
-            if (m_children.size() != 1)
-                throw std::logic_error("Log operation should have one input.");
-
-            if (Inputs(0)->FunctionValues().GetNumElements() == 0)
-                throw std::logic_error("Log operation: the input node has 0 element.");
-
-            FunctionValues().Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(0)->FunctionValues().GetNumCols());
-            m_gradientOfLog.Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(0)->FunctionValues().GetNumCols());
-            CopyImageSizeFromInputs();
-        }
-
-        virtual void AttachInputs(const ComputationNodePtr singleInput)
-        {
-            m_children.resize(1);
-            m_children[0] = singleInput;
-        }
-
-        virtual void MoveMatricesToDevice(const DEVICEID_TYPE deviceId)
-        {
-            ComputationNode<ElemType>::MoveMatricesToDevice(deviceId);
-
-            if (deviceId != AUTOPLACEMATRIX)
-            {
-                if (m_gradientOfLog.GetDeviceId() != deviceId)
-                    m_gradientOfLog.TransferFromDeviceToDevice(m_gradientOfLog.GetDeviceId(), deviceId);
-            }
-        }
-
-        virtual void CopyTo(const ComputationNodePtr nodeP, const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            ComputationNode<ElemType>::CopyTo(nodeP, newName, flags);
-            LogNode<ElemType>* node = (LogNode<ElemType>*) nodeP;
-
-            if (flags & CopyNodeFlags::copyNodeValue)
-            {
-                node->m_gradientOfLog = m_gradientOfLog;
-            }
-        }
-
-        // copy constructor
-        LogNode(const LogNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags)
-            : ComputationNode<ElemType>(node->m_deviceId), m_gradientOfLog(node->m_deviceId)
-        {
-            node->CopyTo(this, newName, flags);
-        }
-
-        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            const std::wstring& name = (newName == L"") ? NodeName() : newName;
-
-            ComputationNodePtr node = new LogNode<ElemType>(this, name, flags);
-            return node;
-        }
-
-    private:
-        Matrix<ElemType> m_gradientOfLog;
-    };
-
-    template class LogNode<float>;
-    template class LogNode<double>;
-
-
-    template<class ElemType>
-    class ExpNode : public ComputationNode<ElemType>
-    {
-        UsingComputationNodeMembers;
-    public:
-        ExpNode(const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX, const std::wstring name = L"")
-            : ComputationNode<ElemType>(deviceId), m_gradientOfExp(deviceId)
-        {
-            m_nodeName = (name == L"" ? CreateUniqNodeName() : name);
-            m_deviceId = deviceId;
-            MoveMatricesToDevice(deviceId);
-            InitRecurrentNode();
-        }
-
-        ExpNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX, const std::wstring name = L"")
-            : ComputationNode<ElemType>(deviceId), m_gradientOfExp(deviceId)
-        {
-            m_nodeName = (name == L"" ? CreateUniqNodeName() : name);
-            LoadFromFile(fstream, modelVersion, deviceId);
-        }
-
-        virtual const std::wstring OperationName() const { return TypeName(); }
-        static const std::wstring TypeName() { return L"Exp"; }
-
-
-        virtual void ComputeInputPartial(const size_t inputIndex)
-        {
-            if (inputIndex != 0)
-                throw std::invalid_argument("Exp only has one input.");
-            ComputeInputPartialS(m_gradientOfExp, Inputs(0)->GradientValues(), Inputs(0)->FunctionValues(), GradientValues());
-        }
-
-        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
-        {
-            if (inputIndex != 0)
-                throw std::invalid_argument("Exp only has one input.");
-
-            Matrix<ElemType> sliceInputGrad = Inputs(0)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            Matrix<ElemType> sliceInputValue = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            ComputeInputPartialS(m_gradientOfExp, sliceInputGrad, sliceInputValue, sliceOutputGrad);
-        }
-
-        static void WINAPI ComputeInputPartialS(Matrix<ElemType>& gradientOfExp, Matrix<ElemType>& inputGradientValues, const Matrix<ElemType>& inputFunctionValues, const Matrix<ElemType>& gradientValues)
-        {
-            gradientOfExp.AssignExpOf(inputFunctionValues); // Exp(x) is its own partial
-
-            inputGradientValues.AddElementProductOf(gradientValues, gradientOfExp);
-        }
-
-        virtual void EvaluateThisNode()
-        {
-            EvaluateThisNodeS(m_functionValues, Inputs(0)->FunctionValues());
-        }
-
-        virtual void EvaluateThisNode(const size_t timeIdxInSeq)
-        {
-            Matrix<ElemType> sliceInputValue = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            EvaluateThisNodeS(sliceOutputValue, sliceInputValue);
-        }
-
-        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, const Matrix<ElemType>& inputFunctionValues)
-        {
-            functionValues.AssignExpOf(inputFunctionValues);
-#if NANCHECK
-            functionValues.HasNan("Exp");
-#endif
-        }
-
-        virtual void Validate()
-        {
-            PrintSelfBeforeValidation();
-
-            if (m_children.size() != 1)
-                throw std::logic_error("Exp operation should have one input.");
-
-            if (Inputs(0)->FunctionValues().GetNumElements() == 0)
-                throw std::logic_error("Exp operation: the input node has 0 element.");
-
-            FunctionValues().Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(0)->FunctionValues().GetNumCols());
-            m_gradientOfExp.Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(0)->FunctionValues().GetNumCols());
-            CopyImageSizeFromInputs();
-        }
-
-        virtual void AttachInputs(const ComputationNodePtr singleInput)
-        {
-            m_children.resize(1);
-            m_children[0] = singleInput;
-        }
-
-        virtual void MoveMatricesToDevice(const DEVICEID_TYPE deviceId)
-        {
-            ComputationNode<ElemType>::MoveMatricesToDevice(deviceId);
-
-            if (deviceId != AUTOPLACEMATRIX)
-            {
-                if (m_gradientOfExp.GetDeviceId() != deviceId)
-                    m_gradientOfExp.TransferFromDeviceToDevice(m_gradientOfExp.GetDeviceId(), deviceId);
-            }
-        }
-
-        virtual void CopyTo(const ComputationNodePtr nodeP, const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            ComputationNode<ElemType>::CopyTo(nodeP, newName, flags);
-            ExpNode<ElemType>* node = (ExpNode<ElemType>*) nodeP;
-
-            if (flags & CopyNodeFlags::copyNodeValue)
-            {
-                node->m_gradientOfExp = m_gradientOfExp;
-            }
-        }
-
-        // copy constructor
-        ExpNode(const ExpNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags)
-            : ComputationNode<ElemType>(node->m_deviceId), m_gradientOfExp(node->m_deviceId)
-        {
-            node->CopyTo(this, newName, flags);
-        }
-
-        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            const std::wstring& name = (newName == L"") ? NodeName() : newName;
-
-            ComputationNodePtr node = new ExpNode<ElemType>(this, name, flags);
-            return node;
-        }
-
-    private:
-        Matrix<ElemType> m_gradientOfExp;
-    };
-
-    template class ExpNode<float>;
-    template class ExpNode<double>;
-
-
-    template<class ElemType>
-    class CosineNode : public ComputationNode<ElemType>
-    {
-        UsingComputationNodeMembers;
-    public:
-        CosineNode(const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"")  
-            : ComputationNode<ElemType>(deviceId), m_gradientOfCosine(deviceId)
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            m_deviceId = deviceId;
-            MoveMatricesToDevice(deviceId);
-            InitRecurrentNode();
-        }
-
-        CosineNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"")
-            : ComputationNode<ElemType>(deviceId), m_gradientOfCosine(deviceId)
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            LoadFromFile(fstream, modelVersion, deviceId);
-        }
-
-        virtual const std::wstring OperationName() const {return TypeName();}
-        static const std::wstring TypeName() {return L"Cosine";} 
-
-        virtual void ComputeInputPartial(const size_t inputIndex)
-        {
-            if (inputIndex != 0)
-                throw std::invalid_argument("Cosine only has one input.");
-            ComputeInputPartialS(m_gradientOfCosine, Inputs(0)->GradientValues(), Inputs(0)->FunctionValues(), GradientValues());
-        }
-
-        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
-        {
-            if (inputIndex != 0)
-                throw std::invalid_argument("Cosine only has one input.");
-
-            Matrix<ElemType> sliceInputGrad = Inputs(0)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            Matrix<ElemType> sliceInputValue = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            ComputeInputPartialS(m_gradientOfCosine, sliceInputGrad, sliceInputValue, sliceOutputGrad);
-        }
-
-        static void WINAPI ComputeInputPartialS(Matrix<ElemType>& gradientOfCosine, Matrix<ElemType>& inputGradientValues, const Matrix<ElemType>& inputFunctionValues, const Matrix<ElemType>& gradientValues)  
-        {
-            gradientOfCosine.AssignNegativeSineOf(inputFunctionValues); // -sin(x) (x is input to Cosine(x))
-            inputGradientValues.AddElementProductOf(gradientValues, gradientOfCosine);
-        }
-
-        virtual void EvaluateThisNode()  
-        {
-            EvaluateThisNodeS(m_functionValues, Inputs(0)->FunctionValues());
-        }
-
-        virtual void EvaluateThisNode(const size_t timeIdxInSeq)
-        {
-            Matrix<ElemType> sliceInputValue = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            EvaluateThisNodeS(sliceOutputValue, sliceInputValue);
-        }
-
-        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, const Matrix<ElemType>& inputFunctionValues)  
-        {
-            functionValues.AssignCosineOf(inputFunctionValues);
-#if NANCHECK
-            functionValues.HasNan("Cosine");
-#endif
-        }
-
-
-        virtual void Validate()
-        {
-            PrintSelfBeforeValidation();
-
-            if (m_children.size() != 1) 
-                throw std::logic_error("Cosine operation should have one input.");
-
-            if (Inputs(0)->FunctionValues().GetNumElements() == 0)
-                throw std::logic_error("Cosine operation: the input node has 0 element.");
-
-            FunctionValues().Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(0)->FunctionValues().GetNumCols());
-            m_gradientOfCosine.Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(0)->FunctionValues().GetNumCols());
-            CopyImageSizeFromInputs(); 
-        }
-
-        virtual void AttachInputs(const ComputationNodePtr singleInput) 
-        {
-            m_children.resize(1);
-            m_children[0] = singleInput;
-        }
-
-        virtual void MoveMatricesToDevice(const DEVICEID_TYPE deviceId)
-        {
-            ComputationNode<ElemType>::MoveMatricesToDevice(deviceId);
-
-            if (deviceId != AUTOPLACEMATRIX)
-            {
-                if (m_gradientOfCosine.GetDeviceId() != deviceId)
-                    m_gradientOfCosine.TransferFromDeviceToDevice(m_gradientOfCosine.GetDeviceId(), deviceId);
-            }
-        }
-
-        virtual void CopyTo(const ComputationNodePtr nodeP, const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            ComputationNode<ElemType>::CopyTo(nodeP, newName, flags);
-            CosineNode<ElemType>* node = (CosineNode<ElemType>*) nodeP;
-
-            if (flags & CopyNodeFlags::copyNodeValue)
-            {
-                node->m_gradientOfCosine = m_gradientOfCosine;
-            }
-        }
-
-        // copy constructor
-        CosineNode(const CosineNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags)
-            : ComputationNode<ElemType>(node->m_deviceId), m_gradientOfCosine(node->m_deviceId)
-        {
-            node->CopyTo(this, newName, flags);
-        }
-
-        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            const std::wstring& name = (newName == L"")?NodeName():newName;
-                
-            ComputationNodePtr node = new CosineNode<ElemType>(this, name, flags);
-            return node;
-        }
-
-    private:
-        Matrix<ElemType> m_gradientOfCosine;
-    };
-
-    template class CosineNode<float>; 
-    template class CosineNode<double>;
-
-
-    //we assume it's  column-wise by default
-    //the derivative will increase the Matrix<ElemType> size to the power of column size and should not be used.
-    template<class ElemType>
-    class SoftmaxNode : public ComputationNode<ElemType>
-    {
-        UsingComputationNodeMembers;
-    public:
-        SoftmaxNode(const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"")
-            : ComputationNode<ElemType>(deviceId), m_gradientDotValue(deviceId), m_diff(deviceId)
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            m_deviceId = deviceId;
-            MoveMatricesToDevice(deviceId);
-            InitRecurrentNode();
-        }
-
-        SoftmaxNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"")
-            : ComputationNode<ElemType>(deviceId), m_gradientDotValue(deviceId), m_diff(deviceId)
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            LoadFromFile(fstream, modelVersion, deviceId);
-        }
-
-        virtual const std::wstring OperationName() const {return TypeName();}
-        static const std::wstring TypeName() {return L"Softmax";} 
-
-        virtual void ComputeInputPartial(const size_t inputIndex)
-        {
-            if (inputIndex != 0)
-                throw std::invalid_argument("Softmax only has one input.");
-            ComputeInputPartialS(m_gradientDotValue, m_diff, Inputs(0)->GradientValues(), GradientValues(), FunctionValues());
-        }
-
-        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
-        {
-            if (inputIndex != 0)
-                throw std::invalid_argument("Softmax only has one input.");
-
-            Matrix<ElemType> sliceInputGrad = Inputs(0)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            ComputeInputPartialS(m_gradientDotValue, m_diff, sliceInputGrad, sliceOutputGrad, sliceOutputValue);
-        }
-
-        static void WINAPI ComputeInputPartialS(Matrix<ElemType>& gradientDotValue, Matrix<ElemType>& diff, Matrix<ElemType>& inputGradientValues, 
-            const Matrix<ElemType>& gradientValues, const Matrix<ElemType>& functionValues)  
-        {
-            gradientDotValue.AssignInnerProductOf(gradientValues, functionValues, true);
-            diff.AssignDifferenceOf(gradientValues, gradientDotValue);
-
-            inputGradientValues.AddElementProductOf(diff, functionValues);
-        }
-
-        virtual void EvaluateThisNode()  
-        {
-            EvaluateThisNodeS(m_functionValues, Inputs(0)->FunctionValues());
-        }
-
-        virtual void EvaluateThisNode(const size_t timeIdxInSeq)
-        {
-            Matrix<ElemType> sliceInputValue = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            EvaluateThisNodeS(sliceOutputValue, sliceInputValue);
-        }
-
-        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, const Matrix<ElemType>& inputFunctionValues)  
-        {
-            functionValues.AssignLogSoftmaxOf(inputFunctionValues, true);
-            functionValues.InplaceExp();
-#if NANCHECK
-            functionValues.HasNan("SoftMax");
-#endif
-        }
-
-        virtual void Validate()
-        {
-            PrintSelfBeforeValidation();
-
-            if (m_children.size() != 1) 
-                throw std::logic_error("SoftmaxNode operation should have one input.");
-
-            if (Inputs(0)->FunctionValues().GetNumElements() == 0)
-                throw std::logic_error("SoftmaxNode operation: the input node has 0 element.");
-
-            FunctionValues().Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(0)->FunctionValues().GetNumCols());
-            CopyImageSizeFromInputs(); 
-        }
-
-        virtual void AttachInputs(const ComputationNodePtr singleInput) 
-        {
-            m_children.resize(1);
-            m_children[0] = singleInput;
-        }
-
-        virtual void MoveMatricesToDevice(const DEVICEID_TYPE deviceId)
-        {
-            ComputationNode<ElemType>::MoveMatricesToDevice(deviceId);
-
-            if (deviceId != AUTOPLACEMATRIX)
-            {
-                if (m_gradientDotValue.GetDeviceId() != deviceId)
-                    m_gradientDotValue.TransferFromDeviceToDevice(m_gradientDotValue.GetDeviceId(), deviceId);
-                if (m_diff.GetDeviceId() != deviceId)
-                    m_diff.TransferFromDeviceToDevice(m_diff.GetDeviceId(), deviceId);
-            }
-        }
-
-        virtual void CopyTo(const ComputationNodePtr nodeP, const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            ComputationNode<ElemType>::CopyTo(nodeP, newName, flags);
-            SoftmaxNode<ElemType>* node = (SoftmaxNode<ElemType>*) nodeP;
-
-            if (flags & CopyNodeFlags::copyNodeValue)
-            {
-                node->m_gradientDotValue = m_gradientDotValue;
-                node->m_diff = m_diff;
-            }
-        }
-
-        // copy constructor
-        SoftmaxNode(const SoftmaxNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags)
-            : ComputationNode<ElemType>(node->m_deviceId), m_gradientDotValue(node->m_deviceId), m_diff(node->m_deviceId) 
-        {
-            node->CopyTo(this, newName, flags);
-        }
-
-        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            const std::wstring& name = (newName == L"")?NodeName():newName;
-                
-            ComputationNodePtr node = new SoftmaxNode<ElemType>(this, name, flags);
-            return node;
-        }
-
-    private:
-        Matrix<ElemType> m_gradientDotValue;
-        Matrix<ElemType> m_diff;
-    };
-
-    template class SoftmaxNode<float>; 
-    template class SoftmaxNode<double>;
-
-    template<class ElemType>
-    class LogSoftmaxNode : public ComputationNode<ElemType>
-    {
-        UsingComputationNodeMembers;
-    public:
-        LogSoftmaxNode(const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX, const std::wstring name = L"")
-            : ComputationNode<ElemType>(deviceId), m_gradientDotValue(deviceId), m_softmax(deviceId)
-        {
-            m_nodeName = (name == L"" ? CreateUniqNodeName() : name);
-            m_deviceId = deviceId;
-            MoveMatricesToDevice(deviceId);
-            InitRecurrentNode();
-        }
-
-        LogSoftmaxNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX, const std::wstring name = L"")
-            : ComputationNode<ElemType>(deviceId), m_gradientDotValue(deviceId), m_softmax(deviceId)
-        {
-            m_nodeName = (name == L"" ? CreateUniqNodeName() : name);
-            LoadFromFile(fstream, modelVersion, deviceId);
-        }
-
-        virtual const std::wstring OperationName() const { return TypeName(); }
-        static const std::wstring TypeName() { return L"LogSoftmax"; }
-
-        virtual void ComputeInputPartial(const size_t inputIndex)
-        {
-            if (inputIndex != 0)
-                throw std::invalid_argument("Softmax only has one input.");
-            ComputeInputPartialS(m_gradientDotValue, m_softmax, Inputs(0)->GradientValues(), GradientValues(), FunctionValues());
-        }
-
-        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
-        {
-            if (inputIndex != 0)
-                throw std::invalid_argument("Softmax only has one input.");
-
-            Matrix<ElemType> sliceInputGrad = Inputs(0)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            ComputeInputPartialS(m_gradientDotValue, m_softmax, sliceInputGrad, sliceOutputGrad, sliceOutputValue);
-        }
-
-        static void WINAPI ComputeInputPartialS(Matrix<ElemType>& gradientDotValue, Matrix<ElemType>& softmax, Matrix<ElemType>& inputGradientValues,
-            const Matrix<ElemType>& gradientValues, const Matrix<ElemType>& functionValues)
-        {
-            softmax.AssignExpOf(functionValues);
-            Matrix<ElemType>::VectorSum(gradientValues, gradientDotValue, true);
-            softmax.RowElementMultiplyWith(gradientDotValue);
-            Matrix<ElemType>::AddScaledDifference(1.0, gradientValues, softmax, inputGradientValues);
-        }
-
-        virtual void EvaluateThisNode()
-        {
-            EvaluateThisNodeS(m_functionValues, Inputs(0)->FunctionValues());
-        }
-
-        virtual void EvaluateThisNode(const size_t timeIdxInSeq)
-        {
-            Matrix<ElemType> sliceInputValue = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            EvaluateThisNodeS(sliceOutputValue, sliceInputValue);
-        }
-
-        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, const Matrix<ElemType>& inputFunctionValues)
-        {
-            functionValues.AssignLogSoftmaxOf(inputFunctionValues, true);
-#if NANCHECK
-            functionValues.HasNan("LogSoftMax");
-#endif
-        }
-
-        virtual void Validate()
-        {
-            PrintSelfBeforeValidation();
-
-            if (m_children.size() != 1)
-                throw std::logic_error("LogSoftmaxNode operation should have one input.");
-
-            if (Inputs(0)->FunctionValues().GetNumElements() == 0)
-                throw std::logic_error("LogSoftmaxNode operation: the input node has 0 element.");
-
-            FunctionValues().Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(0)->FunctionValues().GetNumCols());
-            CopyImageSizeFromInputs();
-        }
-
-        virtual void AttachInputs(const ComputationNodePtr singleInput)
-        {
-            m_children.resize(1);
-            m_children[0] = singleInput;
-        }
-
-        virtual void MoveMatricesToDevice(const DEVICEID_TYPE deviceId)
-        {
-            ComputationNode<ElemType>::MoveMatricesToDevice(deviceId);
-
-            if (deviceId != AUTOPLACEMATRIX)
-            {
-                if (m_gradientDotValue.GetDeviceId() != deviceId)
-                    m_gradientDotValue.TransferFromDeviceToDevice(m_gradientDotValue.GetDeviceId(), deviceId);
-                if (m_softmax.GetDeviceId() != deviceId)
-                    m_softmax.TransferFromDeviceToDevice(m_softmax.GetDeviceId(), deviceId);
-            }
-        }
-
-        virtual void CopyTo(const ComputationNodePtr nodeP, const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            ComputationNode<ElemType>::CopyTo(nodeP, newName, flags);
-            LogSoftmaxNode<ElemType>* node = (LogSoftmaxNode<ElemType>*) nodeP;
-
-            if (flags & CopyNodeFlags::copyNodeValue)
-            {
-                node->m_gradientDotValue = m_gradientDotValue;
-                node->m_softmax = m_softmax;
-            }
-        }
-
-        // copy constructor
-        LogSoftmaxNode(const LogSoftmaxNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags)
-            : ComputationNode<ElemType>(node->m_deviceId), m_gradientDotValue(node->m_deviceId), m_softmax(node->m_deviceId)
-        {
-            node->CopyTo(this, newName, flags);
-        }
-
-        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            const std::wstring& name = (newName == L"") ? NodeName() : newName;
-
-            ComputationNodePtr node = new LogSoftmaxNode<ElemType>(this, name, flags);
-            return node;
-        }
-
-    private:
-        Matrix<ElemType> m_gradientDotValue;
-        Matrix<ElemType> m_softmax;
-    };
-
-    template class LogSoftmaxNode<float>;
-    template class LogSoftmaxNode<double>;
-
-    template<class ElemType>
-    class SumElementsNode : public ComputationNode<ElemType>
-    {
-        UsingComputationNodeMembers;
-    public:
-        SumElementsNode(const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)  
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            m_deviceId = deviceId;
-            MoveMatricesToDevice(deviceId);
-            InitRecurrentNode();
-        }
-
-        SumElementsNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            LoadFromFile(fstream, modelVersion, deviceId);
-        }
-
-        // copy constructor
-        SumElementsNode(const SumElementsNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags) : ComputationNode<ElemType>(node->m_deviceId)
-        {
-            node->CopyTo(this, newName, flags);
-        }
-
-        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            const std::wstring& name = (newName == L"")?NodeName():newName;
-                
-            ComputationNodePtr node = new SumElementsNode<ElemType>(this, name, flags);
-            return node;
-        }
-
-        virtual const std::wstring OperationName() const {return TypeName();}
-        static const std::wstring TypeName() {return L"SumElements";} 
-
-        virtual void ComputeInputPartial(const size_t inputIndex)
-        {
-            if (inputIndex != 0)
-                throw std::invalid_argument("SumElements only has one input.");
-            ComputeInputPartialS(Inputs(0)->GradientValues(), GradientValues());
-        }
-
-        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
-        {
-            if (inputIndex != 0)
-                throw std::invalid_argument("SumElements only has one input.");
-
-            Matrix<ElemType> sliceInputGrad = Inputs(0)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            ComputeInputPartialS(sliceInputGrad, sliceOutputGrad);
-        }
-
-        static void WINAPI ComputeInputPartialS(Matrix<ElemType>& inputGradientValues, const Matrix<ElemType>& gradientValues)  
-        {
-            inputGradientValues += gradientValues; //here the assumption is that gradientValues are 1x1 matrix
-        }
-
-        virtual void EvaluateThisNode()  
-        {
-            EvaluateThisNodeS(m_functionValues, Inputs(0)->FunctionValues());
-        }
-
-        virtual void EvaluateThisNode(const size_t timeIdxInSeq)
-        {
-            Matrix<ElemType> sliceInputValue = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            EvaluateThisNodeS(sliceOutputValue, sliceInputValue);
-        }
-
-        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, const Matrix<ElemType>& inputFunctionValues)  
-        {
-            functionValues.AssignSumOfElements(inputFunctionValues);
-#if NANCHECK
-            functionValues.HasNan("SumElements");
-#endif
-        }
-
-        virtual void Validate()
-        {
-            PrintSelfBeforeValidation();
-
-            if (m_children.size() != 1) 
-                throw std::logic_error("SumElements operation should have one input.");
-
-            if (Inputs(0)->FunctionValues().GetNumElements() == 0)
-                throw std::logic_error("SumElements operation: the input node has 0 element.");
-
-            FunctionValues().Resize(1, 1);
-            CopyImageSizeFromInputs(); 
-        }
-
-        virtual void CopyImageSizeFromInputs()
-        {
-            CopyImageSizeFromInput(0, false);
-
-            m_outputWidth = 1;
-            m_outputHeight = 1;        
-            m_outputChannels = 1;
-        }
-
-        virtual void AttachInputs(const ComputationNodePtr singleInput) 
-        {
-            m_children.resize(1);
-            m_children[0] = singleInput;
-        }
-    };
-
-    template class SumElementsNode<float>; 
-    template class SumElementsNode<double>;
-
-    //this node is used to extract part of the input by rows as the output
-    //it has to be continuous segments of rows since each column is treated as one sample
-    template<class ElemType>
-    class RowSliceNode : public ComputationNode<ElemType>
-    {
-        UsingComputationNodeMembers;
-    public:
-        RowSliceNode(const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId), m_startIndex(0), m_numRows (0) 
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            m_deviceId = deviceId;
-            MoveMatricesToDevice(deviceId);
-            InitRecurrentNode();
-        }
-
-        RowSliceNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            LoadFromFile(fstream, modelVersion, deviceId);
-        }
-
-        // copy constructor
-        RowSliceNode(const RowSliceNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags) : ComputationNode<ElemType>(node->m_deviceId)
-        {
-            node->CopyTo(this, newName, flags);
-        }
-        
-        RowSliceNode(const DEVICEID_TYPE deviceId, size_t start_index, size_t num_rows, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)  
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            m_deviceId = deviceId;
-            m_startIndex = start_index;
-            m_numRows = num_rows;
-            
-
-            MoveMatricesToDevice(deviceId);
-            InitRecurrentNode();
-        }
-
-        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            const std::wstring& name = (newName == L"")?NodeName():newName;
-                
-            ComputationNodePtr node = new RowSliceNode<ElemType>(this, name, flags);
-            return node;
-        }
-
-        virtual void CopyTo(const ComputationNodePtr nodeP, const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            ComputationNode<ElemType>::CopyTo(nodeP, newName, flags);
-            RowSliceNode<ElemType>* node = (RowSliceNode<ElemType>*) nodeP;
-
-            node->m_startIndex = m_startIndex;
-            node->m_numRows = m_numRows;
-        }
-
-        virtual void SaveToFile(File& fstream) const
-        {
-            ComputationNode<ElemType>::SaveToFile(fstream);
-
-            fstream << m_startIndex << m_numRows;
-        }
-        
-        virtual void LoadFromFile(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX)
-        {
-            ComputationNode<ElemType>::LoadFromFile(fstream, modelVersion, deviceId);
-
-            fstream >> m_startIndex >> m_numRows;
-        }
-
-        virtual const std::wstring OperationName() const {return TypeName();}
-        static const std::wstring TypeName() {return L"RowSlice";} 
-
-        virtual void PrintSelfBeforeValidation(bool allowNulls = false) const
-        {
-            fprintf(stderr, "\nValidating --> %ls = %ls", NodeName().c_str(), OperationName().c_str());
-
-            if (!IsLeaf())
-            {
-                fprintf(stderr, "(");
-                for (size_t i = 0; i<ChildrenSize(); i++)
-                {
-                    ComputationNodePtr child = Inputs(i);
-                    if (i > 0)
-                        fprintf(stderr, ", ");
-
-                    if (child == nullptr)
-                    {
-                        if (allowNulls)
-                        {
-                            fprintf(stderr, "NULL");
-                            continue;
-                        }
-                        throw runtime_error("One of the children is missing.");
-                    }
-
-                    fprintf(stderr, "%ls[%lu, %lu]", child->NodeName().c_str(), child->FunctionValues().GetNumRows(), child->FunctionValues().GetNumCols());
-
-                }
-                fprintf(stderr, ", StartIndex=%lu, NumOfRows=%lu)", m_startIndex, m_numRows);
-            }
-        }
-
-        virtual void ComputeInputPartial(const size_t inputIndex)
-        {
-            if (inputIndex != 0)
-                throw std::invalid_argument("RowSlice only has one input.");
-
-            ComputeInputPartialS(Inputs(0)->GradientValues(), GradientValues(), m_startIndex, m_numRows);
-        }
-
-        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
-        {
-            if (inputIndex != 0)
-                throw std::invalid_argument("RowSlice only has one input.");
-
-            Matrix<ElemType> sliceInputGrad = Inputs(0)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            ComputeInputPartialS(sliceInputGrad, sliceOutputGrad, m_startIndex, m_numRows);
-        }
-
-        static void WINAPI ComputeInputPartialS(Matrix<ElemType>& inputGradientValues, const Matrix<ElemType>& gradientValues, const size_t startIndex, const size_t numRows)  
-        {
-            inputGradientValues.AddToRowSliceValuesOf(gradientValues, startIndex, numRows); 
-        }
-
-        virtual void EvaluateThisNode()  
-        {
-            EvaluateThisNodeS(m_functionValues, Inputs(0)->FunctionValues(), m_startIndex, m_numRows);
-        }
-
-        virtual void EvaluateThisNode(const size_t timeIdxInSeq)
-        {
-            Matrix<ElemType> sliceInputValue = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            EvaluateThisNodeS(sliceOutputValue, sliceInputValue, m_startIndex, m_numRows);
-        }
-
-        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, const Matrix<ElemType>& inputFunctionValues, const size_t startIndex, const size_t numRows)  
-        {
-            functionValues.AssignRowSliceValuesOf(inputFunctionValues, startIndex, numRows);
-#if NANCHECK
-            functionValues.HasNan("RowSlice");
-#endif
-        }
-
-        virtual void Validate()
-        {
-            PrintSelfBeforeValidation();
-
-            if (m_children.size() != 1) 
-                throw std::logic_error("RowSlice operation should have one input.");
-
-            if (Inputs(0)->FunctionValues().GetNumElements() == 0)
-                throw std::logic_error("RowSlice operation: the input node has 0 element.");
-
-            if (Inputs(0)->FunctionValues().GetNumRows() < m_startIndex + m_numRows)
-                throw std::logic_error("RowSlice operation: m_startIndex + m_numRows exceeds number of rows in the input.");
-
-            FunctionValues().Resize(m_numRows, Inputs(0)->FunctionValues().GetNumCols());
-            CopyImageSizeFromInputs(); 
-        }
-
-        virtual void CopyImageSizeFromInputs()
-        {
-            CopyImageSizeFromInput(0, true);
-            m_outputHeight = m_numRows;        
-
-            //WARNING: this node will destroy the image size information from the child
-            if (m_inputWidth * m_inputChannels != 1)
-                fprintf(stderr, "WARNING: RowSlice operation cannot inherit image size information from its child. Image size info is lost.\n");
-        }
-
-        virtual void AttachInputs(const ComputationNodePtr singleInput) 
-        {
-            m_children.resize(1);
-            m_children[0] = singleInput;
-        }
-
-    private:
-        size_t m_startIndex, m_numRows;
-    };
-
-    template class RowSliceNode<float>; 
-    template class RowSliceNode<double>;
-
-    template<class ElemType>
-    class ScaleNode : public ComputationNode<ElemType>
-    {
-        UsingComputationNodeMembers;
-    public:
-        ScaleNode(const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)  
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            m_deviceId = deviceId;
-            MoveMatricesToDevice(deviceId);
-            InitRecurrentNode();
-        }
-
-        ScaleNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            LoadFromFile(fstream, modelVersion, deviceId);
-        }
-
-        // copy constructor
-        ScaleNode(const ScaleNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags) : ComputationNode<ElemType>(node->m_deviceId)
-        {
-            node->CopyTo(this, newName, flags);
-        }
-
-        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            const std::wstring& name = (newName == L"")?NodeName():newName;
-                
-            ComputationNodePtr node = new ScaleNode<ElemType>(this, name, flags);
-            return node;
-        }
-
-        virtual const std::wstring OperationName() const {return TypeName();}
-        static const std::wstring TypeName() {return L"Scale";} 
-
-        virtual void ComputeInputPartial(const size_t inputIndex)
-        {
-            if (inputIndex > 1)
-                throw std::invalid_argument("ScaleNode operation only takes two inputs.");
-
-            //left Node must be a scalar
-            if (inputIndex == 0)  //left derivative
-            {
-                ComputeInputPartialLeft(Inputs(1)->FunctionValues(), Inputs(0)->GradientValues(), GradientValues());
-            }
-            else
-            {
-                ComputeInputPartialRight(Inputs(0)->FunctionValues(), Inputs(1)->GradientValues(), GradientValues());
-            }
-        }
-
-        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
-        {
-            if (inputIndex > 1)
-                throw std::invalid_argument("ScaleNode operation only takes two inputs.");
-
-            //left Node must be a scalar
-            if (inputIndex == 0)  //left derivative
-            {
-                Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-                Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-                ComputeInputPartialLeft(sliceInput1Value, Inputs(0)->GradientValues(), sliceOutputGrad);
-            }
-            else
-            {
-                Matrix<ElemType> sliceInput1Grad = Inputs(1)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-                Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-                ComputeInputPartialRight(Inputs(0)->FunctionValues(), sliceInput1Grad, sliceOutputGrad);
-            }
-        }
-
-        static void WINAPI ComputeInputPartialLeft(const Matrix<ElemType>& inputFunctionValues, Matrix<ElemType>& inputGradientValues, const Matrix<ElemType>& gradientValues)  
-        {
-            inputGradientValues += Matrix<ElemType>::InnerProductOfMatrices(gradientValues, inputFunctionValues);
-        }
-
-        static void WINAPI ComputeInputPartialRight(const Matrix<ElemType>& inputFunctionValues, Matrix<ElemType>& inputGradientValues, const Matrix<ElemType>& gradientValues)  
-        {
-            Matrix<ElemType>::ScaleAndAdd(inputFunctionValues.Get00Element(), gradientValues, inputGradientValues);
-        }
-
-        virtual void EvaluateThisNode()  
-        {
-            EvaluateThisNodeS(FunctionValues(), Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues());
-        }
-
-        virtual void EvaluateThisNode(const size_t timeIdxInSeq)  
-        {
-            Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            EvaluateThisNodeS(sliceOutputValue, Inputs(0)->FunctionValues(), sliceInput1Value);
-        }
-
-        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, const Matrix<ElemType>& input0, const Matrix<ElemType>& input1)  
-        {
-            functionValues.AssignProductOf(input0.Get00Element(), input1);
-#if NANCHECK
-            functionValues.HasNan("Scale");
-#endif
-        }
-
-        virtual void Validate()
-        {
-            PrintSelfBeforeValidation();
-
-            if (m_children.size() != 2) 
-                throw std::logic_error("Scale operation requires two inputs.");
-
-            if (Inputs(0)->FunctionValues().GetNumElements() == 0 || Inputs(1)->FunctionValues().GetNumElements() == 0)
-                throw std::logic_error("Scale operation: one of the operands has 0 element.");
-
-            if (Inputs(0)->FunctionValues().GetNumRows() != 1 || Inputs(0)->FunctionValues().GetNumCols() != 1)
-                throw std::logic_error("The left value of ScaleNode must be a scalar value.");
-
-            FunctionValues().Resize(Inputs(1)->FunctionValues().GetNumRows(), Inputs(1)->FunctionValues().GetNumCols());
-            //left Node must be a scalar
-            CopyImageSizeFromInputs(); 
-        }
-
-        virtual void CopyImageSizeFromInputs()
-        {
-            CopyImageSizeFromInput(1); 
-        }
-
-        virtual void AttachInputs(const ComputationNodePtr scalarValue, const ComputationNodePtr Value) 
-        {
-            m_children.resize(2);
-            m_children[0] = scalarValue;
-            m_children[1] = Value;
-        }
-    };
-
-    template class ScaleNode<float>; 
-    template class ScaleNode<double>;
-
-    template<class ElemType>
-    class TimesNode : public ComputationNode<ElemType>
-    {
-        UsingComputationNodeMembers;
-    public:
-        TimesNode(const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)  
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            m_deviceId = deviceId;
-            MoveMatricesToDevice(deviceId);
-            InitRecurrentNode();
-        }
-
-        TimesNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            LoadFromFile(fstream, modelVersion, deviceId);
-        }
-
-        // copy constructor
-        TimesNode(const TimesNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags) : ComputationNode<ElemType>(node->m_deviceId)
-        {
-            node->CopyTo(this, newName, flags);
-        }
-
-        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            const std::wstring& name = (newName == L"")?NodeName():newName;
-                
-            ComputationNodePtr node = new TimesNode<ElemType>(this, name, flags);
-            return node;
-        }
-
-        virtual const std::wstring OperationName() const {return TypeName();}
-        static const std::wstring TypeName() {return L"Times";} 
-
-        virtual void ComputeInputPartial(const size_t inputIndex)
-        {
-            if (inputIndex > 1)
-                throw std::invalid_argument("Times operation only takes two inputs.");
-
-            if (inputIndex == 0)  //left derivative
-            {
-                ComputeInputPartialLeft(Inputs(1)->FunctionValues(), Inputs(0)->GradientValues(), GradientValues());
-            }
-            else  //right derivative
-            {
-                ComputeInputPartialRight(Inputs(0)->FunctionValues(), Inputs(1)->GradientValues(), GradientValues());
-            }
-        }
-
-        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
-        {
-            if (inputIndex > 1)
-                throw std::invalid_argument("Times operation only takes two inputs.");
-
-            if (inputIndex == 0)  //left derivative
-            {
-                Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-                Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-                ComputeInputPartialLeft(sliceInput1Value, Inputs(0)->GradientValues(), sliceOutputGrad);
-            }
-            else  //right derivative
-            {
-                Matrix<ElemType> sliceInput1Grad = Inputs(1)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-                Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-                ComputeInputPartialRight(Inputs(0)->FunctionValues(), sliceInput1Grad, sliceOutputGrad);
-            }
-        }
-
-        static void WINAPI ComputeInputPartialLeft(Matrix<ElemType>& inputFunctionValues, Matrix<ElemType>& inputGradientValues, const Matrix<ElemType>& gradientValues)  
-            {
-#if DUMPOUTPUT
-            gradientValues.Print("Gradient-in");
-            inputGradientValues.Print("child Gradient-in/out");
-            inputFunctionValues.Print("child Function values");
-#endif
-            //currently we only support one combination when the input is sparse.
-            if (inputFunctionValues.GetMatrixType() == SPARSE && inputGradientValues.GetMatrixType() == DENSE && gradientValues.GetMatrixType() == DENSE)
-                inputGradientValues.SwitchToMatrixType(SPARSE, MatrixFormat::matrixFormatSparseBlockCol, false);
-
-                Matrix<ElemType>::MultiplyAndAdd(gradientValues, false, inputFunctionValues, true, inputGradientValues);
-#if DUMPOUTPUT
-            inputGradientValues.Print("child Gradient-out");
-#endif
-        }
-
-        static void WINAPI ComputeInputPartialRight(Matrix<ElemType>& inputFunctionValues, Matrix<ElemType>& inputGradientValues, const Matrix<ElemType>& gradientValues)  
-            {
-#if DUMPOUTPUT
-            gradientValues.Print("Gradient-in");
-            inputGradientValues.Print("child Gradient-in/out");
-            inputFunctionValues.Print("child Function values");
-#endif
-                Matrix<ElemType>::MultiplyAndAdd(inputFunctionValues, true, gradientValues, false, inputGradientValues);
-#if DUMPOUTPUT
-            inputGradientValues.Print("child Gradient-out");
-#endif
-        }
-
-
-        virtual void EvaluateThisNode()  
-        {
-            EvaluateThisNodeS(FunctionValues(), Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues());
-        }
-
-        virtual void EvaluateThisNode(const size_t timeIdxInSeq)  
-        {
-            Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            EvaluateThisNodeS(sliceOutputValue, Inputs(0)->FunctionValues(), sliceInput1Value);
-        }
-
-        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, const Matrix<ElemType>& input0, const Matrix<ElemType>& input1)  
-        {
-#if DUMPOUTPUT
-            input0.Print("TimesNode - Input0");
-#endif
-            functionValues.AssignProductOf(input0, false, input1, false);
-#if NANCHECK
-            functionValues.HasNan("Times");
-#endif
-#if DUMPOUTPUT
-            functionValues.Print("TimesNode");
-#endif
-        }
-
-        virtual void Validate()
-        {
-            PrintSelfBeforeValidation();
-
-            if (m_children.size() != 2) 
-                throw std::logic_error("Times operation requires two inputs.");
-
-            //support automatic dimention inference for learnable parameters
-            size_t rows0 = Inputs(0)->FunctionValues().GetNumRows(), cols0 = Inputs(0)->FunctionValues().GetNumCols();
-            size_t rows1 = Inputs(1)->FunctionValues().GetNumRows(), cols1 = Inputs(1)->FunctionValues().GetNumCols();
-
-            if ((rows0 == 0 || cols1 == 0 ) && this->LoopId() < 0)
-                throw logic_error("Times operation: Inputs(0)->FunctionValues().GetNumRows() and Inputs(1)->FunctionValues().GetNumCols() should not be 0 since it cannot be automatically inferred");
-
-            if ((Inputs(0)->OperationName() == LearnableParameter<ElemType>::TypeName() && cols0 == 0 && rows1 != 0) && this->LoopId() < 0)
-                Inputs(0)->FunctionValues().Resize(rows0, rows1);
-
-            if (Inputs(1)->OperationName() == LearnableParameter<ElemType>::TypeName() && cols0 != 0 && rows1 == 0)
-                Inputs(1)->FunctionValues().Resize(cols0, cols1);
-
-            if ((Inputs(0)->FunctionValues().GetNumElements() == 0 || Inputs(1)->FunctionValues().GetNumElements() == 0)&& this->LoopId() < 0)
-                throw std::logic_error("Times operation: One of the operants has 0 elements.");
-
-            //cols0 and rows1 may have been changed so don't use them in the following check
-            if ((Inputs(1)->FunctionValues().GetNumRows() != Inputs(0)->FunctionValues().GetNumCols()) && this->LoopId() < 0)
-            {
-                throw std::logic_error("The Matrix dimension in the Times operation does not match.");
-            }
-            FunctionValues().Resize(rows0, cols1);
-            CopyImageSizeFromInputs(); 
-        }
-
-        virtual void CopyImageSizeFromInputs()  
-        {
-            CopyImageSizeFromInput(1, false); //the second one is the input since it's column wize
-
-            //after multiplication the structure is lost
-            m_outputWidth = 1;
-            m_outputHeight = Inputs(0)->FunctionValues().GetNumRows();
-            m_outputChannels =  1;
-        }
-
-        virtual void AttachInputs(const ComputationNodePtr leftNode, const ComputationNodePtr rightNode) 
-        {
-            m_children.resize(2);
-            m_children[0] = leftNode;
-            m_children[1] = rightNode;
-        }
-    };
-
-    template class TimesNode<float>; 
-    template class TimesNode<double>;
-
-    template<class ElemType>
-    class ElementTimesNode : public ComputationNode<ElemType>
-    {
-        UsingComputationNodeMembers;
-    public:
-        ElementTimesNode(const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)  
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            m_deviceId = deviceId;
-            MoveMatricesToDevice(deviceId);
-            InitRecurrentNode();
-        }
-
-        ElementTimesNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            LoadFromFile(fstream, modelVersion, deviceId);
-        }
-
-        // copy constructor
-        ElementTimesNode(const ElementTimesNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags) : ComputationNode<ElemType>(node->m_deviceId)
-        {
-            node->CopyTo(this, newName, flags);
-        }
-
-        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            const std::wstring& name = (newName == L"")?NodeName():newName;
-                
-            ComputationNodePtr node = new ElementTimesNode<ElemType>(this, name, flags);
-            return node;
-        }
-
-        virtual const std::wstring OperationName() const {return TypeName();}
-        static const std::wstring TypeName() {return L"ElementTimes";} 
-
-        virtual void ComputeInputPartial(const size_t inputIndex)  
-        {
-            if (inputIndex > 1)
-                throw std::invalid_argument("ElementTimes operation only takes two inputs.");
-
-            ComputeInputPartialS(Inputs(1-inputIndex)->FunctionValues(), Inputs(inputIndex)->GradientValues(), GradientValues());
-        }
-
-        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)  
-        {
-            if (inputIndex > 1)
-                throw std::invalid_argument("ElementTimes operation only takes two inputs.");
-
-            Matrix<ElemType> sliceInput0Grad = Inputs(inputIndex)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            Matrix<ElemType> sliceInput1Value = Inputs(1-inputIndex)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            ComputeInputPartialS(sliceInput1Value, sliceInput0Grad, sliceOutputGrad);
-        }
-
-        // depending on inputIndex, all the input variables change meaning
-        // inputIndex == 0 (left) -  inputGradientValues[0], inputFunctionValues[1]
-        // inputIndex == 1 (right) - inputGradientValues[1], inputFunctionValues[0]
-        static void WINAPI ComputeInputPartialS(Matrix<ElemType>& inputFunctionValues, Matrix<ElemType>& inputGradientValues, const Matrix<ElemType>& gradientValues)  
-        {
-            inputGradientValues.AddElementProductOf(gradientValues, inputFunctionValues);
-#if NANCHECK
-            inputGradientValues.HasNan("ElementTimes");
-#endif
-        }
-
-
-        virtual void EvaluateThisNode()  
-        {
-            EvaluateThisNodeS(FunctionValues(), Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues());
-        }
-
-        virtual void EvaluateThisNode(const size_t timeIdxInSeq)  
-        {
-            Matrix<ElemType> sliceInput0Value = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            EvaluateThisNodeS(sliceOutputValue, sliceInput0Value, sliceInput1Value);
-        }
-
-        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, const Matrix<ElemType>& input0, const Matrix<ElemType>& input1)  
-        {
-            functionValues.AssignElementProductOf(input0, input1);
-#if NANCHECK
-            functionValues.HasNan("ElementTimes");
-#endif
-        }
-
-        virtual void Validate()
-        {
-            PrintSelfBeforeValidation();
-
-            if (m_children.size() != 2) 
-                throw std::logic_error("ElementTimes operation requires two inputs.");
-
-            size_t index = 0;
-            if (Inputs(index)->OperationName() == LearnableParameter<ElemType>::TypeName())
-            {
-                size_t rows = Inputs(index)->FunctionValues().GetNumRows() == 0? Inputs(1-index)->FunctionValues().GetNumRows() : Inputs(index)->FunctionValues().GetNumRows();
-                size_t cols = Inputs(index)->FunctionValues().GetNumCols() == 0? Inputs(1-index)->FunctionValues().GetNumCols() : Inputs(index)->FunctionValues().GetNumCols();
-                Inputs(index)->FunctionValues().Resize(rows, cols);
-            }
-
-            index = 1;
-            if (Inputs(index)->OperationName() == LearnableParameter<ElemType>::TypeName())
-            {
-                size_t rows = Inputs(index)->FunctionValues().GetNumRows() == 0? Inputs(1-index)->FunctionValues().GetNumRows() : Inputs(index)->FunctionValues().GetNumRows();
-                size_t cols = Inputs(index)->FunctionValues().GetNumCols() == 0? Inputs(1-index)->FunctionValues().GetNumCols() : Inputs(index)->FunctionValues().GetNumCols();
-                Inputs(index)->FunctionValues().Resize(rows, cols);
-            }
-
-            if (Inputs(0)->FunctionValues().GetNumElements() == 0 || Inputs(1)->FunctionValues().GetNumElements() == 0)
-                throw std::logic_error("ElementTimes operation: one of the operants has 0 element.");
-
-            if (Inputs(1)->FunctionValues().GetNumRows() != Inputs(0)->FunctionValues().GetNumRows() ||
-                Inputs(1)->FunctionValues().GetNumCols() != Inputs(0)->FunctionValues().GetNumCols())
-                throw std::logic_error("The Matrix<ElemType> dimension in the ElementTimes operation does not match.");
-
-            FunctionValues().Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(0)->FunctionValues().GetNumCols());
-            CopyImageSizeFromInputs(); 
-        }
-
-        virtual void CopyImageSizeFromInputs()
-        {
-            if (IsChildAnImage(0))  //when conflict, give priority to child 0
-                CopyImageSizeFromInput(0);
-            else
-                CopyImageSizeFromInput(1);
-        }
-
-        virtual void AttachInputs(const ComputationNodePtr leftNode, const ComputationNodePtr rightNode) 
-        {
-            m_children.resize(2);
-            m_children[0] = leftNode;
-            m_children[1] = rightNode;
-        }
-    };
-
-    template class ElementTimesNode<float>; 
-    template class ElementTimesNode<double>;
-
-    template<class ElemType>
-    class PlusNode : public ComputationNode<ElemType>
-    {
-        UsingComputationNodeMembers;
-    public:
-        PlusNode(const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)  
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            m_deviceId = deviceId;
-            MoveMatricesToDevice(deviceId);
-            InitRecurrentNode();
-        }
-
-        PlusNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            LoadFromFile(fstream, modelVersion, deviceId);
-        }
-
-        // copy constructor
-        PlusNode(const PlusNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags) : ComputationNode<ElemType>(node->m_deviceId)
-        {
-            node->CopyTo(this, newName, flags);
-        }
-
-        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            const std::wstring& name = (newName == L"")?NodeName():newName;
-                
-            ComputationNodePtr node = new PlusNode<ElemType>(this, name, flags);
-            return node;
-        }
-
-        virtual const std::wstring OperationName() const {return TypeName();}
-        static const std::wstring TypeName() {return L"Plus";} 
-
-        virtual void ComputeInputPartial(const size_t inputIndex)
-        {
-            if (inputIndex > 1)
-                throw std::invalid_argument("Plus operation only takes two inputs.");
-            ComputationNodePtr child = Inputs(inputIndex);
-            ComputeInputPartialS(FunctionValues(), GradientValues(), child->FunctionValues(), child->GradientValues());
-        }
-
-        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
-        {
-            if (inputIndex > 1)
-                throw std::invalid_argument("Plus operation only takes two inputs.");
-
-            //only the one with more columns can be sliced, if both have same columns both are sliced
-            size_t cols0 = Inputs(inputIndex)->FunctionValues().GetNumCols(), cols1=Inputs(1-inputIndex)->FunctionValues().GetNumCols();
-
-            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            if (cols0 >= cols1)
-            {
-                Matrix<ElemType> sliceInput0Grad = Inputs(inputIndex)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-                Matrix<ElemType> sliceInput0Value = Inputs(inputIndex)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-                ComputeInputPartialS(sliceOutputValue, sliceOutputGrad, sliceInput0Value, sliceInput0Grad);
-            }
-            else 
-            {
-                ComputeInputPartialS(sliceOutputValue, sliceOutputGrad, Inputs(inputIndex)->FunctionValues(), Inputs(inputIndex)->GradientValues());
-            }
-        }
-
-        static void WINAPI ComputeInputPartialS(Matrix<ElemType>& functionValues, Matrix<ElemType>& gradientValues, Matrix<ElemType>& inputFunctionValues, Matrix<ElemType>& inputGradientValues)
-        {
-#if DUMPOUTPUT
-
-            functionValues.Print("PlusNode");
-#endif
-
-            size_t rowsc = inputFunctionValues.GetNumRows(), colsc = inputFunctionValues.GetNumCols();
-            size_t rowsp = functionValues.GetNumRows(), colsp = functionValues.GetNumCols();
-#if DUMPOUTPUT
-            fprintf(stderr, "input dimensions %lld x %lld,  this node dimensions %lld x %lld\n", rowsc, colsc, rowsp, colsp);
-            gradientValues.Print("Gradient-in");
-            inputGradientValues.Print("child Gradient-in/out");
-#endif
-
-            if (colsc == colsp && rowsc == rowsp)
-                inputGradientValues += gradientValues;
-            else if (colsc == 1 && rowsc == 1)
-                inputGradientValues += gradientValues.SumOfElements();
-            else if (colsc == 1 && colsp != 1)
-            {
-                size_t colspExpand = rowsp*colsp/rowsc;
-                gradientValues.Reshape(rowsc, colspExpand);
-                Matrix<ElemType>::MultiplyAndAdd(gradientValues, false, ConstOnes(colspExpand, 1, functionValues.GetDeviceId()), false, inputGradientValues);
-                gradientValues.Reshape(rowsp, colsp);
-            }
-            else if (rowsc == 1 && rowsp != 1)
-                Matrix<ElemType>::MultiplyAndAdd(ConstOnes(1, rowsp,functionValues.GetDeviceId()), false, gradientValues, false, inputGradientValues);
-            else
-                throw std::runtime_error("Plus partial: unexpected condition.");
-#if DUMPOUTPUT
-            inputGradientValues.Print("child Gradient-out");
-#endif
-                }
-
-
-        virtual void EvaluateThisNode()  
-        {
-            EvaluateThisNodeS(FunctionValues(), Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues());
-        }
-
-        virtual void EvaluateThisNode(const size_t timeIdxInSeq)  
-        {
-            size_t cols0 = Inputs(0)->FunctionValues().GetNumCols(), cols1=Inputs(1)->FunctionValues().GetNumCols();
-
-            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            //only the one with more columns can be sliced, if both have same columns both are sliced
-            if (cols0 == cols1)
-            {
-                Matrix<ElemType> sliceInput0Value = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-                Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-                EvaluateThisNodeS(sliceOutputValue, sliceInput0Value, sliceInput1Value);
-            }
-            else if (cols0 > cols1)
-            {
-                Matrix<ElemType> sliceInput0Value = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-                EvaluateThisNodeS(sliceOutputValue, sliceInput0Value, Inputs(1)->FunctionValues());
-            }
-            else //cols0 < cols1)
-            {
-                Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-                EvaluateThisNodeS(sliceOutputValue, Inputs(0)->FunctionValues(), sliceInput1Value);
-            }
-        }
-
-        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, Matrix<ElemType>& inputFunctionValues0, Matrix<ElemType>& inputFunctionValues1)  
-        {
-            size_t rows0 = inputFunctionValues0.GetNumRows(), cols0 = inputFunctionValues0.GetNumCols();
-            size_t rows1 = inputFunctionValues1.GetNumRows(), cols1 = inputFunctionValues1.GetNumCols();
-            functionValues.Resize(max(rows0, rows1), max(cols0,cols1));
-
-            if ((rows0 == rows1 && cols0 == cols1) || ((rows0 == 1 || rows1 == 1) && cols0 == cols1))
-            {
-                functionValues.AssignSumOf(inputFunctionValues0, inputFunctionValues1);
-            }
-            else if (cols0 == 1 && rows1 % rows0 == 0)  //one is col vec with divisable rows, including scalar
-            {
-                inputFunctionValues1.Reshape(rows0, rows1 * cols1 / rows0);
-                functionValues.AssignSumOf(inputFunctionValues0, inputFunctionValues1);
-                inputFunctionValues1.Reshape(rows1, cols1);
-                functionValues.Reshape(max(rows0, rows1), max(cols0,cols1));
-            }
-            else if (cols1 == 1 && rows0 % rows1 == 0)  //one is col vec with divisable rows, including scalar
-            {
-                inputFunctionValues0.Reshape(rows1, rows0 * cols0 / rows1);
-                functionValues.AssignSumOf(inputFunctionValues0, inputFunctionValues1);
-                inputFunctionValues0.Reshape(rows0, cols0);
-                functionValues.Reshape(max(rows0, rows1), max(cols0,cols1));
-            }       
-
-#if NANCHECK
-            functionValues.HasNan("Plus");
-#endif
-#if DUMPOUTPUT
-            functionValues.Print("PlusNode");
-#endif
-        }
-
-        virtual void Validate()
-        {
-            PrintSelfBeforeValidation();
-
-            if (m_children.size() != 2) 
-                throw std::logic_error("Plus operation requires two inputs.");
-
-            //if dimention not specified we assume two operants' dimentions should be the same
-            size_t index = 0;
-            if (Inputs(index)->OperationName() == LearnableParameter<ElemType>::TypeName())
-            {
-                size_t rows = Inputs(index)->FunctionValues().GetNumRows() == 0? Inputs(1-index)->FunctionValues().GetNumRows() : Inputs(index)->FunctionValues().GetNumRows();
-                size_t cols = Inputs(index)->FunctionValues().GetNumCols() == 0? Inputs(1-index)->FunctionValues().GetNumCols() : Inputs(index)->FunctionValues().GetNumCols();
-                Inputs(index)->FunctionValues().Resize(rows, cols);
-            }
-
-            index = 1;
-            if (Inputs(index)->OperationName() == LearnableParameter<ElemType>::TypeName())
-            {
-                size_t rows = Inputs(index)->FunctionValues().GetNumRows() == 0? Inputs(1-index)->FunctionValues().GetNumRows() : Inputs(index)->FunctionValues().GetNumRows();
-                size_t cols = Inputs(index)->FunctionValues().GetNumCols() == 0? Inputs(1-index)->FunctionValues().GetNumCols() : Inputs(index)->FunctionValues().GetNumCols();
-                Inputs(index)->FunctionValues().Resize(rows, cols);
-            }
-
-            if ((Inputs(0)->FunctionValues().GetNumElements() == 0 || Inputs(1)->FunctionValues().GetNumElements() == 0) && this->LoopId() < 0)
-                throw std::logic_error("Plus operation: one of the operants has 0 element.");
-
-            size_t rows0 = Inputs(0)->FunctionValues().GetNumRows(), cols0 = Inputs(0)->FunctionValues().GetNumCols();
-            size_t rows1 = Inputs(1)->FunctionValues().GetNumRows(), cols1 = Inputs(1)->FunctionValues().GetNumCols();
-
-            if ((!(rows0 == rows1 && cols0 == cols1) &&  //match size
-                !((rows0 == 1 || rows1 == 1) && cols0 == cols1) && //one is row vec
-                !((cols0 == 1 && rows1 % rows0 == 0) || (cols1 == 1 && rows0 % rows1 == 0)))&& this->LoopId() < 0) //one is col vec with divisable rows, including scalar
-            {
-                throw std::logic_error("The Matrix dimension in the Plus operation does not match.");
-            }       
-
-            FunctionValues().Resize(max(rows0, rows1), max(cols0,cols1) );
-            CopyImageSizeFromInputs(); 
-        }
-
-        virtual void CopyImageSizeFromInputs() //based on the matrix with larger size
-        {
-            size_t rows0 = Inputs(0)->FunctionValues().GetNumRows(), cols0 = Inputs(0)->FunctionValues().GetNumCols();
-            size_t rows1 = Inputs(1)->FunctionValues().GetNumRows(), cols1 = Inputs(1)->FunctionValues().GetNumCols();
-
-            if (rows0 > rows1 || cols0 > cols1) //child 0 is larger
-                CopyImageSizeFromInput(0);
-            else if (rows0 < rows1 || cols0 < cols1) //child 1 is larger
-                CopyImageSizeFromInput(1);
-            else //same size
-            {
-                if (IsChildAnImage(0))  //when conflict, give priority to child 0
-                    CopyImageSizeFromInput(0);
-                else
-                    CopyImageSizeFromInput(1);
-            }
-        }
-
-        virtual void AttachInputs(const ComputationNodePtr leftNode, const ComputationNodePtr rightNode) 
-        {
-            m_children.resize(2);
-            m_children[0] = leftNode;
-            m_children[1] = rightNode;
-        }
-    };
-
-    template class PlusNode<float>; 
-    template class PlusNode<double>;
-
-    template<class ElemType>
-    class MinusNode : public ComputationNode<ElemType>
-    {
-        UsingComputationNodeMembers;
-    public:
-        MinusNode(const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)  
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            m_deviceId = deviceId;
-            MoveMatricesToDevice(deviceId);
-            InitRecurrentNode();
-        }
-
-        MinusNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            LoadFromFile(fstream, modelVersion, deviceId);
-        }
-
-        // copy constructor
-        MinusNode(const MinusNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags) : ComputationNode<ElemType>(node->m_deviceId)
-        {
-            node->CopyTo(this, newName, flags);
-        }
-
-        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            const std::wstring& name = (newName == L"")?NodeName():newName;
-                
-            ComputationNodePtr node = new MinusNode<ElemType>(this, name, flags);
-            return node;
-        }
-
-        virtual const std::wstring OperationName() const {return TypeName();}
-        static const std::wstring TypeName() {return L"Minus";}
-
-        virtual void ComputeInputPartial(const size_t inputIndex)
-        {
-            if (inputIndex > 1)
-                throw std::invalid_argument("Minus operation only takes two inputs.");
-
-            // prepare a matrix of ones as needed
-            ComputationNodePtr child = Inputs(inputIndex);
-            size_t rowsc = child->FunctionValues().GetNumRows(), colsc = child->FunctionValues().GetNumCols();
-            size_t rowsp = FunctionValues().GetNumRows(), colsp = FunctionValues().GetNumCols();
-
-            Matrix<ElemType> ones = Matrix<ElemType>();
-            if (colsc == 1 && colsp != 1)
-            {
-                size_t colspExpand = rowsp*colsp/rowsc;
-                ones = ConstOnes(colspExpand, 1,FunctionValues().GetDeviceId());
-            }
-            else if (rowsc == 1 && rowsp != 1)
-            {
-                ones = ConstOnes(1, rowsp,FunctionValues().GetDeviceId());
-            }
-
-            if (inputIndex == 0)  //left derivative
-            {
-                ComputeInputPartialLeft(child->FunctionValues(), child->GradientValues(), FunctionValues(), GradientValues(), ones); 
-            }
-            else  //right derivative
-        {
-                ComputeInputPartialRight(child->FunctionValues(), child->GradientValues(), FunctionValues(), GradientValues(), ones); 
-            }
-        }
-
-        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq) 
-        {
-            //only the one with more columns can be sliced, if both have same columns both are sliced
-            size_t cols0 = Inputs(inputIndex)->FunctionValues().GetNumCols(), cols1=Inputs(1-inputIndex)->FunctionValues().GetNumCols();
-
-            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            Matrix<ElemType> sliceInput0Grad = Inputs(inputIndex)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceInput0Value = Inputs(inputIndex)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            Matrix<ElemType> ones = Matrix<ElemType>();
-
-            size_t rowsc = Inputs(inputIndex)->FunctionValues().GetNumRows(), rowsp = FunctionValues().GetNumRows();
-            size_t colsp = FunctionValues().GetNumCols();
-
-            if (cols0 >= cols1) //indicates cols0 == functionValue.cols
-            {
-
-                if (rowsc == 1 && rowsp != 1)
-        {
-                    ones = ConstOnes(1, rowsp, FunctionValues().GetDeviceId());
-                }
-    
-                if (inputIndex == 0)  //left derivative
-            {
-                    ComputeInputPartialLeft(sliceInput0Value, sliceInput0Grad, sliceOutputValue, sliceOutputGrad, ones); 
-            }
-                else  //right derivativeAzqz
-            {
-                    ComputeInputPartialRight(sliceInput0Value, sliceInput0Grad, sliceOutputValue, sliceOutputGrad, ones); 
-            }
-            }
-            else // cols0 < cols1 -> cols0=1
-            {
-                if (cols0 == 1 && colsp != 1)
-                {
-                    size_t colspExpand = rowsp*colsp/rowsc;
-                    ones = ConstOnes(colspExpand, 1,FunctionValues().GetDeviceId());
-                }
-
-                if (inputIndex == 0)  //left derivative
-            {
-                    ComputeInputPartialLeft(sliceInput0Value, sliceInput0Grad, sliceOutputValue, sliceOutputGrad, ones); 
-                }
-                else  //right derivative
-                {
-                    ComputeInputPartialRight(sliceInput0Value, sliceInput0Grad, sliceOutputValue, sliceOutputGrad, ones); 
-                }
-            }
-        }
-
-        static void WINAPI ComputeInputPartialLeft(Matrix<ElemType>& childFunctionValues, Matrix<ElemType>& childGradientValues, const Matrix<ElemType>& functionValues, /*const*/ Matrix<ElemType>& gradientValues, /*const*/ Matrix<ElemType>& ones)
-            {
-            ComputeInputPartialS(0, childFunctionValues, childGradientValues, functionValues, gradientValues, ones);
-        }
-
-        static void WINAPI ComputeInputPartialRight(Matrix<ElemType>& childFunctionValues, Matrix<ElemType>& childGradientValues, const Matrix<ElemType>& functionValues, /*const*/ Matrix<ElemType>& gradientValues, /*const*/ Matrix<ElemType>& ones)  
-                {
-            ComputeInputPartialS(1, childFunctionValues, childGradientValues, functionValues, gradientValues, ones);
-        }
-
-        static void WINAPI ComputeInputPartialS(const size_t inputIndex, Matrix<ElemType>& childFunctionValues, Matrix<ElemType>& childGradientValues, const Matrix<ElemType>& functionValues, /*const*/ Matrix<ElemType>& gradientValues, /*const*/ Matrix<ElemType>& ones)
-        {
-            ElemType weight = ElemType(inputIndex == 0? 1:-1);
-            size_t rowsc = childFunctionValues.GetNumRows(), colsc = childFunctionValues.GetNumCols();
-            size_t rowsp = functionValues.GetNumRows(), colsp = functionValues.GetNumCols();
-
-            if (colsc == 1 && colsp != 1)
-            {
-                size_t colspExpand = rowsp*colsp/rowsc;
-                ones.Resize(colspExpand, 1);
-                }
-            else if (rowsc == 1 && rowsp != 1)
-            {
-                ones.Resize(1, rowsp);
-            }
-
-            if (colsc == colsp && rowsc == rowsp)
-            {
-                if (inputIndex == 0)
-                    childGradientValues += gradientValues;
-                else
-                    childGradientValues -= gradientValues;
-            }
-            else if (colsc == 1 && rowsc == 1)
-                {
-                if (inputIndex == 0)
-                    childGradientValues += gradientValues.SumOfElements();
-                else
-                    childGradientValues -= gradientValues.SumOfElements();
-                }
-            else if (colsc == 1 && colsp != 1)
-            {
-                size_t colspExpand = rowsp*colsp/rowsc;
-                gradientValues.Reshape(rowsc, colspExpand);
-                Matrix<ElemType>::MultiplyAndWeightedAdd(weight, gradientValues, false, ones, false, 1, childGradientValues);
-                gradientValues.Reshape(rowsp, colsp);
-            }
-            else if (rowsc == 1 && rowsp != 1)
-                Matrix<ElemType>::MultiplyAndWeightedAdd(weight, ones, false, gradientValues, false, 1, childGradientValues);
-            else
-                throw std::runtime_error("Minus partial: unexpected condition.");
-        }
-
-
-        virtual void EvaluateThisNode()  
-        {
-            EvaluateThisNodeS(FunctionValues(), Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues());  
-        }
-
-        virtual void EvaluateThisNode(const size_t timeIdxInSeq)
-        {
-            size_t cols0 = Inputs(0)->FunctionValues().GetNumCols(), cols1=Inputs(1)->FunctionValues().GetNumCols();
-
-            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            //only the one with more columns can be sliced, if both have same columns both are sliced
-            if (cols0 == cols1)
-            {
-                Matrix<ElemType> sliceInput0Value = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-                Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-                EvaluateThisNodeS(sliceOutputValue, sliceInput0Value, sliceInput1Value);
-            }
-            else if (cols0 > cols1)
-            {
-                Matrix<ElemType> sliceInput0Value = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-                EvaluateThisNodeS(sliceOutputValue, sliceInput0Value, Inputs(1)->FunctionValues());
-            }
-            else //cols0 < cols1)
-            {
-                Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-                EvaluateThisNodeS(sliceOutputValue, Inputs(0)->FunctionValues(), sliceInput1Value);
-            }
-        }
-
-        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, Matrix<ElemType>& in0, Matrix<ElemType>& in1)  
-        {
-            size_t rows0 = in0.GetNumRows(), cols0 = in0.GetNumCols();
-            size_t rows1 = in1.GetNumRows(), cols1 = in1.GetNumCols();
-            functionValues.Resize(max(rows0, rows1), max(cols0,cols1));
-
-            if ((rows0 == rows1 && cols0 == cols1) || ((rows0 == 1 || rows1 == 1) && cols0 == cols1))
-            {
-                functionValues.AssignDifferenceOf(in0, in1);
-            }
-            else if (cols0 == 1 && rows1 % rows0 == 0)  //one is col vec with divisable rows, including scalar
-            {
-                in1.Reshape(rows0, rows1 * cols1 / rows0);
-                functionValues.AssignDifferenceOf(in0, in1);
-                in1.Reshape(rows1, cols1);
-                functionValues.Reshape(max(rows0, rows1), max(cols0,cols1));
-            }
-            else if (cols1 == 1 && rows0 % rows1 == 0)  //one is col vec with divisable rows, including scalar
-            {
-                in0.Reshape(rows1, rows0 * cols0 / rows1);
-                functionValues.AssignDifferenceOf(in0, in1);
-                in0.Reshape(rows0, cols0);
-                functionValues.Reshape(max(rows0, rows1), max(cols0,cols1));
-            }      
-#if NANCHECK
-            functionValues.HasNan("Minus");
-#endif
-        }
-
-        virtual void Validate()
-        {
-            PrintSelfBeforeValidation();
-
-            if (m_children.size() != 2) 
-                throw std::logic_error("Minus operation requires two inputs.");
-
-            //if dimention is missing make the two operatants to have same size
-            size_t index = 0;
-            if (Inputs(index)->OperationName() == LearnableParameter<ElemType>::TypeName())
-            {
-                size_t rows = Inputs(index)->FunctionValues().GetNumRows() == 0? Inputs(1-index)->FunctionValues().GetNumRows() : Inputs(index)->FunctionValues().GetNumRows();
-                size_t cols = Inputs(index)->FunctionValues().GetNumCols() == 0? Inputs(1-index)->FunctionValues().GetNumCols() : Inputs(index)->FunctionValues().GetNumCols();
-                Inputs(index)->FunctionValues().Resize(rows, cols);
-            }
-
-            index = 1;
-            if (Inputs(index)->OperationName() == LearnableParameter<ElemType>::TypeName())
-            {
-                size_t rows = Inputs(index)->FunctionValues().GetNumRows() == 0? Inputs(1-index)->FunctionValues().GetNumRows() : Inputs(index)->FunctionValues().GetNumRows();
-                size_t cols = Inputs(index)->FunctionValues().GetNumCols() == 0? Inputs(1-index)->FunctionValues().GetNumCols() : Inputs(index)->FunctionValues().GetNumCols();
-                Inputs(index)->FunctionValues().Resize(rows, cols);
-            }
-
-            if (Inputs(0)->FunctionValues().GetNumElements() == 0 || Inputs(1)->FunctionValues().GetNumElements() == 0)
-                throw std::logic_error("Minus operation: one of the operants has 0 element.");
-
-            size_t rows0 = Inputs(0)->FunctionValues().GetNumRows(), cols0 = Inputs(0)->FunctionValues().GetNumCols();
-            size_t rows1 = Inputs(1)->FunctionValues().GetNumRows(), cols1 = Inputs(1)->FunctionValues().GetNumCols();
-
-            if (!(rows0 == rows1 && cols0 == cols1) &&  //match size
-                !((rows0 == 1 || rows1 == 1) && cols0 == cols1) && //one is row vec
-                !((cols0 == 1 && rows1 % rows0 == 0) || (cols1 == 1 && rows0 % rows1 == 0)))  //one is col vec with divisable rows, including scalar
-            {
-                throw std::logic_error("The Matrix dimension in the Minus operation does not match.");
-            }       
-
-            FunctionValues().Resize(max(rows0, rows1), max(cols0,cols1) );
-            CopyImageSizeFromInputs(); 
-        }
-
-        virtual void CopyImageSizeFromInputs() //based on the matrix with larger size
-        {
-            size_t rows0 = Inputs(0)->FunctionValues().GetNumRows(), cols0 = Inputs(0)->FunctionValues().GetNumCols();
-            size_t rows1 = Inputs(1)->FunctionValues().GetNumRows(), cols1 = Inputs(1)->FunctionValues().GetNumCols();
-
-            if (rows0 > rows1 || cols0 > cols1) //child 0 is larger
-                CopyImageSizeFromInput(0);
-            else if (rows0 < rows1 || cols0 < cols1) //child 1 is larger
-                CopyImageSizeFromInput(1);
-            else //same size
-            {
-                if (IsChildAnImage(0))  //when conflict, give priority to child 0
-                    CopyImageSizeFromInput(0);
-                else
-                    CopyImageSizeFromInput(1);
-            }
-        }
-
-        virtual void AttachInputs(const ComputationNodePtr leftNode, const ComputationNodePtr rightNode) 
-        {
-            m_children.resize(2);
-            m_children[0] = leftNode;
-            m_children[1] = rightNode;
-        }
-    };
-
-    template class MinusNode<float>; 
-    template class MinusNode<double>;
-
-    //The first matrix should be a vector regpresting the diagonal of a square matrix in the DiagTimes operation
-    template<class ElemType>
-    class DiagTimesNode : public ComputationNode<ElemType>
-    {
-        UsingComputationNodeMembers;
-    public:
-        DiagTimesNode(const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"")  
-            : ComputationNode<ElemType>(deviceId), m_innerproduct(deviceId), m_rightGradient(deviceId)
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            m_deviceId = deviceId;
-            MoveMatricesToDevice(deviceId);
-            InitRecurrentNode();
-        }
-
-        DiagTimesNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"")
-            : ComputationNode<ElemType>(deviceId), m_innerproduct(deviceId), m_rightGradient(deviceId)
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            LoadFromFile(fstream, modelVersion, deviceId);
-        }
-
-        virtual const std::wstring OperationName() const {return TypeName();}
-        static const std::wstring TypeName() {return L"DiagTimes";} 
-
-        virtual void ComputeInputPartial(const size_t inputIndex)
-        {
-            if (inputIndex > 1)
-                throw std::invalid_argument("DiagTimes operation only takes two inputs.");
-
-            if (inputIndex == 0)  //left derivative
-            {
-                ComputeInputPartialLeft(m_innerproduct, Inputs(1)->FunctionValues(), Inputs(0)->GradientValues(), GradientValues());
-            }
-            else  //right derivative
-            {
-                ComputeInputPartialRight(m_rightGradient, Inputs(0)->FunctionValues(), Inputs(1)->GradientValues(), GradientValues());
-            }
-        }
-
-        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
-        {
-            if (inputIndex > 1)
-                throw std::invalid_argument("DiagTimes operation only takes two inputs.");
-
-            //left parameter (diag matix cannot be sliced)
-            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            if (inputIndex == 0)  //left derivative
-            {
-                Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-                ComputeInputPartialLeft(m_innerproduct, sliceInput1Value, Inputs(0)->GradientValues(), sliceOutputGrad);
-            }
-            else  //right derivative
-            {
-                Matrix<ElemType> sliceInput1Grad = Inputs(1)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-                ComputeInputPartialRight(m_rightGradient, Inputs(0)->FunctionValues(), sliceInput1Grad, sliceOutputGrad);
-            }
-        }
-
-        static void WINAPI ComputeInputPartialLeft(Matrix<ElemType>& temp, const Matrix<ElemType>& inputFunctionValues, Matrix<ElemType>& inputGradientValues, const Matrix<ElemType>& gradientValues)  
-        {
-            temp.AssignInnerProductOf(gradientValues, inputFunctionValues, false);
-            inputGradientValues += temp;
-        }
-
-        static void WINAPI ComputeInputPartialRight(Matrix<ElemType>& temp, const Matrix<ElemType>& inputFunctionValues, Matrix<ElemType>& inputGradientValues, const Matrix<ElemType>& gradientValues)  
-        {
-            temp.SetValue(gradientValues);
-            temp.ColumnElementMultiplyWith(inputFunctionValues);
-            inputGradientValues += temp;
-        }
-
-
-        virtual void EvaluateThisNode()  
-        {
-            EvaluateThisNodeS(FunctionValues(), Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues()); 
-        }
-
-        virtual void EvaluateThisNode(const size_t timeIdxInSeq)  
-        {
-            Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            EvaluateThisNodeS(sliceOutputValue, Inputs(0)->FunctionValues(), sliceInput1Value); 
-        }
-
-        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, const Matrix<ElemType>& inputFunctionValues0, const Matrix<ElemType>& inputFunctionValues1)  
-        {
-            functionValues.SetValue(inputFunctionValues1);
-            functionValues.ColumnElementMultiplyWith(inputFunctionValues0);
-        }
-
-        virtual void Validate()
-        {
-            PrintSelfBeforeValidation();
-
-            if (m_children.size() != 2) 
-                throw std::logic_error("DiagTimes operation requires two inputs.");
-
-            //if dimention not specified we assume two operants' dimentions should match
-            if (Inputs(0)->OperationName() == LearnableParameter<ElemType>::TypeName() && Inputs(0)->FunctionValues().GetNumRows() == 0 && Inputs(1)->FunctionValues().GetNumRows() != 0)
-            {
-                Inputs(0)->FunctionValues().Resize(Inputs(1)->FunctionValues().GetNumRows(), 1);
-            }
-
-            if (Inputs(1)->OperationName() == LearnableParameter<ElemType>::TypeName() && Inputs(0)->FunctionValues().GetNumRows() != 0 && Inputs(1)->FunctionValues().GetNumRows() == 0)
-            {
-                Inputs(1)->FunctionValues().Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(1)->FunctionValues().GetNumCols());
-            }
-
-            if (Inputs(0)->FunctionValues().GetNumElements() == 0 || Inputs(1)->FunctionValues().GetNumElements() == 0)
-                throw std::logic_error("DiagTimes operation: one of the operants has 0 element.");
-
-            if (Inputs(1)->FunctionValues().GetNumRows() != Inputs(0)->FunctionValues().GetNumRows())
-                throw std::logic_error("The Matrix dimension in the DiagTimes operation does not match.");
-
-            if (1 != Inputs(0)->FunctionValues().GetNumCols())
-                throw std::logic_error("The first matrix should be a vector regpresting the diagonal of a square matrix in the DiagTimes operation.");
-
-            FunctionValues().Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(1)->FunctionValues().GetNumCols());
-            m_innerproduct.Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(1)->FunctionValues().GetNumCols());
-            m_rightGradient.Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(1)->FunctionValues().GetNumCols());
-
-            CopyImageSizeFromInputs(); 
-        }
-
-        virtual void CopyImageSizeFromInputs() //this is element wise scaling, so based on child 1
-        {
-            CopyImageSizeFromInput(1);
-        }
-
-        virtual void AttachInputs(const ComputationNodePtr leftNode, const ComputationNodePtr rightNode) 
-        {
-            m_children.resize(2);
-            m_children[0] = leftNode;
-            m_children[1] = rightNode;
-        }
-
-        virtual void MoveMatricesToDevice(const DEVICEID_TYPE deviceId)
-        {
-            ComputationNode<ElemType>::MoveMatricesToDevice(deviceId);
-
-            if (deviceId != AUTOPLACEMATRIX)
-            {
-                if (m_innerproduct.GetDeviceId() != deviceId)
-                    m_innerproduct.TransferFromDeviceToDevice(m_innerproduct.GetDeviceId(), deviceId);
-                if (m_rightGradient.GetDeviceId() != deviceId)
-                    m_rightGradient.TransferFromDeviceToDevice(m_rightGradient.GetDeviceId(), deviceId);
-            }
-        }
-
-        virtual void CopyTo(const ComputationNodePtr nodeP, const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            ComputationNode<ElemType>::CopyTo(nodeP, newName, flags);
-            DiagTimesNode<ElemType>* node = (DiagTimesNode<ElemType>*) nodeP;
-
-            if (flags & CopyNodeFlags::copyNodeValue)
-            {
-                node->m_innerproduct = m_innerproduct;
-                node->m_rightGradient = m_rightGradient;
-            }
-        }
-
-        // copy constructor
-        DiagTimesNode(const DiagTimesNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags)
-            : ComputationNode<ElemType>(node->m_deviceId), m_innerproduct(node->m_deviceId), m_rightGradient(node->m_deviceId)
-        {
-            node->CopyTo(this, newName, flags);
-        }
-
-        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            const std::wstring& name = (newName == L"")?NodeName():newName;
-                
-            ComputationNodePtr node = new DiagTimesNode<ElemType>(this, name, flags);
-            return node;
-        }
-
-    private:
-        Matrix<ElemType> m_innerproduct;
-        Matrix<ElemType> m_rightGradient;
-    };
-
-    template class DiagTimesNode<float>; 
-    template class DiagTimesNode<double>;
-
-    //The first matrix should be a vector regpresting the diagonal of a square matrix in the DiagTimes operation
-    template<class ElemType>
-    class CosDistanceNode : public ComputationNode<ElemType>
-    {
-        UsingComputationNodeMembers;
-    public:
-        CosDistanceNode(const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"")  
-            : ComputationNode<ElemType>(deviceId), m_invNorm0(deviceId), m_invNorm1(deviceId), m_leftTerm(deviceId), m_rightTerm(deviceId), m_temp(deviceId)
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            m_deviceId = deviceId;
-            MoveMatricesToDevice(deviceId);
-            InitRecurrentNode();
-        }
-
-        CosDistanceNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"")
-            : ComputationNode<ElemType>(deviceId), m_invNorm0(deviceId), m_invNorm1(deviceId), m_leftTerm(deviceId), m_rightTerm(deviceId), m_temp(deviceId)
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            LoadFromFile(fstream, modelVersion, deviceId);
-        }
-
-        virtual const std::wstring OperationName() const {return TypeName();}
-        static const std::wstring TypeName() {return L"CosDistance";} 
-
-        virtual void ComputeInputPartial(const size_t inputIndex)
-        {
-            if (inputIndex > 1)
-                throw std::invalid_argument("CosDistance operation only takes two inputs.");
-
-            if (inputIndex == 0)  //left derivative
-            {
-                ComputeInputPartialLeft(m_invNorm0, m_invNorm1, FunctionValues(), m_temp, m_rightTerm, m_leftTerm, Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues(), GradientValues(), Inputs(inputIndex)->GradientValues());
-            }
-            else  //right derivative
-            {
-                ComputeInputPartialRight(m_invNorm0, m_invNorm1, FunctionValues(), m_temp, m_rightTerm, m_leftTerm, Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues(), GradientValues(), Inputs(inputIndex)->GradientValues());
-            }
-        }
-
-        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq) 
-        {
-            if (inputIndex > 1)
-                throw std::invalid_argument("CosDistance operation only takes two inputs.");
-
-            Matrix<ElemType> sliceInput0Value = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceInputGrad = Inputs(inputIndex)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputGrad = this->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            if (inputIndex == 0)  //left derivative
-            {
-                ComputeInputPartialLeft(m_invNorm0, m_invNorm1, sliceOutputValue, m_temp, m_rightTerm, m_leftTerm, sliceInput0Value, sliceInput1Value, sliceOutputGrad, sliceInputGrad);
-            }
-            else  //right derivative
-            {
-                ComputeInputPartialRight(m_invNorm0, m_invNorm1, sliceOutputValue, m_temp, m_rightTerm, m_leftTerm, sliceInput0Value, sliceInput1Value, sliceOutputGrad, sliceInputGrad);
-            }
-        }
-
-        static void WINAPI ComputeInputPartialLeft(const Matrix<ElemType>& invNorm0, const Matrix<ElemType>& invNorm1, const Matrix<ElemType>& functionValues, 
-            Matrix<ElemType>& temp, Matrix<ElemType>& rightTerm, Matrix<ElemType>& leftTerm, // the temporary variables
-            const Matrix<ElemType>& in0, const Matrix<ElemType>& in1, const Matrix<ElemType>& gradientValues,
-            Matrix<ElemType>& inputGradientValues)
-        {
-            ComputeInputPartialS(0, invNorm0, invNorm1, functionValues, temp, rightTerm, leftTerm, in0, in1, gradientValues, inputGradientValues);
-        }
-
-        static void WINAPI ComputeInputPartialRight(const Matrix<ElemType>& invNorm0, const Matrix<ElemType>& invNorm1, const Matrix<ElemType>& functionValues, 
-            Matrix<ElemType>& temp, Matrix<ElemType>& rightTerm, Matrix<ElemType>& leftTerm, // the temporary variables
-            const Matrix<ElemType>& in0, const Matrix<ElemType>& in1, const Matrix<ElemType>& gradientValues,
-            Matrix<ElemType>& inputGradientValues)  
-        {
-            ComputeInputPartialS(1, invNorm0, invNorm1, functionValues, temp, rightTerm, leftTerm, in0, in1, gradientValues, inputGradientValues);  
-        }
-
-        // functionValues, invNorm0, invNorm1 - output from the EvaluateNode() method
-        // temp, rightTerm, leftTerm - temporary matrices
-        // in0, in1 - input functionValues from other nodes
-        // inputGradientValues(x) - gradients to update, where x matches inputIndex
-        static void WINAPI ComputeInputPartialS(const size_t inputIndex, const Matrix<ElemType>& invNorm0, const Matrix<ElemType>& invNorm1, const Matrix<ElemType>& functionValues, 
-            Matrix<ElemType>& temp, Matrix<ElemType>& rightTerm, Matrix<ElemType>& leftTerm, // the temporary variables
-            const Matrix<ElemType>& in0, const Matrix<ElemType>& in1, const Matrix<ElemType>& gradientValues,
-            Matrix<ElemType>& inputGradientValues)  
-        {
-            if (inputIndex == 0)  //left derivative
-            {
-                temp.AssignElementProductOf(invNorm0, invNorm0);
-            }
-            else  //right derivative
-            {
-                temp.AssignElementProductOf(invNorm1, invNorm1);
-            }
-
-            temp.ElementMultiplyWith(functionValues);
-            rightTerm.SetValue(inputIndex?in1:in0);
-            rightTerm.RowElementMultiplyWith(temp);
-
-            temp.AssignElementProductOf(invNorm0, invNorm1);
-            leftTerm.SetValue(inputIndex?in0:in1);
-            leftTerm.RowElementMultiplyWith(temp);
-
-            leftTerm -= rightTerm;
-            leftTerm.RowElementMultiplyWith(gradientValues);
-            inputGradientValues += leftTerm;
-            
-            //alternatively the above three lines can be replaced by
-            //leftTerm.RowElementMultiplyWith(gradientValues);
-            //rightTerm.RowElementMultiplyWith(gradientValues);
-            //Matrix<ElemType>::AddScaledDifference(1, leftTerm, rightTerm, inputGradientValues);
-        }
-
-        virtual void EvaluateThisNode()  
-        {
-            EvaluateThisNodeS(m_invNorm0, m_invNorm1, FunctionValues(), Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues());  
-        }
-
-        virtual void EvaluateThisNode(const size_t timeIdxInSeq) 
-        {
-            Matrix<ElemType> sliceInput0Value = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            EvaluateThisNodeS(m_invNorm0, m_invNorm1, sliceOutputValue, sliceInput0Value, sliceInput1Value);  
-        }
-
-        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& invNorm0, Matrix<ElemType>& invNorm1, 
-            Matrix<ElemType>& functionValues, Matrix<ElemType>& in0, Matrix<ElemType>& in1)  
-        {
-            invNorm0.AssignVectorNorm2Of(in0, true); // seems to modify input (in0)
-            invNorm0.AssignElementInverseOf(invNorm0);
-
-            invNorm1.AssignVectorNorm2Of(in1, true); // seems to modify the input (in1)
-            invNorm1.AssignElementInverseOf(invNorm1);
-
-            functionValues.AssignInnerProductOf(in0, in1, true);
-            functionValues.ElementMultiplyWith(invNorm0);
-            functionValues.ElementMultiplyWith(invNorm1);
-        }
-
-        virtual void Validate()
-        {
-            PrintSelfBeforeValidation();
-
-            if (m_children.size() != 2) 
-                throw std::logic_error("CosDistance operation requires two inputs.");
-
-            //if dimention is missing make the two operatants to have same size
-            size_t index = 0;
-            if (Inputs(index)->OperationName() == LearnableParameter<ElemType>::TypeName())
-            {
-                size_t rows = Inputs(index)->FunctionValues().GetNumRows() == 0? Inputs(1-index)->FunctionValues().GetNumRows() : Inputs(index)->FunctionValues().GetNumRows();
-                size_t cols = Inputs(index)->FunctionValues().GetNumCols() == 0? Inputs(1-index)->FunctionValues().GetNumCols() : Inputs(index)->FunctionValues().GetNumCols();
-                Inputs(index)->FunctionValues().Resize(rows, cols);
-            }
-
-            index = 1;
-            if (Inputs(index)->OperationName() == LearnableParameter<ElemType>::TypeName())
-            {
-                size_t rows = Inputs(index)->FunctionValues().GetNumRows() == 0? Inputs(1-index)->FunctionValues().GetNumRows() : Inputs(index)->FunctionValues().GetNumRows();
-                size_t cols = Inputs(index)->FunctionValues().GetNumCols() == 0? Inputs(1-index)->FunctionValues().GetNumCols() : Inputs(index)->FunctionValues().GetNumCols();
-                Inputs(index)->FunctionValues().Resize(rows, cols);
-            }
-
-            if (Inputs(0)->FunctionValues().GetNumElements() == 0 || Inputs(1)->FunctionValues().GetNumElements() == 0)
-                throw std::logic_error("CosDistance operation: one of the operants has 0 element.");
-
-            if (Inputs(1)->FunctionValues().GetNumRows() != Inputs(0)->FunctionValues().GetNumRows() || 
-                Inputs(1)->FunctionValues().GetNumCols() != Inputs(0)->FunctionValues().GetNumCols())
-                throw std::logic_error("The Matrix dimension in the CosDistance operation does not match.");
-
-            FunctionValues().Resize(1, Inputs(1)->FunctionValues().GetNumCols());
-
-            CopyImageSizeFromInputs(); 
-        }
-
-        virtual void CopyImageSizeFromInputs() 
-        {
-            CopyImageSizeFromInput(0, false);
-
-            m_outputChannels = 1;
-            m_outputWidth = 1;
-            m_outputHeight = 1;        
-        }
-
-        virtual void AttachInputs(const ComputationNodePtr leftNode, const ComputationNodePtr rightNode) 
-        {
-            m_children.resize(2);
-            m_children[0] = leftNode;
-            m_children[1] = rightNode;
-        }
-
-        virtual void MoveMatricesToDevice(const DEVICEID_TYPE deviceId)
-        {
-            ComputationNode<ElemType>::MoveMatricesToDevice(deviceId);
-
-            if (deviceId != AUTOPLACEMATRIX)
-            {
-                if (m_invNorm0.GetDeviceId() != deviceId)
-                    m_invNorm0.TransferFromDeviceToDevice(m_invNorm0.GetDeviceId(), deviceId);
-                if (m_invNorm1.GetDeviceId() != deviceId)
-                    m_invNorm1.TransferFromDeviceToDevice(m_invNorm1.GetDeviceId(), deviceId);
-                if (m_leftTerm.GetDeviceId() != deviceId)
-                    m_leftTerm.TransferFromDeviceToDevice(m_leftTerm.GetDeviceId(), deviceId);
-                if (m_rightTerm.GetDeviceId() != deviceId)
-                    m_rightTerm.TransferFromDeviceToDevice(m_rightTerm.GetDeviceId(), deviceId);
-                if (m_temp.GetDeviceId() != deviceId)
-                    m_temp.TransferFromDeviceToDevice(m_temp.GetDeviceId(), deviceId);
-            }
-        }
-
-        virtual void CopyTo(const ComputationNodePtr nodeP, const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            ComputationNode<ElemType>::CopyTo(nodeP, newName, flags);
-            CosDistanceNode<ElemType>* node = (CosDistanceNode<ElemType>*) nodeP;
-
-            if (flags & CopyNodeFlags::copyNodeValue)
-            {
-                node->m_invNorm0 = m_invNorm0;
-                node->m_invNorm1 = m_invNorm1;
-                node->m_leftTerm = m_leftTerm;
-                node->m_rightTerm = m_rightTerm;
-                node->m_temp = m_temp;
-            }
-        }
-
-        // copy constructor
-        CosDistanceNode(const CosDistanceNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags)
-            : ComputationNode<ElemType>(node->m_deviceId), m_invNorm0(node->m_deviceId), m_invNorm1(node->m_deviceId), m_leftTerm(node->m_deviceId), m_rightTerm(node->m_deviceId), m_temp(node->m_deviceId)
-        {
-            node->CopyTo(this, newName, flags);
-        }
-
-        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            const std::wstring& name = (newName == L"")?NodeName():newName;
-                
-            ComputationNodePtr node = new CosDistanceNode<ElemType>(this, name, flags);
-            return node;
-        }
-
-    private:
-        // invNorm nodes tranfer data between EvaluateThisNode and ComputeInputPartial
-        Matrix<ElemType> m_invNorm0;
-        Matrix<ElemType> m_invNorm1;
-        // the rest are temporaries, values don't need to be maintained
-        Matrix<ElemType> m_leftTerm;
-        Matrix<ElemType> m_rightTerm;
-        Matrix<ElemType> m_temp;
-    };
-
-    template class CosDistanceNode<float>; 
-    template class CosDistanceNode<double>;
-
     template<class ElemType>
     class DropoutNode : public ComputationNode<ElemType>
     {
@@ -4321,13 +1015,12 @@ protected:  \
             Matrix<ElemType> sliceMask = Matrix<ElemType>();
             if(m_dropoutRate > 0)
             {
-				FunctionValues().Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(0)->FunctionValues().GetNumCols());
-				m_maskOfDropout.Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(0)->FunctionValues().GetNumCols());
+                FunctionValues().Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(0)->FunctionValues().GetNumCols());
+                m_maskOfDropout.Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(0)->FunctionValues().GetNumCols());
                 sliceMask = m_maskOfDropout.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-			}
-			
-			sliceOutputValue = FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-			
+            }
+
+            sliceOutputValue = FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
 
             EvaluateThisNodeS(m_dropoutRate, m_randomSeed, sliceOutputValue, sliceMask, sliceInput0Value);
         }
@@ -4453,987 +1146,6 @@ protected:  \
     template class DropoutNode<float>; 
     template class DropoutNode<double>;
 
-    template<class ElemType>
-    class KhatriRaoProductNode : public ComputationNode<ElemType>
-    {
-        UsingComputationNodeMembers;
-    public:
-        KhatriRaoProductNode(const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)  
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            m_deviceId = deviceId;
-            MoveMatricesToDevice(deviceId);
-            InitRecurrentNode();
-        }
-
-        KhatriRaoProductNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            LoadFromFile(fstream, modelVersion, deviceId);
-        }
-
-        // copy constructor
-        KhatriRaoProductNode(const KhatriRaoProductNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags) : ComputationNode<ElemType>(node->m_deviceId)
-        {
-            node->CopyTo(this, newName, flags);
-        }
-
-        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            const std::wstring& name = (newName == L"")?NodeName():newName;
-                
-            ComputationNodePtr node = new KhatriRaoProductNode<ElemType>(this, name, flags);
-            return node;
-        }
-
-        virtual const std::wstring OperationName() const {return TypeName();}
-        static const std::wstring TypeName() {return L"KhatriRaoProduct";} 
-
-        virtual void ComputeInputPartial(const size_t inputIndex)
-        {
-            if (inputIndex > 1)
-                throw std::invalid_argument("KhatriRaoProduct operation only takes two inputs.");
-
-            if (inputIndex == 0)  //left derivative
-            {
-                ComputeInputPartialLeft(Inputs(1)->FunctionValues(), Inputs(0)->GradientValues(), GradientValues()); 
-            }
-            else  //right derivative
-            {
-                ComputeInputPartialRight(Inputs(0)->FunctionValues(), Inputs(1)->GradientValues(), GradientValues()); 
-            }
-        }
-
-        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq) 
-        {
-            if (inputIndex > 1)
-                throw std::invalid_argument("KhatriRaoProduct operation only takes two inputs.");
-
-            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            if (inputIndex == 0)  //left derivative
-            {
-                Matrix<ElemType> sliceInput0Grad = Inputs(0)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-                Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-                ComputeInputPartialLeft(sliceInput1Value, sliceInput0Grad, sliceOutputGrad); 
-            }
-            else  //right derivative
-            {
-                Matrix<ElemType> sliceInput0Value = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-                Matrix<ElemType> sliceInput1Grad = Inputs(1)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-                ComputeInputPartialRight(sliceInput0Value, sliceInput1Grad, sliceOutputGrad); 
-            }
-        }
-
-        static void WINAPI ComputeInputPartialLeft(Matrix<ElemType>& childFunctionValues, Matrix<ElemType>& childGradientValues, const Matrix<ElemType>& gradientValues)
-        {
-            childGradientValues.AddColumnReshapeProductOf(gradientValues, childFunctionValues, false);
-        }
-
-        static void WINAPI ComputeInputPartialRight(Matrix<ElemType>& childFunctionValues, Matrix<ElemType>& childGradientValues, const Matrix<ElemType>& gradientValues)  
-        {
-            childGradientValues.AddColumnReshapeProductOf(gradientValues, childFunctionValues, true);
-        }
-
-        virtual void EvaluateThisNode()  
-        {
-            EvaluateThisNodeS(FunctionValues(), Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues());  
-        }
-
-        virtual void EvaluateThisNode(const size_t timeIdxInSeq)  
-        {
-            Matrix<ElemType> sliceInput0Value = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            EvaluateThisNodeS(sliceOutputValue, sliceInput0Value, sliceInput1Value); 
-        }
-
-        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, Matrix<ElemType>& in0, Matrix<ElemType>& in1)  
-        {
-            functionValues.AssignKhatriRaoProductOf(in0,in1);
-#if NANCHECK
-            functionValues.HasNan("KhatriRaoProduct");
-#endif
-        }
-
-        virtual void Validate()
-        {
-            PrintSelfBeforeValidation();
-
-            if (m_children.size() != 2) 
-                throw std::logic_error("KhatriRaoProduct operation requires two inputs.");
-
-            //support automatic dimention inference for learnable parameters
-            size_t rows0 = Inputs(0)->FunctionValues().GetNumRows(), cols0 = Inputs(0)->FunctionValues().GetNumCols();
-            size_t rows1 = Inputs(1)->FunctionValues().GetNumRows(), cols1 = Inputs(1)->FunctionValues().GetNumCols();
-
-            if (rows0 == 0 || rows1 == 0)
-                throw logic_error("KhatriRaoProduct operation: The number of rows in the input should not be 0.");
-
-            if (Inputs(0)->OperationName() == LearnableParameter<ElemType>::TypeName() && cols0 == 0 && cols1 != 0)
-                Inputs(0)->FunctionValues().Resize(rows0, cols1);
-
-            if (Inputs(1)->OperationName() == LearnableParameter<ElemType>::TypeName() && cols0 != 0 && cols1 == 0)
-                Inputs(1)->FunctionValues().Resize(rows1, cols0);
-
-            //cols may be changed before this line and so cannot use cached cols values below
-            if (Inputs(0)->FunctionValues().GetNumElements() == 0 || Inputs(1)->FunctionValues().GetNumElements() == 0)
-                throw std::logic_error("KhatriRaoProduct operation: One of the operants has 0 elements.");
-
-            if (Inputs(1)->FunctionValues().GetNumCols() != Inputs(0)->FunctionValues().GetNumCols())
-            {
-                throw std::logic_error("The Matrices should have same number of columns.");
-            }
-
-            FunctionValues().Resize(rows0 * rows1, Inputs(0)->FunctionValues().GetNumCols());
-            CopyImageSizeFromInputs(); 
-        }
-
-        virtual void CopyImageSizeFromInputs()  
-        {
-            //since it's symmetrical any one of the input may be the true input. 
-            //since we dont' use the input image size info in the operation, the input part doesn't matter.
-            CopyImageSizeFromInput(1, false); 
-
-            //after KhatriRaoProduct the structure is lost
-            m_outputWidth = 1;
-            m_outputHeight = m_functionValues.GetNumRows();
-            m_outputChannels =  1;
-        }
-
-        virtual void AttachInputs(const ComputationNodePtr leftNode, const ComputationNodePtr rightNode) 
-        {
-            m_children.resize(2);
-            m_children[0] = leftNode;
-            m_children[1] = rightNode;
-        }
-    };
-
-    template class KhatriRaoProductNode<float>; 
-    template class KhatriRaoProductNode<double>;
-
-    //originally designed to extract word embedding representation from bag-of-word. 
-    //takes two inputs, input0 is weight matrix and input1 is the bag-of-word representation of the inputs
-    template<class ElemType>
-    class LookupTableNode : public ComputationNode<ElemType>
-    {
-        UsingComputationNodeMembers;
-    public:
-        LookupTableNode(const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            m_deviceId = deviceId;
-            MoveMatricesToDevice(deviceId);
-            InitRecurrentNode();
-        }
-
-        LookupTableNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            LoadFromFile(fstream, modelVersion, deviceId);
-        }
-
-        virtual const std::wstring OperationName() const {return TypeName();}
-        static const std::wstring TypeName() {return L"LookupTable";} 
-
-        virtual void ComputeInputPartial(const size_t inputIndex)
-        {
-            if (inputIndex > 1)
-                throw std::invalid_argument("LookupTable operation only takes two inputs.");
-
-            if (inputIndex == 0)  //left derivative
-            {
-                ComputeInputPartialLeft(Inputs(1)->FunctionValues(), Inputs(0)->GradientValues(), GradientValues());
-            }
-            else  //right derivative
-        {
-                ComputeInputPartialRight(Inputs(0)->FunctionValues(), Inputs(1)->GradientValues(), GradientValues());
-            }
-        }
-
-        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
-        {
-            if (inputIndex > 1)
-                throw std::invalid_argument("LookupTable operation only takes two inputs.");
-
-            if (inputIndex == 0)  //left derivative
-        {
-                Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-                Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-                ComputeInputPartialLeft(sliceInput1Value, Inputs(0)->GradientValues(), sliceOutputGrad);
-            }
-            else  //right derivative
-            {
-                Matrix<ElemType> sliceInput1Grad = Inputs(1)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-                Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-                ComputeInputPartialRight(Inputs(0)->FunctionValues(), sliceInput1Grad, sliceOutputGrad);
-            }
-        }
-
-        static void WINAPI ComputeInputPartialLeft(Matrix<ElemType>& inputFunctionValues, Matrix<ElemType>& inputGradientValues, Matrix<ElemType>& gradientValues)  
-        {
-            size_t rows1 =inputFunctionValues.GetNumRows(), cols1 = inputFunctionValues.GetNumCols();
-            size_t rowsp = gradientValues.GetNumRows(), colsp = gradientValues.GetNumCols();
-            int wordsInEachSample = rows1 / inputGradientValues.GetNumCols();
-
-            inputFunctionValues.Reshape(rows1 / wordsInEachSample, cols1 * wordsInEachSample);
-            gradientValues.Reshape(rowsp / wordsInEachSample, colsp * wordsInEachSample);
-
-            Matrix<ElemType>::MultiplyAndAdd(gradientValues, false, inputFunctionValues, true, inputGradientValues);
-
-            inputFunctionValues.Reshape(rows1, cols1);
-            gradientValues.Reshape(rowsp, colsp);
-        }
-
-        static void WINAPI ComputeInputPartialRight(Matrix<ElemType>& inputFunctionValues, Matrix<ElemType>& inputGradientValues, Matrix<ElemType>& gradientValues)  
-            {
-            size_t rows1 =inputGradientValues.GetNumRows(), cols1 = inputGradientValues.GetNumCols();
-            size_t rowsp = gradientValues.GetNumRows(), colsp = gradientValues.GetNumCols();
-            int wordsInEachSample = rows1 / inputFunctionValues.GetNumCols();
-
-            inputGradientValues.Reshape(rows1 / wordsInEachSample, cols1 * wordsInEachSample);
-            gradientValues.Reshape(rowsp / wordsInEachSample, colsp * wordsInEachSample);
-
-            Matrix<ElemType>::MultiplyAndAdd(inputFunctionValues, true, gradientValues, false, inputGradientValues);
-
-            inputGradientValues.Reshape(rows1, cols1);
-            gradientValues.Reshape(rowsp, colsp);
-        }
-
-        virtual void EvaluateThisNode()
-        {
-            EvaluateThisNodeS(FunctionValues(), Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues());
-        }
-
-        virtual void EvaluateThisNode(const size_t timeIdxInSeq) 
-        {
-            Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            EvaluateThisNodeS(sliceOutputValue, Inputs(0)->FunctionValues(), sliceInput1Value);
-        }
-
-        //input0 is the weight (each column is an embedding of one word), input 1 contains m_bnrLooked words in each column (sample)
-        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, const Matrix<ElemType>& input0, Matrix<ElemType>& input1)  
-        {
-            size_t rows1 =input1.GetNumRows(), cols1 = input1.GetNumCols();
-            int wordsInEachSample = rows1 / input0.GetNumCols();
-
-            input1.Reshape(rows1 / wordsInEachSample, cols1 * wordsInEachSample);
-
-            functionValues.AssignProductOf(input0, false, input1, false);
-
-            input1.Reshape(rows1, cols1);
-            size_t rows = functionValues.GetNumRows();
-            functionValues.Reshape(rows * wordsInEachSample, cols1);
-        }
-            
-        virtual void Validate()
-        {
-            PrintSelfBeforeValidation();
-
-            if (Inputs(1)->FunctionValues().GetNumRows() % Inputs(0)->FunctionValues().GetNumCols() != 0)
-                throw invalid_argument("Mismatched dimention. rows in input1 must be multiples of cols in input0.");
-
-            int wordsInEachSample = Inputs(1)->FunctionValues().GetNumRows() / Inputs(0)->FunctionValues().GetNumCols();
-          
-            FunctionValues().Resize(Inputs(0)->FunctionValues().GetNumRows() * wordsInEachSample, Inputs(1)->FunctionValues().GetNumCols());
-
-            CopyImageSizeFromInputs(); 
-        }
-
-        virtual void AttachInputs(const ComputationNodePtr leftNode, const ComputationNodePtr rightNode) 
-        {
-            m_children.resize(2);
-            m_children[0] = leftNode;
-            m_children[1] = rightNode;
-        }
-
-        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            const std::wstring& name = (newName == L"")?NodeName():newName;
-            ComputationNodePtr node = new LookupTableNode<ElemType>(this, name, flags);
-            return node;
-        }
-
-        LookupTableNode(const LookupTableNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags) : ComputationNode<ElemType>(node->m_deviceId)
-        {
-            node->CopyTo(this, newName, flags);
-        }
-    };
-
-    template class LookupTableNode<float>;
-    template class LookupTableNode<double>;
-
-    template<class ElemType>
-    class DelayNode : public ComputationNode<ElemType>
-    {
-        ElemType  m_default_activity; 
-
-        UsingComputationNodeMembers;
-    public:
-        DelayNode(const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"")  
-            : ComputationNode<ElemType>(deviceId), m_pastActivity(deviceId)
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            m_deviceId = deviceId;
-            MoveMatricesToDevice(deviceId);
-            m_default_activity = (ElemType)DEFAULT_HIDDEN_ACTIVITY;
-            m_delay = 1;
-            m_functionValues.Resize(1,1);
-            m_pastActivity.Resize(1,1);
-            Reset();
-            InitRecurrentNode();
-        }
-                
-        DelayNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"")
-            : ComputationNode<ElemType>(deviceId), m_pastActivity(deviceId)
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-
-            m_default_activity = (ElemType)DEFAULT_HIDDEN_ACTIVITY;
-            m_delay = 1;
-            m_functionValues.Resize(1,1);
-            m_pastActivity.Resize(1,1);
-            Reset();
-
-            LoadFromFile(fstream, modelVersion, deviceId);
-        }
-
-        void SaveToFile(File& fstream) const
-        {
-            fstream << OperationName() << NodeName();
-            fstream << m_delay; 
-            fstream << FunctionValues().GetNumRows() << FunctionValues().GetNumCols(); 
-        }
-
-        void LoadFromFile(File& fstream, const size_t /*modelVersion*/, const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX)
-        {
-            m_deviceId = deviceId;
-            MoveMatricesToDevice(deviceId);
-            InitRecurrentNode();
-
-            fstream >> m_delay;
-
-            size_t iRow, timeIdxInSeq;
-            fstream >> iRow >> timeIdxInSeq;
-            FunctionValues().Resize(iRow,timeIdxInSeq);
-            m_pastActivity.Resize(iRow, timeIdxInSeq);
-        }
-
-        DelayNode(const DEVICEID_TYPE deviceId, ElemType initHiddenActivity, size_t row_size, size_t col_size, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)  
-        {
-            m_nodeName = (name == L""? CreateUniqNodeName() : name);
-            m_deviceId = deviceId;
-            MoveMatricesToDevice(deviceId);
-            m_default_activity = initHiddenActivity;
-            m_delay = 1;
-
-            m_functionValues.Resize(row_size, col_size);
-            m_functionValues.SetValue(m_default_activity);
-
-            m_pastActivity.Resize(row_size, col_size);
-            m_pastActivity.SetValue(m_default_activity);
-
-            m_gradientValues.Resize(row_size, col_size);
-            m_gradientValues.SetValue(0.0f);
-
-            Reset();
-            InitRecurrentNode();
-        }
-
-        virtual const std::wstring OperationName() const {return TypeName();}
-
-        virtual void ComputeInputPartial(const size_t inputIndex)
-        {
-            if (inputIndex > 0)
-                throw std::invalid_argument("Delay operation only takes one input.");
-
-            size_t nbrSamples = GradientValues().GetNumCols() / m_samplesInRecurrentStep; 
-            for (int i = nbrSamples - 1; i >= 0; i--)
-            {
-                ComputeInputPartialSR(i, m_delay, Inputs(0)->GradientValues(), GradientValues(), m_samplesInRecurrentStep);
-            }
-        }
-
-        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
-        {
-            if (inputIndex > 0)
-                throw std::invalid_argument("Delay operation only takes one input.");
-            assert(m_functionValues.GetNumRows() == GradientValues().GetNumRows()); // original used m_functionValues.GetNumRows() for loop dimension
-            if (m_samplesInRecurrentStep == 1)
-            {
-                ComputeInputPartialSR(timeIdxInSeq, m_delay, Inputs(0)->GradientValues(), GradientValues(), m_samplesInRecurrentStep);
-            }else
-            {
-                for (size_t i = 0 ; i < m_samplesInRecurrentStep; i++)
-                {
-                    bool reset = false;
-
-                    if ((((int)m_sentenceEnd[i] +(int)m_delay - 1) >= (int)timeIdxInSeq) && (m_sentenceEnd[i] <= timeIdxInSeq))
-                    {
-                        reset = true;
-                    }
-
-                    ComputeInputPartialSRP(timeIdxInSeq, m_delay, reset, Inputs(0)->GradientValues(), GradientValues(), i, m_samplesInRecurrentStep);
-                }
-            }
-        }
-
-        static void WINAPI ComputeInputPartialSR(int timeIdxInSeq, int delay,  
-            Matrix<ElemType>& inputGradientValues, const Matrix<ElemType>& gradientValues, const size_t mNbr)
-        {
-            assert(timeIdxInSeq >= 0);
-            if ((timeIdxInSeq - delay) >= 0 && (timeIdxInSeq - delay) * mNbr <= inputGradientValues.GetNumCols())
-            {
-                Matrix<ElemType> to = inputGradientValues.ColumnSlice((timeIdxInSeq - delay)*mNbr, mNbr);
-                Matrix<ElemType> frm= gradientValues.ColumnSlice(timeIdxInSeq * mNbr, mNbr);
-                to += frm; 
-            }
-        }
-
-        static void WINAPI ComputeInputPartialSRP(int timeIdxInSeq, int delay,  bool reset,
-            Matrix<ElemType>& inputGradientValues, const Matrix<ElemType>& gradientValues, const size_t indexInBatch, const size_t mNbr)
-        {
-            assert(timeIdxInSeq >= 0);
-            if ((timeIdxInSeq - delay) >= 0 && (timeIdxInSeq - delay) * mNbr <= inputGradientValues.GetNumCols() && !reset)
-            {
-                Matrix<ElemType> to = inputGradientValues.ColumnSlice((timeIdxInSeq - delay)*mNbr + indexInBatch, 1);
-                Matrix<ElemType> frm= gradientValues.ColumnSlice(timeIdxInSeq * mNbr + indexInBatch, 1);
-                to += frm; 
-            }
-        }
-
-
-        virtual void EvaluateThisNode()  
-        {
-            ASSERT(m_delay > 0);
-            size_t blogSize = Inputs(0)->FunctionValues().GetNumCols();
-
-            for (size_t i = 0; i < blogSize / m_samplesInRecurrentStep; i++)
-                EvaluateThisNodeSR(i, m_delay, m_Reset, m_default_activity, m_functionValues, m_pastActivity, Inputs(0)->FunctionValues(), m_samplesInRecurrentStep);
-            /// reset past activity
-            m_pastActivity = Inputs(0)->FunctionValues();
-        }
-
-        void Reset()
-        {
-            m_Reset = true;
-        }
-
-
-        void NotReset()
-        {
-            m_Reset = false;
-        }
-
-        virtual void EvaluateThisNode(const size_t timeIdxInSeq)  
-        {
-            /// reset past activity as it reached to the begining of a minibatch
-            /// the node pointed hasn't yet updated, so it is the past activity 
-            if (timeIdxInSeq == 0)
-                m_pastActivity = Inputs(0)->FunctionValues();
-            
-            if (m_samplesInRecurrentStep == 1)
-            {
-                //bool reset = (m_sentenceEnd[0] == timeIdxInSeq);
-                bool reset = false;
-
-                if ((((int)m_sentenceEnd[0] +(int)m_delay - 1) >= (int)timeIdxInSeq) && (m_sentenceEnd[0] <= timeIdxInSeq))
-                {
-                    reset = true;
-                }
-                EvaluateThisNodeSR(timeIdxInSeq, m_delay, reset, m_default_activity, m_functionValues, m_pastActivity, Inputs(0)->FunctionValues(), m_samplesInRecurrentStep);
-            } else
-            {
-                for (size_t i = 0 ; i < m_samplesInRecurrentStep; i++)
-                {
-                    // bool reset = (m_sentenceEnd[i] == timeIdxInSeq);
-                    bool reset = false;
-
-                    if ((((int)m_sentenceEnd[i] +(int)m_delay - 1) >= (int)timeIdxInSeq) && (m_sentenceEnd[i] <= timeIdxInSeq))
-                    {
-                        reset = true;
-                    }
-                    EvaluateThisNodeSRP(timeIdxInSeq, m_delay, reset, m_default_activity, m_functionValues, m_pastActivity, Inputs(0)->FunctionValues(), i, m_samplesInRecurrentStep);
-                }
-            }
-
-        }
-
-        static void WINAPI EvaluateThisNodeSR(const size_t timeIdxInSeq, const int delay, const bool reset, const ElemType default_activity, Matrix<ElemType>& functionValues, const Matrix<ElemType>& pastActivity, const Matrix<ElemType>& inputFunctionValues, const size_t mNbr)
-        {
-            ASSERT(delay > 0);
-
-            if (functionValues.GetNumRows() != inputFunctionValues.GetNumRows() ||
-                functionValues.GetNumCols() != inputFunctionValues.GetNumCols())
-                functionValues.Resize(inputFunctionValues.GetNumRows(),
-                    inputFunctionValues.GetNumCols());
-
-            int iPastIndex = (int) (timeIdxInSeq - delay) * mNbr;
-            int d = iPastIndex; 
-            if (d < 0)
-                d = (int)functionValues.Mod((float)iPastIndex, (float)pastActivity.GetNumCols());  
-           /// this can point to the past activity of the previous mninibatch
-
-            Matrix<ElemType> out = functionValues.ColumnSlice(timeIdxInSeq * mNbr, mNbr);
-            Matrix<ElemType> inp((DEVICEID_TYPE)functionValues.GetDeviceId()) ;
-
-            if (reset)
-                out.SetValue(default_activity);
-            else
-            {
-                if (iPastIndex < 0)
-                    inp = pastActivity.ColumnSlice(d, mNbr);
-                else
-                    inp = inputFunctionValues.ColumnSlice(d, mNbr);
-                out.SetValue(inp);
-            }
-        }
-
-        static void WINAPI EvaluateThisNodeSRP(const size_t timeIdxInSeq, const int delay, const bool reset, const ElemType default_activity, Matrix<ElemType>& functionValues, const Matrix<ElemType>& pastActivity, const Matrix<ElemType>& inputFunctionValues, const size_t indexInBatch, const size_t mNbr)
-        {
-            ASSERT(delay > 0);
-
-            if (functionValues.GetNumRows() != inputFunctionValues.GetNumRows() ||
-                functionValues.GetNumCols() != inputFunctionValues.GetNumCols())
-                functionValues.Resize(inputFunctionValues.GetNumRows(),
-                    inputFunctionValues.GetNumCols());
-
-            int iPastIndex = (int) (timeIdxInSeq - delay) * mNbr;
-            int d = iPastIndex; 
-            if (d < 0)
-                d = (int)functionValues.Mod((float)iPastIndex, (float)pastActivity.GetNumCols());  
-            /// this can point to the past activity of the previous mninibatch
-
-            Matrix<ElemType> out = functionValues.ColumnSlice(timeIdxInSeq * mNbr+indexInBatch, 1);
-            Matrix<ElemType> inp((DEVICEID_TYPE)functionValues.GetDeviceId()) ;
-
-            if (reset)
-                out.SetValue(default_activity);
-            else
-            {
-                if (iPastIndex < 0)
-                    inp = pastActivity.ColumnSlice(d+indexInBatch, 1);
-                else
-                    inp = inputFunctionValues.ColumnSlice(d+indexInBatch, 1);
-                out.SetValue(inp);
-            }
-        }
-
-
-
-        virtual const Matrix<ElemType>& FunctionValues() const 
-        {
-            return m_functionValues;
-        }
-
-        virtual Matrix<ElemType>& FunctionValues() 
-        {
-            return m_functionValues;
-        }
-
-        virtual void Validate()
-        {
-            PrintSelfBeforeValidation(true/*allowNulls*/);
-
-            if (m_children.size() != 1) 
-                throw std::logic_error("Delay operation should have one input.");
-
-            if (!(Inputs(0) == nullptr))
-            {
-                size_t rows0 = Inputs(0)->FunctionValues().GetNumRows(), cols0 = Inputs(0)->FunctionValues().GetNumCols();
-
-                if (rows0 > 0 && cols0 > 0) FunctionValues().Resize(rows0, cols0);
-            }
-            CopyImageSizeFromInputs(); 
-        }
-
-        virtual void AttachInputs(const ComputationNodePtr inputNode) 
-        {
-            m_children.resize(1);
-            m_children[0] = inputNode;
-        }
-
-        void SetDelay(const int val)
-        {
-            if (val <= 0)
-                throw std::logic_error("Delay must be > 0.");
-            m_delay = val;
-        }
-
-        virtual void MoveMatricesToDevice(const DEVICEID_TYPE deviceId)
-        {
-            ComputationNode<ElemType>::MoveMatricesToDevice(deviceId);
-
-            if (deviceId != AUTOPLACEMATRIX)
-            {
-                if (m_functionValues.GetDeviceId() != deviceId)
-                    m_functionValues.TransferFromDeviceToDevice(m_functionValues.GetDeviceId(), deviceId);
-                if (m_pastActivity.GetDeviceId() != deviceId)
-                    m_pastActivity.TransferFromDeviceToDevice(m_pastActivity.GetDeviceId(), deviceId, true);
-            }
-        }
-
-        static const std::wstring TypeName() {return L"Delay";} 
-
-        virtual void CopyTo(const ComputationNodePtr nodeP, const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            ComputationNode<ElemType>::CopyTo(nodeP, newName, flags);
-            DelayNode<ElemType>* node = (DelayNode<ElemType>*) nodeP;
-
-            if (flags & CopyNodeFlags::copyNodeValue)
-            {
-                node->m_delay = m_delay;
-                node->m_Reset = m_Reset;
-                node->m_default_activity = m_default_activity;
-                node->m_pastActivity = m_pastActivity;
-            }
-        }
-
-        // copy constructor
-        DelayNode(const DelayNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags)
-            : ComputationNode<ElemType>(node->m_deviceId), m_pastActivity(node->m_deviceId)
-        {
-            node->CopyTo(this, newName, flags);
-        }
-
-        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            const std::wstring& name = (newName == L"")?NodeName():newName;
-                
-            ComputationNodePtr node = new DelayNode<ElemType>(this, name, flags);
-            return node;
-        }
-
-    private:
-        Matrix<ElemType> m_pastActivity;  /// saves the past activity this delay node points to
-        int      m_delay;    /// steps for delay 
-        bool     m_Reset; 
-
-    };
-
-    template class DelayNode<float>; 
-    template class DelayNode<double>;
-
-    template<class ElemType>
-    class CosDistanceWithNegativeSamplesNode : public ComputationNode<ElemType>
-    {
-        //typedef ComputationNode<ElemType>* ComputationNodePtr;
-        UsingComputationNodeMembers;
-
-    public:
-        CosDistanceWithNegativeSamplesNode(const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX, const std::wstring name = L"")
-            : ComputationNode<ElemType>(deviceId), m_invNorm0(deviceId), m_invNorm1(deviceId), m_invNormSquare(deviceId), 
-            m_leftTerm(deviceId), m_rightTerm(deviceId), m_temp(deviceId)
-        {
-            m_nodeName = (name == L"" ? CreateUniqNodeName() : name);
-            m_deviceId = deviceId;
-            MoveMatricesToDevice(deviceId);
-            InitRecurrentNode();
-        }
-
-        CosDistanceWithNegativeSamplesNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX, const std::wstring name = L"")
-            : ComputationNode<ElemType>(deviceId), m_invNorm0(deviceId), m_invNorm1(deviceId), m_invNormSquare(deviceId), 
-            m_leftTerm(deviceId), m_rightTerm(deviceId), m_temp(deviceId)
-        {
-            m_nodeName = (name == L"" ? CreateUniqNodeName() : name);
-            LoadFromFile(fstream, modelVersion, deviceId);
-        }
-
-        virtual const std::wstring OperationName() const { return TypeName(); }
-        static const std::wstring TypeName() { return L"CosDistanceWithNegativeSamples"; }
-
-        virtual void ComputeInputPartial(const size_t inputIndex)
-        {
-            if (inputIndex > 1)
-                throw std::invalid_argument("CosDistanceWithNegativeSamples operation only takes grdients on the first two inputs.");
-
-            ComputeInputPartialS(inputIndex, m_invNorm0, m_invNorm1, FunctionValues(), m_temp, m_rightTerm, m_leftTerm, m_invNormSquare, Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues(), Inputs(2)->FunctionValues(), Inputs(3)->FunctionValues(), Inputs(inputIndex)->GradientValues(), GradientValues());
-        }
-
-        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
-        {
-            if (inputIndex > 1)
-                throw std::invalid_argument("CosDistanceWithNegativeSamples operation only takes grdients on the first two inputs.");
-
-            Matrix<ElemType> sliceInput0Value = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceInputGrad = Inputs(inputIndex)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceThisGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            ComputeInputPartialS(inputIndex, m_invNorm0, m_invNorm1, sliceOutputValue, m_temp, m_rightTerm, m_leftTerm, m_invNormSquare, sliceInput0Value, sliceInput1Value, Inputs(2)->FunctionValues(), Inputs(3)->FunctionValues(), sliceInputGrad, sliceThisGrad);
-        }
-
-        // functionValues, invNorm0, invNorm1 - output from the EvaluateNode() method
-        // temp, rightTerm, leftTerm - temporary matrices
-        // in0, in1, in2, in3 - input functionValues from other nodes
-        // inputGradientValues(x) - gradients to update, where x matches inputIndex
-        static void WINAPI ComputeInputPartialS(const size_t inputIndex, const Matrix<ElemType>& invNorm0, const Matrix<ElemType>& invNorm1, const Matrix<ElemType>& functionValues,
-            Matrix<ElemType>& temp, Matrix<ElemType>& rightTerm, Matrix<ElemType>& leftTerm, Matrix<ElemType>& invNormSquare, // the temporary variables
-            const Matrix<ElemType>& in0, const Matrix<ElemType>& in1, const Matrix<ElemType>& in2, const Matrix<ElemType>& in3,
-            Matrix<ElemType>& inputGradientValues, Matrix<ElemType>& thisGradientValues)
-        {
-            size_t shift = (size_t)in2.Get00Element();
-            size_t negNumber = (size_t)in3.Get00Element();
-            size_t numCols = in0.GetNumCols(); // used in computing right child's graident
-
-            if (inputIndex == 0) // left derivative
-            {
-                invNormSquare.AssignElementProductOf(invNorm0, invNorm0);
-
-                for (long m = 0; m < negNumber + 1; m++)
-                {
-                    temp.GetARowByIndex(functionValues, m); // set this matrx to be the m-th row in functionValues
-                    temp.ElementMultiplyWith(invNormSquare);
-
-                    Matrix<ElemType>::ConductRowElementMultiplyWithShift(temp, in0, rightTerm, 0, true);
-
-                    if (m == 0)
-                    {
-                        temp.AssignElementProductOf(invNorm0, invNorm1);
-
-                        Matrix<ElemType>::ConductRowElementMultiplyWithShift(temp, in1, leftTerm, 0, true);
-                    }
-                    else
-                    {
-                        size_t currshift = m + shift - 1;  // for current line, how much should we shift
-
-                        temp.AssignElementProductOfWithShift(invNorm0, invNorm1, currshift); // this is a row vector
-
-                        Matrix<ElemType>::ConductRowElementMultiplyWithShift(temp, in1, leftTerm, currshift, true);
-                    }
-
-                    leftTerm = leftTerm - rightTerm;
-
-                    temp.GetARowByIndex(thisGradientValues, m);
-
-                    Matrix<ElemType>::ConductRowElementMultiplyWithShift(temp, leftTerm, rightTerm, 0, true);
-
-                    inputGradientValues += rightTerm;
-                }
-            }
-            else // right part
-            {
-                invNormSquare.AssignElementProductOf(invNorm1, invNorm1);  //this matrix should be save and unchanged. It should not be changed
-
-                for (long m = 0; m < negNumber + 1; m++)
-                {
-                    temp.GetARowByIndex(functionValues, m); // set this matrx to be the m-th row in functionValues
-
-                    if (m == 0) // this is the first line. computation should be symmetric
-                    {
-                        // the following is for the right part
-                        temp.ElementMultiplyWith(invNormSquare);
-
-                        Matrix<ElemType>::ConductRowElementMultiplyWithShift(temp, in1, rightTerm, 0, true);
-
-                        // the following is for the left part
-                        temp.AssignElementProductOf(invNorm0, invNorm1);
-
-                        Matrix<ElemType>::ConductRowElementMultiplyWithShift(temp, in0, leftTerm, 0, true);
-
-                        leftTerm = leftTerm - rightTerm;
-
-                        temp.GetARowByIndex(thisGradientValues, m);
-
-                        Matrix<ElemType>::ConductRowElementMultiplyWithShift(temp, leftTerm, rightTerm, 0, true);
-
-                        inputGradientValues += rightTerm;
-                    }
-                    else // this requires shift
-                    {
-                        size_t currshift = (m + shift - 1) % numCols;
-                        size_t reverseshift = numCols - currshift;
-
-                        leftTerm.AssignElementProductOfWithShift(invNormSquare, temp, reverseshift);  //use leftTerm as a temp variable here
-
-                        Matrix<ElemType>::ConductRowElementMultiplyWithShift(leftTerm, in1, rightTerm, 0, true);
-
-                        temp.AssignElementProductOfWithShift(invNorm1, invNorm0, reverseshift);
-
-                        Matrix<ElemType>::ConductRowElementMultiplyWithShift(temp, in0, leftTerm, reverseshift, true);
-
-                        leftTerm = leftTerm - rightTerm;
-
-                        temp.GetARowByIndex(thisGradientValues, m);
-
-                        Matrix<ElemType>::ConductRowElementMultiplyWithShift(temp, leftTerm, rightTerm, reverseshift, false);
-
-                        inputGradientValues += rightTerm;
-                    }
-                }
-            }
-        }
-
-        virtual void EvaluateThisNode()
-        {
-            EvaluateThisNodeS(m_invNorm0, m_invNorm1, FunctionValues(), Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues(), Inputs(2)->FunctionValues(), Inputs(3)->FunctionValues(), m_leftTerm, m_rightTerm);
-        }
-
-        virtual void EvaluateThisNode(const size_t timeIdxInSeq)
-        {
-            Matrix<ElemType> sliceInput0Value = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
-
-            EvaluateThisNodeS(m_invNorm0, m_invNorm1, sliceOutputValue, sliceInput0Value, sliceInput1Value, Inputs(2)->FunctionValues(), Inputs(3)->FunctionValues(), m_leftTerm, m_rightTerm);
-        }
-
-        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& invNorm0, Matrix<ElemType>& invNorm1,
-            Matrix<ElemType>& functionValues, Matrix<ElemType>& in0, Matrix<ElemType>& in1, Matrix<ElemType>& in2, Matrix<ElemType>& in3, Matrix<ElemType>& leftTermTemp, Matrix<ElemType>& rightTermTemp)
-        {
-            invNorm0.AssignVectorNorm2Of(in0, true); // seems to modify input (in0)
-            invNorm0.AssignElementInverseOf(invNorm0);
-
-            invNorm1.AssignVectorNorm2Of(in1, true); // seems to modify the input (in1)
-            invNorm1.AssignElementInverseOf(invNorm1);
-
-            size_t shift = (size_t)in2.Get00Element();
-            size_t negNumber = (size_t)in3.Get00Element();
-
-            // mutiply invNorm0 and invNorm1 with shift and neg. 
-            // The result is a matrix of (numberneg+1, invNorm0.Cols)
-            leftTermTemp.AssignElementProductOfWithShiftNeg(invNorm0, invNorm1, shift, negNumber);
-
-            // compute the right values
-            // Again, the ouput is a matrix of (negNumber+1, invNorm0.cols)
-            rightTermTemp.AssignInnerProductOfWithShiftNeg(in0, in1, true, shift, negNumber);
-
-            // compute the evaluation result matrix by multiply these two matrices, element by element
-            // we get a (negNumber+1, n) matrix
-            functionValues.AssignElementProductOf(leftTermTemp, rightTermTemp);
-        }
-
-        virtual void Validate()
-        {
-            PrintSelfBeforeValidation();
-
-            if (m_children.size() != 4)
-                throw std::logic_error("CosDistanceWithNegativeSamples operation requires 4 inputs.");
-
-            //if dimention is missing make the two operatants to have same size
-            size_t index = 0;
-            if (Inputs(index)->OperationName() == LearnableParameter<ElemType>::TypeName())
-            {
-                size_t rows = Inputs(index)->FunctionValues().GetNumRows() == 0 ? Inputs(1 - index)->FunctionValues().GetNumRows() : Inputs(index)->FunctionValues().GetNumRows();
-                size_t cols = Inputs(index)->FunctionValues().GetNumCols() == 0 ? Inputs(1 - index)->FunctionValues().GetNumCols() : Inputs(index)->FunctionValues().GetNumCols();
-                Inputs(index)->FunctionValues().Resize(rows, cols);
-            }
-
-            index = 1;
-            if (Inputs(index)->OperationName() == LearnableParameter<ElemType>::TypeName())
-            {
-                size_t rows = Inputs(index)->FunctionValues().GetNumRows() == 0 ? Inputs(1 - index)->FunctionValues().GetNumRows() : Inputs(index)->FunctionValues().GetNumRows();
-                size_t cols = Inputs(index)->FunctionValues().GetNumCols() == 0 ? Inputs(1 - index)->FunctionValues().GetNumCols() : Inputs(index)->FunctionValues().GetNumCols();
-                Inputs(index)->FunctionValues().Resize(rows, cols);
-            }
-
-            if (Inputs(0)->FunctionValues().GetNumElements() == 0 || Inputs(1)->FunctionValues().GetNumElements() == 0)
-                throw std::logic_error("CosDistanceWithNegativeSamples operation: one of the operants has 0 element.");
-
-            if (Inputs(1)->FunctionValues().GetNumRows() != Inputs(0)->FunctionValues().GetNumRows() ||
-                Inputs(1)->FunctionValues().GetNumCols() != Inputs(0)->FunctionValues().GetNumCols())
-                throw std::logic_error("The Matrix dimension in the CosDistanceWithNegativeSamples operation does not match.");
-
-            // input(2) is shift, input(3) is the #neg
-            size_t negNumber = (size_t)Inputs(3)->FunctionValues()(0, 0);
-
-            FunctionValues().Resize(negNumber + 1, Inputs(1)->FunctionValues().GetNumCols());
-
-            CopyImageSizeFromInputs();
-        }
-
-        virtual void CopyImageSizeFromInputs()
-        {
-            CopyImageSizeFromInput(0, false);
-
-            m_outputChannels = 1;
-            m_outputWidth = 1;
-            m_outputHeight = 1;
-        }
-
-        virtual void AttachInputs(const ComputationNodePtr leftNode, const ComputationNodePtr rightNode, const ComputationNodePtr shiftNode, const ComputationNodePtr negNode)
-        {
-            m_children.resize(4);
-            m_children[0] = leftNode;
-            m_children[1] = rightNode;
-            m_children[2] = shiftNode;
-            m_children[3] = negNode;
-        }
-
-        virtual void MoveMatricesToDevice(const short deviceId)
-        {
-            ComputationNode<ElemType>::MoveMatricesToDevice(deviceId);
-
-            if (deviceId != AUTOPLACEMATRIX)
-            {
-                if (m_invNorm0.GetDeviceId() != deviceId)
-                    m_invNorm0.TransferFromDeviceToDevice(m_invNorm0.GetDeviceId(), deviceId);
-                if (m_invNorm1.GetDeviceId() != deviceId)
-                    m_invNorm1.TransferFromDeviceToDevice(m_invNorm1.GetDeviceId(), deviceId);
-                if (m_invNormSquare.GetDeviceId() != deviceId)
-                    m_invNormSquare.TransferFromDeviceToDevice(m_invNormSquare.GetDeviceId(), deviceId);
-                if (m_leftTerm.GetDeviceId() != deviceId)
-                    m_leftTerm.TransferFromDeviceToDevice(m_leftTerm.GetDeviceId(), deviceId);
-                if (m_rightTerm.GetDeviceId() != deviceId)
-                    m_rightTerm.TransferFromDeviceToDevice(m_rightTerm.GetDeviceId(), deviceId);
-                if (m_temp.GetDeviceId() != deviceId)
-                    m_temp.TransferFromDeviceToDevice(m_temp.GetDeviceId(), deviceId);
-            }
-        }
-
-        virtual void CopyTo(const ComputationNodePtr nodeP, const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            ComputationNode<ElemType>::CopyTo(nodeP, newName, flags);
-            CosDistanceWithNegativeSamplesNode<ElemType>* node = (CosDistanceWithNegativeSamplesNode<ElemType>*) nodeP;
-
-            if (flags & CopyNodeFlags::copyNodeValue)
-            {
-                node->m_invNorm0 = m_invNorm0;
-                node->m_invNorm1 = m_invNorm1;
-                node->m_invNormSquare = m_invNormSquare;
-                node->m_leftTerm = m_leftTerm;
-                node->m_rightTerm = m_rightTerm;
-                node->m_temp = m_temp;
-            }
-        }
-
-        // copy constructor
-        CosDistanceWithNegativeSamplesNode(const CosDistanceWithNegativeSamplesNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags)
-            : ComputationNode<ElemType>(node->m_deviceId), m_invNorm0(node->m_deviceId), m_invNorm1(node->m_deviceId), m_leftTerm(node->m_deviceId), m_rightTerm(node->m_deviceId), m_temp(node->m_deviceId)
-        {
-            node->CopyTo(this, newName, flags);
-        }
-
-        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
-        {
-            const std::wstring& name = (newName == L"") ? NodeName() : newName;
-
-            ComputationNodePtr node = new CosDistanceWithNegativeSamplesNode<ElemType>(this, name, flags);
-            return node;
-        }
-
-    private:
-        // invNorm nodes tranfer data between EvaluateThisNode and ComputeInputPartial
-        Matrix<ElemType> m_invNorm0;
-        Matrix<ElemType> m_invNorm1;
-        // the rest are temporaries, values don't need to be maintained
-        Matrix<ElemType> m_leftTerm;
-        Matrix<ElemType> m_rightTerm;
-        Matrix<ElemType> m_invNormSquare;
-        Matrix<ElemType> m_temp;
-    };
-
-	template class CosDistanceWithNegativeSamplesNode<float>;
-	template class CosDistanceWithNegativeSamplesNode<double>;
-
 #pragma endregion derived operations
 
 }}}
diff --git a/MachineLearning/CNTK/ConvolutionalNodes.h b/MachineLearning/CNTK/ConvolutionalNodes.h
new file mode 100644
index 000000000..22cf6abec
--- /dev/null
+++ b/MachineLearning/CNTK/ConvolutionalNodes.h
@@ -0,0 +1,945 @@
+//
+// <copyright file="ConvolutionalNodes.h" company="Microsoft">
+//     Copyright (c) Microsoft Corporation.  All rights reserved.
+// </copyright>
+//
+#pragma once
+
+#include <unordered_set>
+#include <map>
+#include <string>
+#include <vector>
+#include <stdexcept>
+#include <list>
+#include <memory>
+#include <algorithm>
+#include <assert.h>
+#include <atomic>
+#include <sstream>
+#include <iostream>
+
+#include "Basics.h"
+#include "Matrix.h"
+#include "ComputationNode.h"
+
+namespace Microsoft { namespace MSR { namespace CNTK {
+
+    // convolution parameters structure, to make it easier to pass these around all these parameters
+    struct ConvolutionParams
+    {
+        size_t inputWidth, inputHeight, inputChannels;
+        size_t kernelWidth, kernelHeight;
+        size_t horizontalSubsample, verticalSubsample;
+        size_t outputWidth, outputHeight, outputChannels;
+        size_t maxTempMemSizeInSamples;
+        bool zeroPadding;
+    };
+
+    //convolutional network 
+    //follow "high performance convolutional neural networks for document processing" by Kumar chellapilla, Sidde Puri, and Patrice Simard
+    //assume each column is an input sample. Each sample is stored in [channel, row, col]  (r00, g00, b00, r01, g01, b01, r10, g10, b10, r11, g11, b11)
+    template<class ElemType>
+    class ConvolutionNode : public ComputationNode<ElemType>
+    {
+        UsingComputationNodeMembers;
+    public:
+        ConvolutionNode(const size_t kernelWidth, const size_t kernelHeight, const size_t outputChannels, 
+                        const size_t horizontalSubsample, const size_t verticalSubsample, 
+                        const bool zeroPadding = false, 
+                        const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"",
+                        const size_t maxTempMemSizeInSamples = 0)
+                        : ComputationNode<ElemType>(deviceId), m_tempMatrix(deviceId),
+                          m_kernelWidth(kernelWidth), m_kernelHeight(kernelHeight), 
+                          m_horizontalSubsample(horizontalSubsample), m_verticalSubsample(verticalSubsample),
+                          m_zeroPadding(zeroPadding), m_maxTempMemSizeInSamples(maxTempMemSizeInSamples)
+        {
+            m_outputChannels = outputChannels;
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            m_deviceId = deviceId;
+            MoveMatricesToDevice(deviceId);
+            InitRecurrentNode();
+        }
+
+        ConvolutionNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") 
+            : ComputationNode<ElemType>(deviceId), m_tempMatrix(deviceId)
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            LoadFromFile(fstream, modelVersion, deviceId);
+        }
+                
+        virtual void SaveToFile(File& fstream) const
+        {
+            ComputationNode<ElemType>::SaveToFile(fstream);
+
+            fstream <<  m_kernelWidth << m_kernelHeight << m_horizontalSubsample << m_verticalSubsample; 
+            fstream << m_outputChannels << m_zeroPadding << m_maxTempMemSizeInSamples; 
+        }
+
+        virtual void LoadFromFile(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX)
+        {
+            ComputationNode<ElemType>::LoadFromFile(fstream, modelVersion, deviceId);
+
+            fstream >>  m_kernelWidth >> m_kernelHeight >> m_horizontalSubsample >> m_verticalSubsample; 
+            fstream >> m_outputChannels >> m_zeroPadding >> m_maxTempMemSizeInSamples; 
+        }
+
+        virtual void CopyTo(const ComputationNodePtr nodeP, const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            ComputationNode<ElemType>::CopyTo(nodeP, newName, flags);
+            ConvolutionNode<ElemType>* node = (ConvolutionNode<ElemType>*) nodeP;
+
+            if (flags & CopyNodeFlags::copyNodeValue)
+            {
+                node->m_kernelWidth = m_kernelWidth;
+                node->m_kernelHeight = m_kernelHeight;
+
+                node->m_horizontalSubsample = m_horizontalSubsample;
+                node->m_verticalSubsample = m_verticalSubsample;
+
+                node->m_zeroPadding = m_zeroPadding;
+
+                node->m_maxTempMemSizeInSamples = m_maxTempMemSizeInSamples;
+
+                node->m_tempMatrix = m_tempMatrix;
+            }
+        }
+
+        // copy constructor
+        ConvolutionNode(const ConvolutionNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags) 
+            : ComputationNode<ElemType>(node->m_deviceId), m_tempMatrix(node->m_deviceId)
+        {
+            node->CopyTo(this, newName, flags);
+        }
+
+        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            const std::wstring& name = (newName == L"")?NodeName():newName;
+                
+            ComputationNodePtr node = new ConvolutionNode<ElemType>(this, name, flags);
+            return node;
+        }
+
+        virtual const std::wstring OperationName() const {return TypeName();}
+        static const std::wstring TypeName() {return L"Convolution";} 
+
+        ConvolutionParams GetConvolutionParams() const
+        {
+            ConvolutionParams convParam;
+            convParam.inputWidth = m_inputWidth;
+            convParam.inputHeight = m_inputHeight;
+            convParam.inputChannels = m_inputChannels;
+
+            convParam.kernelWidth = m_kernelWidth;
+            convParam.kernelHeight = m_kernelHeight;
+
+            convParam.horizontalSubsample = m_horizontalSubsample;
+            convParam.verticalSubsample = m_verticalSubsample;
+
+            convParam.outputWidth = m_outputWidth;
+            convParam.outputHeight = m_outputHeight;
+            convParam.outputChannels = m_outputChannels;
+
+            convParam.zeroPadding = m_zeroPadding;
+
+            convParam.maxTempMemSizeInSamples = m_maxTempMemSizeInSamples;
+            return convParam;
+        }
+
+        virtual void ComputeInputPartial(const size_t inputIndex) 
+        {
+            if (inputIndex > 1)
+                throw std::invalid_argument("Convolution operation only takes two inputs.");
+
+            if (inputIndex == 0)  //derivative with regard to the weight matrix
+            {
+                ComputeInputPartialOverWeight(this, GradientValues(), Inputs(0)->GradientValues(), Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues(), m_tempMatrix, true);
+            }
+            else  // derivative with regard to the input feature
+            {
+                ComputeInputPartialOverInputFeature(this, GradientValues(), Inputs(1)->GradientValues(), Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues(), m_tempMatrix);
+            }
+        }
+
+        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq) 
+        {
+            if (inputIndex > 1)
+                throw std::invalid_argument("Convolution operation only takes two inputs.");
+
+            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            if (inputIndex == 0)  //derivative with regard to the weight matrix
+            {
+                ComputeInputPartialOverWeight(this, sliceOutputGrad, Inputs(0)->GradientValues(), Inputs(0)->FunctionValues(), sliceInput1Value, m_tempMatrix);
+            }
+            else  // derivative with regard to the input feature
+            {
+                Matrix<ElemType> sliceInput1Grad = Inputs(1)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+                ComputeInputPartialOverInputFeature(this, sliceOutputGrad, sliceInput1Grad, Inputs(0)->FunctionValues(), sliceInput1Value, m_tempMatrix);
+            }
+        }
+
+        virtual void EvaluateThisNode()  
+        {
+            EvaluateThisNodeS(this, FunctionValues(), Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues(), m_tempMatrix);
+        }
+
+        virtual void EvaluateThisNode(const size_t timeIdxInSeq) 
+        {
+            Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            EvaluateThisNodeS(this, sliceOutputValue, Inputs(0)->FunctionValues(), sliceInput1Value, m_tempMatrix);
+        }
+
+        static void WINAPI EvaluateThisNodeS(const ConvolutionNode<ElemType>* pConv, Matrix<ElemType> &functionValues, const Matrix<ElemType> &input0, 
+            const Matrix<ElemType> &input1, Matrix<ElemType> &tempMatrix)
+        {
+#if NANCHECK
+            input0.HasNan("Convolution-input0");
+            input1.HasNan("Convolution-input1");
+#endif
+            ConvolutionParams convParam = pConv->GetConvolutionParams();
+
+            size_t packedInputRows = convParam.kernelWidth * convParam.kernelHeight * convParam.inputChannels;
+            size_t packedInputColsPerSample = convParam.outputWidth * convParam.outputHeight;
+            size_t outputSizePerChannel = packedInputColsPerSample;
+            //size_t packedInputDim = packedInputRows * packedInputColsPerSample; // size of each packed input sample
+            //size_t inputDim = convParam.inputWidth * convParam.inputHeight * convParam.inputChannels;  //size of each input sample
+
+            long batchSize = (long)input1.GetNumCols();  //right child is the input sample
+
+            long maxTempMemSizeInSamples = (long)(convParam.maxTempMemSizeInSamples == 0? batchSize : convParam.maxTempMemSizeInSamples);
+
+            const Matrix<ElemType> & weightMatrix = input0;
+            assert(weightMatrix.GetNumCols() == packedInputRows && weightMatrix.GetNumRows() == convParam.outputChannels);
+            functionValues.Resize(convParam.outputChannels, outputSizePerChannel * batchSize);
+
+            long subBatchSize = (long)min(batchSize, maxTempMemSizeInSamples); 
+            long numSubBatches = (batchSize+subBatchSize-1)/subBatchSize; 
+
+            for (long i=0; i<numSubBatches; i++) 
+            {
+                long startSampleID = i*subBatchSize; 
+                long endSampleID = min(batchSize, startSampleID + subBatchSize); 
+                long smallBatchSize = endSampleID-startSampleID; 
+
+                tempMatrix.Resize(packedInputRows, packedInputColsPerSample * smallBatchSize);
+                Matrix<ElemType>  inputSubBatch = input1.ColumnSlice(startSampleID, smallBatchSize);
+                tempMatrix.AssignPackedConvolutionInput(inputSubBatch, 
+                                                                 convParam.inputWidth, convParam.inputHeight, convParam.inputChannels,
+                                                                 convParam.outputWidth, convParam.outputHeight, convParam.outputChannels,
+                                                                 convParam.kernelWidth, convParam.kernelHeight, convParam.horizontalSubsample, convParam.verticalSubsample, 
+                                                                 convParam.zeroPadding); 
+
+                Matrix<ElemType>  outputSubBatch = functionValues.ColumnSlice(outputSizePerChannel * startSampleID, outputSizePerChannel * smallBatchSize);
+                Matrix<ElemType>::Multiply(weightMatrix, false, tempMatrix, false, outputSubBatch);
+            }
+
+            functionValues.Reshape(convParam.outputChannels * outputSizePerChannel, batchSize);  //each sample becomes a column
+
+#if NANCHECK
+            functionValues.HasNan("Convolution");
+#endif
+        }
+
+        virtual void Validate()
+        {
+            PrintSelfBeforeValidation();
+
+            if (m_children.size() != 2) 
+                throw std::logic_error("ConvolutionNode requires two inputs.");
+
+            //we may want to remove this check in the future if we want to support the case that the weight itself is result of some computation 
+            //if (Inputs(0)->OperationName() != LearnableParameter<ElemType>::TypeName())
+            //    throw std::logic_error("ConvolutionNode requires the first input to be LearnableParameter type.");
+
+            if (m_horizontalSubsample > m_kernelWidth || m_verticalSubsample > m_kernelHeight)
+                throw std::invalid_argument("In ConvolutionNode horizontalSubsample must <= kernelWidth and verticalSubsample must <= kernelHeight.");
+
+            CopyImageSizeFromInputs();
+
+            size_t weightCols = m_kernelWidth * m_kernelHeight * m_inputChannels;
+
+            if (Inputs(0)->OperationName() == LearnableParameter<ElemType>::TypeName() && Inputs(0)->FunctionValues().GetNumElements() == 0)
+            {
+                Inputs(0)->FunctionValues().Resize(m_outputChannels, weightCols);
+            }
+
+            if (m_children[0]->FunctionValues().GetNumCols() != weightCols || m_children[0]->FunctionValues().GetNumRows() != m_outputChannels)
+            {
+                msra::strfun::strprintf msg("convolutionWeight matrix %ls should have dimension [%d, %d] which is [outputChannels, kernelWidth * kernelHeight * inputChannels]", 
+                    m_children[0]->NodeName().c_str(), m_outputChannels, weightCols);
+                throw std::logic_error(msg.c_str());            
+            }
+
+            size_t inputDim = m_inputWidth * m_inputHeight * m_inputChannels;
+            if (Inputs(1)->OperationName() == LearnableParameter<ElemType>::TypeName() && Inputs(1)->FunctionValues().GetNumRows() == 0)
+            {
+                Inputs(1)->FunctionValues().Resize(inputDim, Inputs(1)->FunctionValues().GetNumCols());
+            }
+
+            if (m_children[1]->FunctionValues().GetNumRows() != inputDim)
+            {
+                msra::strfun::strprintf msg("each column of input to the convolution node %ls is a sample and should have dimension %d, which is inputWidth * inputHeight * inputChannels", 
+                    NodeName().c_str(), inputDim);
+                throw std::logic_error(msg.c_str());            
+            }
+
+            if (Inputs(0)->FunctionValues().GetNumElements() == 0 || Inputs(1)->FunctionValues().GetNumElements() == 0 )
+                throw std::logic_error("Convolution operation: one of the operants has 0 element.");
+            
+            size_t outputDim = m_outputWidth * m_outputHeight * m_outputChannels;
+            FunctionValues().Resize(outputDim, m_children[1]->FunctionValues().GetNumCols());
+        }
+
+        virtual void CopyImageSizeFromInputs()
+        {
+            CopyImageSizeFromInput(1, false);
+
+            if (m_inputWidth < m_kernelWidth || m_inputHeight < m_kernelHeight)
+                throw std::invalid_argument("inputWidth must >= kernelWidth and inputHeight must >= kernelHeight.");
+
+            if (m_zeroPadding)
+            {
+                const int kernelWidthCenter = m_kernelWidth % 2;
+                const int kernelHeightCenter = m_kernelHeight % 2;
+                m_outputWidth = (m_inputWidth-kernelWidthCenter)/m_horizontalSubsample + 1;
+                m_outputHeight = (m_inputHeight-kernelHeightCenter)/m_verticalSubsample + 1;
+            }
+            else
+            {
+                m_outputWidth = (m_inputWidth-m_kernelWidth)/m_horizontalSubsample + 1;
+                m_outputHeight = (m_inputHeight-m_kernelHeight)/m_verticalSubsample + 1;
+            }    
+        }
+
+        virtual void AttachInputs(const ComputationNodePtr convolutionWeight, const ComputationNodePtr inputFeature) 
+        {
+            m_children.resize(2);
+            m_children[0] = convolutionWeight;
+            m_children[1] = inputFeature;
+        }
+
+        virtual void MoveMatricesToDevice(const DEVICEID_TYPE deviceId)
+        {
+            ComputationNode<ElemType>::MoveMatricesToDevice(deviceId);
+
+            if (deviceId != AUTOPLACEMATRIX)
+            {
+                if (m_tempMatrix.GetDeviceId() != deviceId)
+                    m_tempMatrix.TransferFromDeviceToDevice(m_tempMatrix.GetDeviceId(), deviceId);
+            }
+        }
+
+        virtual void DumpNodeInfo(const bool printValues, File& fstream) const
+        {
+            ComputationNode<ElemType>::DumpNodeInfo(printValues, fstream);
+
+            char str[4096];
+            sprintf(str, "Input[Width:%lu, Height:%lu, Channels:%lu]  \n", m_inputWidth, m_inputHeight, m_inputChannels);
+            fstream << string(str);
+            sprintf(str, "Kernel[Width:%lu, Height:%lu]  SubSample[Horizontal:%lu, Vertical:%lu]\n", m_kernelWidth, m_kernelHeight, m_horizontalSubsample, m_verticalSubsample);
+            fstream << string(str);
+            sprintf(str, "Output[Width:%lu, Height:%lu, Channels:%lu]  \n", m_outputWidth, m_outputHeight, m_outputChannels);
+            fstream << string(str);
+            sprintf(str, "ZeroPadding=%ls  maxTempMemSizeInSamples=%lu\n", m_zeroPadding? L"true" : L"false", m_maxTempMemSizeInSamples);
+            fstream << string(str);
+        }
+
+        void SetmMaxTempMemSizeInSamples(const size_t maxTempMemSizeInSamples)
+        {
+            m_maxTempMemSizeInSamples = maxTempMemSizeInSamples;
+        }
+
+    private:
+        static void WINAPI ComputeInputPartialOverWeight(const ConvolutionNode<ElemType>* pConv, Matrix<ElemType> &gradientValues, 
+            Matrix<ElemType> &inputGradientValues, const Matrix<ElemType> &/*input0*/, const Matrix<ElemType> &input1, Matrix<ElemType> &tempMatrix, const bool inLoop=false)
+        {
+            ConvolutionParams convParam = pConv->GetConvolutionParams();
+
+            size_t packedInputRows = convParam.kernelWidth * convParam.kernelHeight * convParam.inputChannels;
+            size_t packedInputColsPerSample = convParam.outputWidth * convParam.outputHeight;
+            size_t outputSizePerChannel = packedInputColsPerSample;
+            //size_t packedInputDim = packedInputRows * packedInputColsPerSample; // size of each packed input sample
+            //size_t inputDim = convParam.inputWidth * convParam.inputHeight * convParam.inputChannels;  //size of each input sample
+
+            long batchSize = (long) input1.GetNumCols(); //right child is the input sample
+
+            long maxTempMemSizeInSamples = (long) (convParam.maxTempMemSizeInSamples == 0? batchSize : convParam.maxTempMemSizeInSamples);
+
+            //const Matrix<ElemType> & weightMatrix = input0;
+            //inputGradientValues.Resize(weightMatrix.GetNumRows(), weightMatrix.GetNumCols()); //should have been resized when preparing gradient computation
+
+            gradientValues.Reshape(convParam.outputChannels,  outputSizePerChannel * batchSize);  //reshape to match the longernal operation
+
+            long subBatchSize = min(batchSize, maxTempMemSizeInSamples); 
+            long numSubBatches = (batchSize+subBatchSize-1)/subBatchSize; 
+
+            if (numSubBatches == 1 && !inLoop)  //reuse packed input from evaluation step if it's not changed by either subbatch or recurrent steps.
+            {
+                Matrix<ElemType>::MultiplyAndAdd(gradientValues, false, tempMatrix, true, inputGradientValues);
+            }
+            else
+            {
+                for (long i=0; i<numSubBatches; i++) 
+                {
+                    long startSampleID = i*subBatchSize; 
+                    long endSampleID = min(batchSize, startSampleID + subBatchSize); 
+                    long smallBatchSize = endSampleID-startSampleID; 
+
+                    tempMatrix.Resize(packedInputRows, packedInputColsPerSample * smallBatchSize);
+                    Matrix<ElemType> inputSubBatch = input1.ColumnSlice(startSampleID, smallBatchSize);
+                    tempMatrix.AssignPackedConvolutionInput(inputSubBatch, 
+                                                                     convParam.inputWidth, convParam.inputHeight, convParam.inputChannels,
+                                                                     convParam.outputWidth, convParam.outputHeight, convParam.outputChannels,
+                                                                     convParam.kernelWidth, convParam.kernelHeight, convParam.horizontalSubsample, convParam.verticalSubsample, 
+                                                                     convParam.zeroPadding); 
+
+                    Matrix<ElemType> outputGradientSubBatch = gradientValues.ColumnSlice(startSampleID * outputSizePerChannel, smallBatchSize * outputSizePerChannel);
+                    Matrix<ElemType>::MultiplyAndAdd(outputGradientSubBatch, false, tempMatrix, true, inputGradientValues);
+                }
+            }
+
+            gradientValues.Reshape(convParam.outputChannels * outputSizePerChannel, batchSize);  //change back
+        }
+
+        //compute gradient over the packed input and then convert the result to the original input
+        static void WINAPI ComputeInputPartialOverInputFeature(const ConvolutionNode<ElemType>* pConv, Matrix<ElemType> &gradientValues, const Matrix<ElemType> &inputGradientValues, const Matrix<ElemType> &input0, const Matrix<ElemType> &input1, Matrix<ElemType> &tempMatrix)
+        {
+            
+            ConvolutionParams convParam = pConv->GetConvolutionParams();
+            size_t packedInputRows = convParam.kernelWidth * convParam.kernelHeight * convParam.inputChannels;
+            size_t packedInputColsPerSample = convParam.outputWidth * convParam.outputHeight;
+            size_t outputSizePerChannel = packedInputColsPerSample;
+            //size_t packedInputDim = packedInputRows * packedInputColsPerSample; // size of each packed input sample
+            //size_t inputDim = convParam.inputWidth * convParam.inputHeight * convParam.inputChannels;  //size of each input sample
+
+            long batchSize = (long) input1.GetNumCols(); //right child is the input sample
+
+            long maxTempMemSizeInSamples = (long) (convParam.maxTempMemSizeInSamples == 0? batchSize : convParam.maxTempMemSizeInSamples);
+
+            const Matrix<ElemType> & weightMatrix = input0;
+
+            gradientValues.Reshape(convParam.outputChannels,  outputSizePerChannel * batchSize);  //reshape to match the longernal operation
+
+            long subBatchSize = min(batchSize, maxTempMemSizeInSamples); 
+            long numSubBatches = (batchSize+subBatchSize-1)/subBatchSize; 
+
+            for (long i=0; i<numSubBatches; i++) 
+            {
+                long startSampleID = i*subBatchSize; 
+                long endSampleID = min(batchSize, startSampleID + subBatchSize); 
+                long smallBatchSize = endSampleID-startSampleID; 
+
+                tempMatrix.Resize(packedInputRows, packedInputColsPerSample * smallBatchSize);
+                Matrix<ElemType> outputGradientSubBatch = gradientValues.ColumnSlice(startSampleID * outputSizePerChannel, smallBatchSize * outputSizePerChannel);
+                Matrix<ElemType>::Multiply(weightMatrix, true, outputGradientSubBatch, false,  tempMatrix);
+
+                Matrix<ElemType> inputGradientSubBatch = inputGradientValues.ColumnSlice(startSampleID, smallBatchSize);
+                tempMatrix.UnpackConvolutionInput(inputGradientSubBatch, 
+                                                                 convParam.inputWidth, convParam.inputHeight, convParam.inputChannels,
+                                                                 convParam.outputWidth, convParam.outputHeight, convParam.outputChannels,
+                                                                 convParam.kernelWidth, convParam.kernelHeight, convParam.horizontalSubsample, convParam.verticalSubsample, 
+                                                                 convParam.zeroPadding); 
+            }
+
+            gradientValues.Reshape(convParam.outputChannels * outputSizePerChannel, batchSize);  //change back
+        }
+        
+
+    private:
+        size_t m_kernelWidth, m_kernelHeight;
+        size_t m_horizontalSubsample, m_verticalSubsample;
+        bool m_zeroPadding;
+
+        Matrix<ElemType> m_tempMatrix; 
+        size_t m_maxTempMemSizeInSamples; // can change during runtime
+    };
+
+    template class ConvolutionNode<float>; 
+    template class ConvolutionNode<double>;
+
+    struct PoolParams
+    {
+        size_t inputWidth, inputHeight, inputChannels;
+        size_t windowWidth, windowHeight;
+        size_t horizontalSubsample, verticalSubsample;
+        size_t outputWidth, outputHeight, outputChannels;
+        size_t inputSizePerSample, outputSizePerSample;
+    };
+
+    //Max Pooling: support multi channel
+    //assume each column is an input sample. Each sample is stored in  (r00, g00, b00, r01, g01, b01, r10, g10, b10, r11, g11, b11)
+    template<class ElemType>
+    class MaxPoolingNode : public ComputationNode<ElemType>
+    {
+        UsingComputationNodeMembers;
+    public:
+        MaxPoolingNode( const size_t windowWidth, const size_t windowHeight, 
+                        const size_t horizontalSubsample, const size_t verticalSubsample, 
+                        const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId),
+                          m_windowWidth(windowWidth), m_windowHeight(windowHeight),
+                          m_horizontalSubsample(horizontalSubsample), m_verticalSubsample(verticalSubsample)                       
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            m_deviceId = deviceId;
+            MoveMatricesToDevice(deviceId);
+            InitRecurrentNode();
+        }
+                
+        MaxPoolingNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            LoadFromFile(fstream, modelVersion, deviceId);
+        }
+                
+        virtual void SaveToFile(File& fstream) const
+        {
+            ComputationNode<ElemType>::SaveToFile(fstream);
+
+            fstream << m_windowWidth << m_windowHeight << m_horizontalSubsample << m_verticalSubsample; 
+        }
+
+        virtual void LoadFromFile(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX)
+        {
+            ComputationNode<ElemType>::LoadFromFile(fstream, modelVersion, deviceId);
+
+            fstream >> m_windowWidth >> m_windowHeight >> m_horizontalSubsample >> m_verticalSubsample; 
+        }
+
+        virtual void CopyTo(const ComputationNodePtr nodeP, const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            ComputationNode<ElemType>::CopyTo(nodeP, newName, flags);
+            MaxPoolingNode<ElemType>* node = (MaxPoolingNode<ElemType>*) nodeP;
+
+            if (flags & CopyNodeFlags::copyNodeValue)
+            {
+                node->m_inputWidth = m_inputWidth;
+                node->m_inputHeight = m_inputHeight;
+                node->m_inputChannels = m_inputChannels;
+
+                node->m_windowWidth = m_windowWidth;
+                node->m_windowHeight = m_windowHeight;
+
+                node->m_horizontalSubsample = m_horizontalSubsample;
+                node->m_verticalSubsample = m_verticalSubsample;
+
+                node->m_outputWidth = m_outputWidth;
+                node->m_outputHeight = m_outputHeight;
+                node->m_outputChannels = m_outputChannels;
+
+                node->m_inputSizePerSample = m_inputSizePerSample;
+                node->m_outputSizePerSample = m_outputSizePerSample;
+            }
+        }
+        // copy constructor
+        MaxPoolingNode(const MaxPoolingNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags) : ComputationNode<ElemType>(node->m_deviceId)
+        {
+            node->CopyTo(this, newName, flags);
+        }
+
+        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            const std::wstring& name = (newName == L"")?NodeName():newName;
+                
+            ComputationNodePtr node = new MaxPoolingNode<ElemType>(this, name, flags);
+            return node;
+        }
+
+        virtual const std::wstring OperationName() const {return TypeName();}
+        static const std::wstring TypeName() {return L"MaxPooling";}
+
+        PoolParams GetPoolParams() const
+        {
+            PoolParams poolParams;
+            poolParams.inputWidth = m_inputWidth;
+            poolParams.inputHeight = m_inputHeight;
+            poolParams.inputChannels = m_inputChannels;
+
+            poolParams.windowWidth = m_windowWidth;
+            poolParams.windowHeight = m_windowHeight;
+
+            poolParams.horizontalSubsample = m_horizontalSubsample;
+            poolParams.verticalSubsample = m_verticalSubsample;
+
+            poolParams.outputWidth = m_outputWidth;
+            poolParams.outputHeight = m_outputHeight;
+            poolParams.outputChannels = m_outputChannels;
+
+            poolParams.inputSizePerSample = m_inputSizePerSample;
+            poolParams.outputSizePerSample = m_outputSizePerSample;
+            return poolParams;
+        }
+
+        virtual void ComputeInputPartial(const size_t inputIndex)
+        {
+            if (inputIndex > 0)
+                throw std::invalid_argument("MaxPooling operation only takes one inputs.");
+
+            ComputeInputPartialS(this, GradientValues(), Inputs(0)->GradientValues(), Inputs(0)->FunctionValues(), FunctionValues());
+        }
+
+        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq) 
+        {
+            if (inputIndex > 0)
+                throw std::invalid_argument("MaxPooling operation only takes one inputs.");
+
+            Matrix<ElemType> sliceInput0Grad = Inputs(0)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            Matrix<ElemType> sliceInput0Value = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            ComputeInputPartialS(this, sliceOutputGrad, sliceInput0Grad, sliceInput0Value, sliceOutputValue);
+        }
+
+        static void WINAPI ComputeInputPartialS(const MaxPoolingNode<ElemType>* ppool, const Matrix<ElemType> &gradientValues, Matrix<ElemType> &inputGradientValues, const Matrix<ElemType> &input0, const Matrix<ElemType> &functionValues)
+        {
+            PoolParams poolParams = ppool->GetPoolParams();
+
+            inputGradientValues.AddMaxPoolingGradient(gradientValues, input0, functionValues, poolParams.inputChannels,
+                                                    poolParams.inputWidth, poolParams.inputHeight, poolParams.inputSizePerSample, 
+                                                    poolParams.outputWidth, poolParams.outputHeight, poolParams.outputSizePerSample, 
+                                                    poolParams.windowWidth, poolParams.windowHeight, poolParams.horizontalSubsample, poolParams.verticalSubsample);
+        }
+
+        virtual void EvaluateThisNode()  
+        {
+#if NANCHECK
+            Inputs(0)->FunctionValues().HasNan("MaxPooling-input0");
+#endif
+            EvaluateThisNodeS(this, FunctionValues(), Inputs(0)->FunctionValues());
+#if NANCHECK
+            m_functionValues.HasNan("MaxPooling");
+#endif
+        }
+
+        virtual void EvaluateThisNode(const size_t timeIdxInSeq) 
+        {
+            Matrix<ElemType> sliceInput0Value = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            EvaluateThisNodeS(this, sliceOutputValue, sliceInput0Value);
+        }
+
+        static void WINAPI EvaluateThisNodeS(const MaxPoolingNode<ElemType>* ppool, Matrix<ElemType> &functionValues, const Matrix<ElemType> &input0)
+        {
+            PoolParams poolParams = ppool->GetPoolParams();
+            functionValues.AssignMaxPoolingResult(input0, poolParams.inputChannels,
+                                                 poolParams.inputWidth, poolParams.inputHeight, poolParams.inputSizePerSample, 
+                                                 poolParams.outputWidth, poolParams.outputHeight, poolParams.outputSizePerSample, 
+                                                 poolParams.windowWidth, poolParams.windowHeight, poolParams.horizontalSubsample, poolParams.verticalSubsample);
+        }
+
+        virtual void Validate()
+        {
+            PrintSelfBeforeValidation();
+
+            if (m_children.size() != 1) 
+                throw std::logic_error("MaxPoolingNode requires one input.");
+
+            if (m_horizontalSubsample > m_windowWidth || m_verticalSubsample > m_windowHeight)
+                throw std::invalid_argument("MaxPoolingNode: horizontalSubsample must <= windowWidth and verticalSubsample must <= windowHeight.");
+
+            CopyImageSizeFromInputs();
+
+            m_inputSizePerSample = m_inputWidth * m_inputHeight * m_inputChannels;
+            m_outputSizePerSample = m_outputWidth * m_outputHeight * m_outputChannels;
+
+            if (Inputs(0)->OperationName() == LearnableParameter<ElemType>::TypeName() && Inputs(0)->FunctionValues().GetNumRows() == 0)
+            {
+                Inputs(0)->FunctionValues().Resize(m_inputSizePerSample, Inputs(0)->FunctionValues().GetNumCols());
+            }
+
+            if (m_children[0]->FunctionValues().GetNumRows() != m_inputSizePerSample)
+            {
+                msra::strfun::strprintf msg("each column of input to the MaxPooling node %ls is a sample and should have dimension %d, which is inputWidth * inputHeight * inputChannels", 
+                    NodeName().c_str(), m_inputSizePerSample);
+                throw std::logic_error(msg.c_str());            
+            }
+            
+            if (Inputs(0)->FunctionValues().GetNumElements() == 0)
+                throw std::logic_error("MaxPoolingNode operation: the input node has 0 element.");
+
+            m_functionValues.Resize(m_outputSizePerSample, m_children[0]->FunctionValues().GetNumCols());
+        }
+
+        virtual void CopyImageSizeFromInputs()
+        {
+            CopyImageSizeFromInput(0, false);
+
+            if (m_inputWidth < m_windowWidth || m_inputHeight < m_windowHeight)
+                throw std::invalid_argument("MaxPoolingNode: inputWidth must >= windowWidth and inputHeight must >= windowHeight.");
+
+            m_outputWidth = (m_inputWidth-m_windowWidth)/m_horizontalSubsample + 1;
+            m_outputHeight = (m_inputHeight-m_windowHeight)/m_verticalSubsample + 1;
+            m_outputChannels = m_inputChannels;
+        }
+
+        virtual void AttachInputs(const ComputationNodePtr inputFeature) 
+        {
+            m_children.resize(1);
+            m_children[0] = inputFeature;
+        }
+
+        virtual void DumpNodeInfo(const bool printValues, File& fstream) const
+        {
+            ComputationNode<ElemType>::DumpNodeInfo(printValues, fstream);
+
+            char str[4096];
+            sprintf(str, "Input[Width:%lu, Height:%lu, Channels:%lu]  \n", m_inputWidth, m_inputHeight, m_inputChannels);
+            fstream << string(str);
+            sprintf(str, "PoolingWindow[Width:%lu, Height:%lu]  SubSampling[Horizontal:%lu, Vertical:%lu]\n", m_windowWidth, m_windowHeight, m_horizontalSubsample, m_verticalSubsample);
+            fstream << string(str);
+            sprintf(str, "Output[Width:%lu, Height:%lu, Channels:%lu]  \n", m_outputWidth, m_outputHeight, m_outputChannels);
+            fstream << string(str);
+            sprintf(str, "TotalSizePerSample[Input:%lu, Output:%lu]  \n", m_inputSizePerSample, m_outputSizePerSample);
+            fstream << string(str);
+        }
+
+    private:
+        size_t m_windowWidth, m_windowHeight;
+        size_t m_horizontalSubsample, m_verticalSubsample;
+        size_t m_inputSizePerSample, m_outputSizePerSample;
+    };
+
+    template class MaxPoolingNode<float>; 
+    template class MaxPoolingNode<double>;    
+
+    //Average Pooling: support multi channel
+    //assume each column is an input sample. Each sample is stored in  (r00, g00, b00, r01, g01, b01, r10, g10, b10, r11, g11, b11)
+    template<class ElemType>
+    class AveragePoolingNode : public ComputationNode<ElemType>
+    {
+        UsingComputationNodeMembers;
+    public:
+        AveragePoolingNode(const size_t windowWidth, const size_t windowHeight, 
+                        const size_t horizontalSubsample, const size_t verticalSubsample, 
+                        const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId),
+                          m_windowWidth(windowWidth), m_windowHeight(windowHeight),
+                          m_horizontalSubsample(horizontalSubsample), m_verticalSubsample(verticalSubsample)                     
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            m_deviceId = deviceId;
+            MoveMatricesToDevice(deviceId);
+            InitRecurrentNode();
+        }
+
+        AveragePoolingNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            LoadFromFile(fstream, modelVersion, deviceId);
+        }                
+                
+        virtual void SaveToFile(File& fstream) const
+        {
+            ComputationNode<ElemType>::SaveToFile(fstream);
+
+            fstream << m_windowWidth << m_windowHeight << m_horizontalSubsample << m_verticalSubsample; 
+        }
+
+        virtual void LoadFromFile(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX)
+        {
+            ComputationNode<ElemType>::LoadFromFile(fstream, modelVersion, deviceId);
+
+            fstream >> m_windowWidth >> m_windowHeight >> m_horizontalSubsample >> m_verticalSubsample; 
+        }
+
+        virtual void CopyTo(const ComputationNodePtr nodeP, const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            ComputationNode<ElemType>::CopyTo(nodeP, newName, flags);
+            AveragePoolingNode<ElemType>* node = (AveragePoolingNode<ElemType>*) nodeP;
+
+            if (flags & CopyNodeFlags::copyNodeValue)
+            {
+                node->m_inputWidth = m_inputWidth;
+                node->m_inputHeight = m_inputHeight;
+                node->m_inputChannels = m_inputChannels;
+
+                node->m_windowWidth = m_windowWidth;
+                node->m_windowHeight = m_windowHeight;
+
+                node->m_horizontalSubsample = m_horizontalSubsample;
+                node->m_verticalSubsample = m_verticalSubsample;
+
+                node->m_outputWidth = m_outputWidth;
+                node->m_outputHeight = m_outputHeight;
+                node->m_outputChannels = m_outputChannels;
+
+                node->m_inputSizePerSample = m_inputSizePerSample;
+                node->m_outputSizePerSample = m_outputSizePerSample;
+            }
+        }
+
+        // copy constructor
+        AveragePoolingNode(const AveragePoolingNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags) : ComputationNode<ElemType>(node->m_deviceId)
+        {
+            node->CopyTo(this, newName, flags);
+        }
+
+        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            const std::wstring& name = (newName == L"")?NodeName():newName;
+                
+            ComputationNodePtr node = new AveragePoolingNode<ElemType>(this, name, flags);
+            return node;
+        }
+
+        virtual const std::wstring OperationName() const {return TypeName();}
+        static const std::wstring TypeName() {return L"AveragePooling";}
+        PoolParams GetPoolParams() const
+        {
+            PoolParams poolParams;
+            poolParams.inputWidth = m_inputWidth;
+            poolParams.inputHeight = m_inputHeight;
+            poolParams.inputChannels = m_inputChannels;
+
+            poolParams.windowWidth = m_windowWidth;
+            poolParams.windowHeight = m_windowHeight;
+
+            poolParams.horizontalSubsample = m_horizontalSubsample;
+            poolParams.verticalSubsample = m_verticalSubsample;
+
+            poolParams.outputWidth = m_outputWidth;
+            poolParams.outputHeight = m_outputHeight;
+            poolParams.outputChannels = m_outputChannels;
+
+            poolParams.inputSizePerSample = m_inputSizePerSample;
+            poolParams.outputSizePerSample = m_outputSizePerSample;
+            return poolParams;
+        }
+
+        virtual void ComputeInputPartial(const size_t inputIndex)
+        {
+            if (inputIndex > 0)
+                throw std::invalid_argument("AveragePooling operation only takes one inputs.");
+
+            ComputeInputPartialS(this, GradientValues(), Inputs(0)->GradientValues());
+        }
+
+        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq) 
+        {
+            if (inputIndex > 0)
+                throw std::invalid_argument("AveragePooling operation only takes one inputs.");
+
+            Matrix<ElemType> sliceInput0Grad = Inputs(0)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            ComputeInputPartialS(this, sliceOutputGrad, sliceInput0Grad);
+        }
+
+        static void WINAPI ComputeInputPartialS(const AveragePoolingNode<ElemType>* ppool, const Matrix<ElemType> &gradientValues, Matrix<ElemType> &inputGradientValues)
+        {
+            PoolParams poolParams = ppool->GetPoolParams();
+
+            inputGradientValues.AddAveragePoolingGradient(gradientValues, poolParams.inputChannels,
+                                                    poolParams.inputWidth, poolParams.inputHeight, poolParams.inputSizePerSample, 
+                                                    poolParams.outputWidth, poolParams.outputHeight, poolParams.outputSizePerSample, 
+                                                    poolParams.windowWidth, poolParams.windowHeight, poolParams.horizontalSubsample, poolParams.verticalSubsample);
+        }
+
+        virtual void EvaluateThisNode()  
+        {
+#if NANCHECK
+            Inputs(0)->FunctionValues().HasNan("AveragePooling-input0");
+#endif
+            EvaluateThisNodeS(this, FunctionValues(), Inputs(0)->FunctionValues());
+#if NANCHECK
+            m_functionValues.HasNan("AveragePooling");
+#endif
+        }
+
+        virtual void EvaluateThisNode(const size_t timeIdxInSeq) 
+        {
+            Matrix<ElemType> sliceInput0Value = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            EvaluateThisNodeS(this, sliceOutputValue, sliceInput0Value);
+        }
+
+        static void WINAPI EvaluateThisNodeS(const AveragePoolingNode<ElemType>* ppool, Matrix<ElemType> &functionValues, const Matrix<ElemType> &input0)
+        {
+            PoolParams poolParams = ppool->GetPoolParams();
+            
+            functionValues.AssignAveragePoolingResult(input0, poolParams.inputChannels,
+                                                 poolParams.inputWidth, poolParams.inputHeight, poolParams.inputSizePerSample, 
+                                                 poolParams.outputWidth, poolParams.outputHeight, poolParams.outputSizePerSample, 
+                                                 poolParams.windowWidth, poolParams.windowHeight, poolParams.horizontalSubsample, poolParams.verticalSubsample);
+        }
+
+        virtual void Validate()
+        {
+            PrintSelfBeforeValidation();
+
+            if (m_children.size() != 1) 
+                throw std::logic_error("AveragePoolingNode requires one input.");
+
+            if (m_horizontalSubsample > m_windowWidth || m_verticalSubsample > m_windowHeight)
+                throw std::invalid_argument("AveragePoolingNode: horizontalSubsample must <= windowWidth and verticalSubsample must <= windowHeight.");
+
+            CopyImageSizeFromInputs();
+
+            m_inputSizePerSample = m_inputWidth * m_inputHeight * m_inputChannels;
+            m_outputSizePerSample = m_outputWidth * m_outputHeight * m_outputChannels;
+
+            if (Inputs(0)->OperationName() == LearnableParameter<ElemType>::TypeName() && Inputs(0)->FunctionValues().GetNumRows() == 0)
+            {
+                Inputs(0)->FunctionValues().Resize(m_inputSizePerSample, Inputs(0)->FunctionValues().GetNumCols());
+            }
+
+            if (m_children[0]->FunctionValues().GetNumRows() != m_inputSizePerSample)
+            {
+                msra::strfun::strprintf msg("each column of input to the AveragePooling node %ls is a sample and should have dimension %d, which is inputWidth * inputHeight * inputChannels", 
+                    NodeName().c_str(), m_inputSizePerSample);
+                throw std::logic_error(msg.c_str());            
+            }
+                        
+            if (Inputs(0)->FunctionValues().GetNumElements() == 0)
+                throw std::logic_error("AveragePoolingNode operation: the input node has 0 element.");
+
+            FunctionValues().Resize(m_outputSizePerSample, m_children[0]->FunctionValues().GetNumCols());
+        }
+
+        virtual void CopyImageSizeFromInputs()
+        {
+            CopyImageSizeFromInput(0, false);
+
+            if (m_inputWidth < m_windowWidth || m_inputHeight < m_windowHeight)
+                throw std::invalid_argument("AveragePoolingNode: inputWidth must >= windowWidth and inputHeight must >= windowHeight.");
+
+            m_outputWidth = (m_inputWidth-m_windowWidth)/m_horizontalSubsample + 1;
+            m_outputHeight = (m_inputHeight-m_windowHeight)/m_verticalSubsample + 1;
+            m_outputChannels = m_inputChannels;
+        }
+
+        virtual void AttachInputs(const ComputationNodePtr inputFeature) 
+        {
+            m_children.resize(1);
+            m_children[0] = inputFeature;
+        }
+
+        virtual void DumpNodeInfo(const bool printValues, File& fstream) const
+        {
+            ComputationNode<ElemType>::DumpNodeInfo(printValues, fstream);
+
+            char str[4096];
+            sprintf(str, "Input[Width:%lu, Height:%lu, Channels:%lu]  \n", m_inputWidth, m_inputHeight, m_inputChannels);
+            fstream << string(str);
+            sprintf(str, "PoolingWindow[Width:%lu, Height:%lu]  SubSample[Horizontal:%lu, Vertical:%lu]\n", m_windowWidth, m_windowHeight, m_horizontalSubsample, m_verticalSubsample);
+            fstream << string(str);
+            sprintf(str, "Output[Width:%lu, Height:%lu, Channels:%lu]  \n", m_outputWidth, m_outputHeight, m_outputChannels);
+            fstream << string(str);
+            sprintf(str, "TotalSizePerSample[Input:%lu, Output:%lu]\n", m_inputSizePerSample, m_outputSizePerSample);
+            fstream << string(str);
+        }
+
+    private:
+        size_t m_windowWidth, m_windowHeight;
+        size_t m_horizontalSubsample, m_verticalSubsample;
+        size_t m_inputSizePerSample, m_outputSizePerSample;
+    };
+
+    template class AveragePoolingNode<float>; 
+    template class AveragePoolingNode<double>;    
+
+}}}
diff --git a/MachineLearning/CNTK/InputAndParamNodes.h b/MachineLearning/CNTK/InputAndParamNodes.h
new file mode 100644
index 000000000..83c974617
--- /dev/null
+++ b/MachineLearning/CNTK/InputAndParamNodes.h
@@ -0,0 +1,504 @@
+//
+// <copyright file="InputAndParamNodes.h" company="Microsoft">
+//     Copyright (c) Microsoft Corporation.  All rights reserved.
+// </copyright>
+//
+#pragma once
+
+#include <unordered_set>
+#include <map>
+#include <string>
+#include <vector>
+#include <stdexcept>
+#include <list>
+#include <memory>
+#include <algorithm>
+#include <assert.h>
+#include <atomic>
+#include <sstream>
+#include <iostream>
+
+#include "Basics.h"
+#include "Matrix.h"
+#include "ComputationNode.h"
+
+namespace Microsoft { namespace MSR { namespace CNTK {
+
+    //used to represent weight Matrix<ElemType> and biases
+    template<class ElemType>
+    class LearnableParameter : public ComputationNode<ElemType>
+    {
+        UsingComputationNodeMembers;
+    public:
+        LearnableParameter(size_t rows, size_t cols, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)
+        {
+            //intentionally comment out so that we may support automatic dimention inference
+            //if (rows * cols == 0) 
+            //    throw std::logic_error("This LearnableParameter dimension is 0.");
+
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            m_needGradient = true;
+            m_deviceId = deviceId;
+            MoveMatricesToDevice(deviceId);
+            m_functionValues.Resize(rows, cols);
+
+            m_outputWidth = 1;
+            m_outputHeight = rows;
+            m_outputChannels = 1;
+
+            InitRecurrentNode();
+        }
+
+        LearnableParameter(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            LoadFromFile(fstream, modelVersion, deviceId);
+        }
+
+        virtual void SaveToFile(File& fstream) const
+        {
+            ComputationNode<ElemType>::SaveToFile(fstream);
+
+            fstream << NeedGradient();
+            fstream << FunctionValues().GetNumRows() << FunctionValues().GetNumCols(); 
+            fstream << FunctionValues();
+        }
+        
+        virtual void LoadFromFile(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX)
+        {
+            ComputationNode<ElemType>::LoadFromFile(fstream, modelVersion, deviceId);
+
+            size_t rows, cols;
+            fstream >> m_needGradient;
+            fstream >> rows >> cols;
+
+            //intentionally comment out to support automatic dimention inference
+            //if (rows * cols == 0) 
+            //    throw std::logic_error("This LearnableParameter dimension is 0.");
+
+            m_functionValues.Resize(rows, cols);
+            fstream >> m_functionValues;
+
+            m_outputWidth = 1;
+            m_outputHeight = rows;
+            m_outputChannels = 1;
+        }
+
+
+        virtual const std::wstring OperationName() const {return TypeName();}
+        virtual void ComputeInputPartial(const size_t /*inputIndex*/) {}
+        virtual void ComputeInputPartial(const size_t /*inputIndex*/, const size_t /*timeIdxInSeq*/) {}
+        virtual void EvaluateThisNode()  {}
+        virtual void EvaluateThisNode(const size_t /*timeIdxInSeq*/) {}
+        virtual void Validate() 
+        {
+            PrintSelfBeforeValidation();
+        }
+
+        static const std::wstring TypeName() {return L"LearnableParameter";} 
+
+        virtual void DumpNodeInfo(const bool printValues, File& fstream) const
+        {
+            ComputationNode<ElemType>::DumpNodeInfo(printValues, fstream);
+
+            char str[4096];
+            sprintf(str, "[%lu,%lu]  ", FunctionValues().GetNumRows(), FunctionValues().GetNumCols());
+            fstream << string(str);
+            sprintf(str, "NeedGradient=%s", NeedGradient()? "true" : "false");
+            fstream << string(str);
+
+            PrintNodeValuesToFile(printValues, fstream);
+        }
+
+        // copy constructor
+        LearnableParameter(const LearnableParameter<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags) : ComputationNode<ElemType>(node->m_deviceId)
+        {
+            node->CopyTo(this, newName, flags);
+        }
+
+        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            const std::wstring& name = (newName == L"")?NodeName():newName;
+                
+            ComputationNodePtr node = new LearnableParameter<ElemType>(this, name, flags);
+            return node;
+        }
+    };
+
+    //WARNING: Don't use SparseLearnableParameter yet since the current version assumes the parameter is dense instead of sparse
+    //WARNING: After the right implementation is put here we need to turn it on in NetworkDescriptionLangauge.cpp
+    template<class ElemType>
+    class SparseLearnableParameter : public LearnableParameter<ElemType>
+    {
+        UsingComputationNodeMembers;
+    public:
+        SparseLearnableParameter(size_t rows, size_t cols, const size_t size, const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX, const std::wstring name = L"")
+            : LearnableParameter<ElemType>(rows, cols, deviceId, name)
+        {
+            m_gradientValues.SwitchToMatrixType(MatrixType::SPARSE, matrixFormatSparseBlockCol, false);
+            m_gradientValues.Resize(rows, cols, size);
+        }
+
+        SparseLearnableParameter (File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX, const std::wstring name = L"") 
+            : LearnableParameter<ElemType>(fstream, modelVersion, deviceId, name)
+        {
+            m_gradientValues.SwitchToMatrixType(MatrixType::SPARSE, matrixFormatSparseBlockCol, false);
+            m_gradientValues.Resize(FunctionValues().GetNumRows(), FunctionValues().GetNumCols());
+        }
+
+        virtual void LoadFromFile(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX)
+        {
+            LearnableParameter<ElemType>::LoadFromFile(fstream,   modelVersion, deviceId);
+            m_gradientValues.SwitchToMatrixType(MatrixType::SPARSE, matrixFormatSparseBlockCol, false);
+            m_gradientValues.Resize(FunctionValues().GetNumRows(), FunctionValues().GetNumCols());
+        }
+
+        virtual const std::wstring OperationName() const {return TypeName();}
+        static const std::wstring TypeName() {return L"SparseLearnableParameter";} 
+
+        // copy constructor
+        SparseLearnableParameter (const SparseLearnableParameter <ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags) 
+            : LearnableParameter<ElemType>( node, newName, flags)
+        {
+        }
+
+        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            const std::wstring& name = (newName == L"")?NodeName():newName;
+                
+            ComputationNodePtr node = new SparseLearnableParameter<ElemType>(this, name, flags);
+            return node;
+        }
+    };
+
+    template class SparseLearnableParameter<float>; 
+    template class SparseLearnableParameter<double>;
+
+    template<class ElemType>
+    class InputValue : public ComputationNode<ElemType>
+    {
+        UsingComputationNodeMembers;
+    public:
+        InputValue(size_t rows, size_t cols, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId) 
+        {
+            if (rows * cols == 0) 
+                throw std::logic_error("This InputValue dimension is 0.");
+
+            m_outputWidth = 1;
+            m_outputHeight = rows;
+            m_outputChannels = 1;
+
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            m_deviceId = deviceId;
+            MoveMatricesToDevice(deviceId);
+            m_functionValues.Resize(rows, cols);
+            m_needGradient = false;
+            InitRecurrentNode();
+        }
+        
+        InputValue(size_t imageWidth, size_t imageHeight, size_t imageChannels, size_t numImages, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId) 
+        {
+            size_t rows = imageWidth * imageHeight * imageChannels;
+            size_t cols = numImages;
+
+            if (rows * cols == 0) 
+                throw std::logic_error("This InputValue dimension is 0.");
+
+            m_outputWidth = imageWidth;
+            m_outputHeight = imageHeight;
+            m_outputChannels = imageChannels;
+
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            m_deviceId = deviceId;
+            MoveMatricesToDevice(deviceId);
+            m_functionValues.Resize(rows, cols);
+            m_needGradient = false;
+            InitRecurrentNode();
+        }        
+
+        InputValue(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            LoadFromFile(fstream, modelVersion, deviceId);
+        }
+
+        virtual void SaveToFile(File& fstream) const
+        {
+            ComputationNode<ElemType>::SaveToFile(fstream);
+
+            fstream << FunctionValues().GetNumRows() << FunctionValues().GetNumCols(); 
+            fstream << m_outputWidth << m_outputHeight << m_outputChannels; 
+        }
+
+        virtual void LoadFromFile(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX)
+        {
+            ComputationNode<ElemType>::LoadFromFile(fstream, modelVersion, deviceId);
+
+            size_t rows, cols;
+            fstream >> rows >> cols;
+            if (rows * cols == 0) 
+                throw std::logic_error("This InputValue dimension is 0.");
+
+            fstream >> m_outputWidth >> m_outputHeight >> m_outputChannels; 
+
+            m_functionValues.Resize(rows, cols);
+            m_needGradient = false;
+        }
+
+        virtual const std::wstring OperationName() const {return TypeName();}
+        static const std::wstring TypeName() {return L"InputValue";} 
+
+        virtual void EvaluateThisNode()  {} 
+        virtual void EvaluateThisNode(const size_t /*timeIdxInSeq*/) {}
+        
+        virtual void ComputeInputPartial(const size_t /*inputIndex*/) {}
+        virtual void ComputeInputPartial(const size_t /*inputIndex*/, const size_t /*timeIdxInSeq*/) {}
+
+        virtual void Validate() 
+        {
+            PrintSelfBeforeValidation();
+            //CopyImageSizeFromInputs(); //not necessary since InputValue are leafs. put it here for consistent
+        }
+
+        virtual void DumpNodeInfo(const bool printValues, File& fstream) const
+        {
+            ComputationNode<ElemType>::DumpNodeInfo(printValues, fstream);
+
+            char str[4096];
+            sprintf(str, "[%lu,%lu]", FunctionValues().GetNumRows(), FunctionValues().GetNumCols());
+            fstream << string(str);        
+        }
+
+        // copy constructor
+        InputValue(const InputValue<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags) : ComputationNode<ElemType>(node->m_deviceId)
+        {
+            node->CopyTo(this, newName, flags);
+        }
+
+        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            const std::wstring& name = (newName == L"")?NodeName():newName;
+                
+            ComputationNodePtr node = new InputValue<ElemType>(this, name, flags);
+            return node;
+        }
+
+    };
+
+    template class InputValue<float>; 
+    template class InputValue<double>;
+
+    template<class ElemType>
+    class SparseInputValue : public InputValue<ElemType>
+    {
+        UsingComputationNodeMembers;
+    public:
+        SparseInputValue (size_t rows, size_t cols, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : InputValue<ElemType>(rows, cols, deviceId, name) 
+        {
+            ConvertToSparseMatrix();
+        }
+        
+        SparseInputValue (size_t imageWidth, size_t imageHeight, size_t imageChannels, size_t numImages, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") 
+            : InputValue<ElemType>(imageWidth, imageHeight, imageChannels, numImages, deviceId, name)
+        {
+                ConvertToSparseMatrix();
+        }
+
+        SparseInputValue (File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : InputValue<ElemType>(fstream, modelVersion, deviceId, name)
+        {
+            ConvertToSparseMatrix();
+        }
+
+        virtual void LoadFromFile(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX)
+        {
+            InputValue<ElemType>::LoadFromFile(fstream, modelVersion, deviceId);
+            ConvertToSparseMatrix();
+        }
+
+        virtual const std::wstring OperationName() const {return TypeName();}
+        static const std::wstring TypeName() {return L"SparseInputValue";} 
+
+        // copy constructor
+        SparseInputValue (const SparseInputValue <ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags) : InputValue<ElemType>(node, newName, flags)
+        {
+        }
+
+        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            const std::wstring& name = (newName == L"")?NodeName():newName;
+                
+            ComputationNodePtr node = new SparseInputValue<ElemType>(this, name, flags);
+            return node;
+        }
+
+    private:
+        void ConvertToSparseMatrix()
+        {
+            size_t rows = m_functionValues.GetNumRows();
+            size_t cols = m_functionValues.GetNumCols();
+            m_functionValues.SwitchToMatrixType(MatrixType::SPARSE, matrixFormatSparseCSC, false);
+            m_functionValues.Resize(rows, cols); //SwitchToMatrixType does not reserve information right now.
+        }
+
+    };
+
+
+    template class SparseInputValue<float>; 
+    template class SparseInputValue<double>;
+
+    //originally designed to extract word embedding representation from bag-of-word. 
+    //takes two inputs, input0 is weight matrix and input1 is the bag-of-word representation of the inputs
+    template<class ElemType>
+    class LookupTableNode : public ComputationNode<ElemType>
+    {
+        UsingComputationNodeMembers;
+    public:
+        LookupTableNode(const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            m_deviceId = deviceId;
+            MoveMatricesToDevice(deviceId);
+            InitRecurrentNode();
+        }
+
+        LookupTableNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            LoadFromFile(fstream, modelVersion, deviceId);
+        }
+
+        virtual const std::wstring OperationName() const {return TypeName();}
+        static const std::wstring TypeName() {return L"LookupTable";} 
+
+        virtual void ComputeInputPartial(const size_t inputIndex)
+        {
+            if (inputIndex > 1)
+                throw std::invalid_argument("LookupTable operation only takes two inputs.");
+
+            if (inputIndex == 0)  //left derivative
+            {
+                ComputeInputPartialLeft(Inputs(1)->FunctionValues(), Inputs(0)->GradientValues(), GradientValues());
+            }
+            else  //right derivative
+        {
+                ComputeInputPartialRight(Inputs(0)->FunctionValues(), Inputs(1)->GradientValues(), GradientValues());
+            }
+        }
+
+        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
+        {
+            if (inputIndex > 1)
+                throw std::invalid_argument("LookupTable operation only takes two inputs.");
+
+            if (inputIndex == 0)  //left derivative
+        {
+                Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+                Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+                ComputeInputPartialLeft(sliceInput1Value, Inputs(0)->GradientValues(), sliceOutputGrad);
+            }
+            else  //right derivative
+            {
+                Matrix<ElemType> sliceInput1Grad = Inputs(1)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+                Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+                ComputeInputPartialRight(Inputs(0)->FunctionValues(), sliceInput1Grad, sliceOutputGrad);
+            }
+        }
+
+        static void WINAPI ComputeInputPartialLeft(Matrix<ElemType>& inputFunctionValues, Matrix<ElemType>& inputGradientValues, Matrix<ElemType>& gradientValues)  
+        {
+            size_t rows1 =inputFunctionValues.GetNumRows(), cols1 = inputFunctionValues.GetNumCols();
+            size_t rowsp = gradientValues.GetNumRows(), colsp = gradientValues.GetNumCols();
+            int wordsInEachSample = rows1 / inputGradientValues.GetNumCols();
+
+            inputFunctionValues.Reshape(rows1 / wordsInEachSample, cols1 * wordsInEachSample);
+            gradientValues.Reshape(rowsp / wordsInEachSample, colsp * wordsInEachSample);
+
+            Matrix<ElemType>::MultiplyAndAdd(gradientValues, false, inputFunctionValues, true, inputGradientValues);
+
+            inputFunctionValues.Reshape(rows1, cols1);
+            gradientValues.Reshape(rowsp, colsp);
+        }
+
+        static void WINAPI ComputeInputPartialRight(Matrix<ElemType>& inputFunctionValues, Matrix<ElemType>& inputGradientValues, Matrix<ElemType>& gradientValues)  
+            {
+            size_t rows1 =inputGradientValues.GetNumRows(), cols1 = inputGradientValues.GetNumCols();
+            size_t rowsp = gradientValues.GetNumRows(), colsp = gradientValues.GetNumCols();
+            int wordsInEachSample = rows1 / inputFunctionValues.GetNumCols();
+
+            inputGradientValues.Reshape(rows1 / wordsInEachSample, cols1 * wordsInEachSample);
+            gradientValues.Reshape(rowsp / wordsInEachSample, colsp * wordsInEachSample);
+
+            Matrix<ElemType>::MultiplyAndAdd(inputFunctionValues, true, gradientValues, false, inputGradientValues);
+
+            inputGradientValues.Reshape(rows1, cols1);
+            gradientValues.Reshape(rowsp, colsp);
+        }
+
+        virtual void EvaluateThisNode()
+        {
+            EvaluateThisNodeS(FunctionValues(), Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues());
+        }
+
+        virtual void EvaluateThisNode(const size_t timeIdxInSeq) 
+        {
+            Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            EvaluateThisNodeS(sliceOutputValue, Inputs(0)->FunctionValues(), sliceInput1Value);
+        }
+
+        //input0 is the weight (each column is an embedding of one word), input 1 contains m_bnrLooked words in each column (sample)
+        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, const Matrix<ElemType>& input0, Matrix<ElemType>& input1)  
+        {
+            size_t rows1 =input1.GetNumRows(), cols1 = input1.GetNumCols();
+            int wordsInEachSample = rows1 / input0.GetNumCols();
+
+            input1.Reshape(rows1 / wordsInEachSample, cols1 * wordsInEachSample);
+
+            functionValues.AssignProductOf(input0, false, input1, false);
+
+            input1.Reshape(rows1, cols1);
+            size_t rows = functionValues.GetNumRows();
+            functionValues.Reshape(rows * wordsInEachSample, cols1);
+        }
+            
+        virtual void Validate()
+        {
+            PrintSelfBeforeValidation();
+
+            if (Inputs(1)->FunctionValues().GetNumRows() % Inputs(0)->FunctionValues().GetNumCols() != 0)
+                throw invalid_argument("Mismatched dimention. rows in input1 must be multiples of cols in input0.");
+
+            int wordsInEachSample = Inputs(1)->FunctionValues().GetNumRows() / Inputs(0)->FunctionValues().GetNumCols();
+          
+            FunctionValues().Resize(Inputs(0)->FunctionValues().GetNumRows() * wordsInEachSample, Inputs(1)->FunctionValues().GetNumCols());
+
+            CopyImageSizeFromInputs(); 
+        }
+
+        virtual void AttachInputs(const ComputationNodePtr leftNode, const ComputationNodePtr rightNode) 
+        {
+            m_children.resize(2);
+            m_children[0] = leftNode;
+            m_children[1] = rightNode;
+        }
+
+        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            const std::wstring& name = (newName == L"")?NodeName():newName;
+            ComputationNodePtr node = new LookupTableNode<ElemType>(this, name, flags);
+            return node;
+        }
+
+        LookupTableNode(const LookupTableNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags) : ComputationNode<ElemType>(node->m_deviceId)
+        {
+            node->CopyTo(this, newName, flags);
+        }
+    };
+
+    template class LookupTableNode<float>;
+    template class LookupTableNode<double>;
+
+}}}
diff --git a/MachineLearning/CNTK/LinearAlgebraNodes.h b/MachineLearning/CNTK/LinearAlgebraNodes.h
new file mode 100644
index 000000000..eb3ecc8bc
--- /dev/null
+++ b/MachineLearning/CNTK/LinearAlgebraNodes.h
@@ -0,0 +1,2360 @@
+//
+// <copyright file="LinearAlgebraNodes.h" company="Microsoft">
+//     Copyright (c) Microsoft Corporation.  All rights reserved.
+// </copyright>
+//
+#pragma once
+
+#include <unordered_set>
+#include <map>
+#include <string>
+#include <vector>
+#include <stdexcept>
+#include <list>
+#include <memory>
+#include <algorithm>
+#include <assert.h>
+#include <atomic>
+#include <sstream>
+#include <iostream>
+
+#include "Basics.h"
+#include "Matrix.h"
+#include "ComputationNode.h"
+
+namespace Microsoft { namespace MSR { namespace CNTK {
+
+    template<class ElemType>
+    class NegateNode : public ComputationNode<ElemType>
+    {
+        UsingComputationNodeMembers;
+    public:
+        NegateNode(const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)  
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            m_deviceId = deviceId;
+            MoveMatricesToDevice(deviceId);
+            InitRecurrentNode();
+        }
+
+        NegateNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            LoadFromFile(fstream, modelVersion, deviceId);
+        }
+
+        // copy constructor
+        NegateNode(const NegateNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags) : ComputationNode<ElemType>(node->m_deviceId)
+        {
+            node->CopyTo(this, newName, flags);
+        }
+
+        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            const std::wstring& name = (newName == L"")?NodeName():newName;
+                
+            ComputationNodePtr node = new NegateNode<ElemType>(this, name, flags);
+            return node;
+        }
+
+        virtual const std::wstring OperationName() const {return TypeName();}
+        static const std::wstring TypeName() {return L"Negate";} 
+
+        virtual void ComputeInputPartial(const size_t inputIndex)
+        {
+            if (inputIndex != 0)
+                throw std::invalid_argument("Negate operation only has one input.");
+            ComputeInputPartialS(Inputs(0)->GradientValues(), GradientValues());
+        }
+
+        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
+        {
+            if (inputIndex != 0)
+                throw std::invalid_argument("Negate operation only has one input.");
+
+            Matrix<ElemType> sliceInputGrad = Inputs(0)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            ComputeInputPartialS(sliceInputGrad, sliceOutputGrad);
+        }
+
+        static void WINAPI ComputeInputPartialS(Matrix<ElemType>& childGradientValues, const Matrix<ElemType>& gradientValues)
+        {
+            childGradientValues -= gradientValues;
+        }
+
+        virtual void EvaluateThisNode()  
+        {
+            EvaluateThisNodeS(m_functionValues, Inputs(0)->FunctionValues());
+        }
+
+        virtual void EvaluateThisNode(const size_t timeIdxInSeq) 
+        {
+            Matrix<ElemType> sliceInputValue = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            EvaluateThisNodeS(sliceOutputValue, sliceInputValue);
+        }
+
+        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, const Matrix<ElemType>& input)  
+        {
+            functionValues.AssignDifferenceOf(0, input);
+#if NANCHECK
+            functionValues.HasNan("Negate");
+#endif
+        }
+
+        virtual void Validate()
+        {
+            PrintSelfBeforeValidation();
+
+            if (m_children.size() != 1) 
+                throw std::logic_error("Negate operation should have one input.");
+
+            if (Inputs(0)->FunctionValues().GetNumElements() == 0)
+                throw std::logic_error("Negate operation: the input node has 0 element.");
+
+            FunctionValues().Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(0)->FunctionValues().GetNumCols());
+            
+            CopyImageSizeFromInputs(); 
+        }
+
+        virtual void AttachInputs(const ComputationNodePtr singleInput) 
+        {
+            m_children.resize(1);
+            m_children[0] = singleInput;
+        }
+    };
+
+    template class NegateNode<float>; 
+    template class NegateNode<double>;
+
+    template<class ElemType>
+    class SumElementsNode : public ComputationNode<ElemType>
+    {
+        UsingComputationNodeMembers;
+    public:
+        SumElementsNode(const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)  
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            m_deviceId = deviceId;
+            MoveMatricesToDevice(deviceId);
+            InitRecurrentNode();
+        }
+
+        SumElementsNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            LoadFromFile(fstream, modelVersion, deviceId);
+        }
+
+        // copy constructor
+        SumElementsNode(const SumElementsNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags) : ComputationNode<ElemType>(node->m_deviceId)
+        {
+            node->CopyTo(this, newName, flags);
+        }
+
+        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            const std::wstring& name = (newName == L"")?NodeName():newName;
+                
+            ComputationNodePtr node = new SumElementsNode<ElemType>(this, name, flags);
+            return node;
+        }
+
+        virtual const std::wstring OperationName() const {return TypeName();}
+        static const std::wstring TypeName() {return L"SumElements";} 
+
+        virtual void ComputeInputPartial(const size_t inputIndex)
+        {
+            if (inputIndex != 0)
+                throw std::invalid_argument("SumElements only has one input.");
+            ComputeInputPartialS(Inputs(0)->GradientValues(), GradientValues());
+        }
+
+        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
+        {
+            if (inputIndex != 0)
+                throw std::invalid_argument("SumElements only has one input.");
+
+            Matrix<ElemType> sliceInputGrad = Inputs(0)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            ComputeInputPartialS(sliceInputGrad, sliceOutputGrad);
+        }
+
+        static void WINAPI ComputeInputPartialS(Matrix<ElemType>& inputGradientValues, const Matrix<ElemType>& gradientValues)  
+        {
+            inputGradientValues += gradientValues; //here the assumption is that gradientValues are 1x1 matrix
+        }
+
+        virtual void EvaluateThisNode()  
+        {
+            EvaluateThisNodeS(m_functionValues, Inputs(0)->FunctionValues());
+        }
+
+        virtual void EvaluateThisNode(const size_t timeIdxInSeq)
+        {
+            Matrix<ElemType> sliceInputValue = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            EvaluateThisNodeS(sliceOutputValue, sliceInputValue);
+        }
+
+        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, const Matrix<ElemType>& inputFunctionValues)  
+        {
+            functionValues.AssignSumOfElements(inputFunctionValues);
+#if NANCHECK
+            functionValues.HasNan("SumElements");
+#endif
+        }
+
+        virtual void Validate()
+        {
+            PrintSelfBeforeValidation();
+
+            if (m_children.size() != 1) 
+                throw std::logic_error("SumElements operation should have one input.");
+
+            if (Inputs(0)->FunctionValues().GetNumElements() == 0)
+                throw std::logic_error("SumElements operation: the input node has 0 element.");
+
+            FunctionValues().Resize(1, 1);
+            CopyImageSizeFromInputs(); 
+        }
+
+        virtual void CopyImageSizeFromInputs()
+        {
+            CopyImageSizeFromInput(0, false);
+
+            m_outputWidth = 1;
+            m_outputHeight = 1;        
+            m_outputChannels = 1;
+        }
+
+        virtual void AttachInputs(const ComputationNodePtr singleInput) 
+        {
+            m_children.resize(1);
+            m_children[0] = singleInput;
+        }
+    };
+
+    template class SumElementsNode<float>; 
+    template class SumElementsNode<double>;
+
+    //this node is used to extract part of the input by rows as the output
+    //it has to be continuous segments of rows since each column is treated as one sample
+    template<class ElemType>
+    class RowSliceNode : public ComputationNode<ElemType>
+    {
+        UsingComputationNodeMembers;
+    public:
+        RowSliceNode(const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId), m_startIndex(0), m_numRows (0) 
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            m_deviceId = deviceId;
+            MoveMatricesToDevice(deviceId);
+            InitRecurrentNode();
+        }
+
+        RowSliceNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            LoadFromFile(fstream, modelVersion, deviceId);
+        }
+
+        // copy constructor
+        RowSliceNode(const RowSliceNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags) : ComputationNode<ElemType>(node->m_deviceId)
+        {
+            node->CopyTo(this, newName, flags);
+        }
+        
+        RowSliceNode(const DEVICEID_TYPE deviceId, size_t start_index, size_t num_rows, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)  
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            m_deviceId = deviceId;
+            m_startIndex = start_index;
+            m_numRows = num_rows;
+            
+
+            MoveMatricesToDevice(deviceId);
+            InitRecurrentNode();
+        }
+
+        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            const std::wstring& name = (newName == L"")?NodeName():newName;
+                
+            ComputationNodePtr node = new RowSliceNode<ElemType>(this, name, flags);
+            return node;
+        }
+
+        virtual void CopyTo(const ComputationNodePtr nodeP, const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            ComputationNode<ElemType>::CopyTo(nodeP, newName, flags);
+            RowSliceNode<ElemType>* node = (RowSliceNode<ElemType>*) nodeP;
+
+            node->m_startIndex = m_startIndex;
+            node->m_numRows = m_numRows;
+        }
+
+        virtual void SaveToFile(File& fstream) const
+        {
+            ComputationNode<ElemType>::SaveToFile(fstream);
+
+            fstream << m_startIndex << m_numRows;
+        }
+        
+        virtual void LoadFromFile(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX)
+        {
+            ComputationNode<ElemType>::LoadFromFile(fstream, modelVersion, deviceId);
+
+            fstream >> m_startIndex >> m_numRows;
+        }
+
+        virtual const std::wstring OperationName() const {return TypeName();}
+        static const std::wstring TypeName() {return L"RowSlice";} 
+
+        virtual void PrintSelfBeforeValidation(bool allowNulls = false) const
+        {
+            fprintf(stderr, "\nValidating --> %ls = %ls", NodeName().c_str(), OperationName().c_str());
+
+            if (!IsLeaf())
+            {
+                fprintf(stderr, "(");
+                for (size_t i = 0; i<ChildrenSize(); i++)
+                {
+                    ComputationNodePtr child = Inputs(i);
+                    if (i > 0)
+                        fprintf(stderr, ", ");
+
+                    if (child == nullptr)
+                    {
+                        if (allowNulls)
+                        {
+                            fprintf(stderr, "NULL");
+                            continue;
+                        }
+                        throw runtime_error("One of the children is missing.");
+                    }
+
+                    fprintf(stderr, "%ls[%lu, %lu]", child->NodeName().c_str(), child->FunctionValues().GetNumRows(), child->FunctionValues().GetNumCols());
+
+                }
+                fprintf(stderr, ", StartIndex=%lu, NumOfRows=%lu)", m_startIndex, m_numRows);
+            }
+        }
+
+        virtual void ComputeInputPartial(const size_t inputIndex)
+        {
+            if (inputIndex != 0)
+                throw std::invalid_argument("RowSlice only has one input.");
+
+            ComputeInputPartialS(Inputs(0)->GradientValues(), GradientValues(), m_startIndex, m_numRows);
+        }
+
+        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
+        {
+            if (inputIndex != 0)
+                throw std::invalid_argument("RowSlice only has one input.");
+
+            Matrix<ElemType> sliceInputGrad = Inputs(0)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            ComputeInputPartialS(sliceInputGrad, sliceOutputGrad, m_startIndex, m_numRows);
+        }
+
+        static void WINAPI ComputeInputPartialS(Matrix<ElemType>& inputGradientValues, const Matrix<ElemType>& gradientValues, const size_t startIndex, const size_t numRows)  
+        {
+            inputGradientValues.AddToRowSliceValuesOf(gradientValues, startIndex, numRows); 
+        }
+
+        virtual void EvaluateThisNode()  
+        {
+            EvaluateThisNodeS(m_functionValues, Inputs(0)->FunctionValues(), m_startIndex, m_numRows);
+        }
+
+        virtual void EvaluateThisNode(const size_t timeIdxInSeq)
+        {
+            Matrix<ElemType> sliceInputValue = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            EvaluateThisNodeS(sliceOutputValue, sliceInputValue, m_startIndex, m_numRows);
+        }
+
+        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, const Matrix<ElemType>& inputFunctionValues, const size_t startIndex, const size_t numRows)  
+        {
+            functionValues.AssignRowSliceValuesOf(inputFunctionValues, startIndex, numRows);
+#if NANCHECK
+            functionValues.HasNan("RowSlice");
+#endif
+        }
+
+        virtual void Validate()
+        {
+            PrintSelfBeforeValidation();
+
+            if (m_children.size() != 1) 
+                throw std::logic_error("RowSlice operation should have one input.");
+
+            if (Inputs(0)->FunctionValues().GetNumElements() == 0)
+                throw std::logic_error("RowSlice operation: the input node has 0 element.");
+
+            if (Inputs(0)->FunctionValues().GetNumRows() < m_startIndex + m_numRows)
+                throw std::logic_error("RowSlice operation: m_startIndex + m_numRows exceeds number of rows in the input.");
+
+            FunctionValues().Resize(m_numRows, Inputs(0)->FunctionValues().GetNumCols());
+            CopyImageSizeFromInputs(); 
+        }
+
+        virtual void CopyImageSizeFromInputs()
+        {
+            CopyImageSizeFromInput(0, true);
+            m_outputHeight = m_numRows;        
+
+            //WARNING: this node will destroy the image size information from the child
+            if (m_inputWidth * m_inputChannels != 1)
+                fprintf(stderr, "WARNING: RowSlice operation cannot inherit image size information from its child. Image size info is lost.\n");
+        }
+
+        virtual void AttachInputs(const ComputationNodePtr singleInput) 
+        {
+            m_children.resize(1);
+            m_children[0] = singleInput;
+        }
+
+    private:
+        size_t m_startIndex, m_numRows;
+    };
+
+    template class RowSliceNode<float>; 
+    template class RowSliceNode<double>;
+
+    template<class ElemType>
+    class ScaleNode : public ComputationNode<ElemType>
+    {
+        UsingComputationNodeMembers;
+    public:
+        ScaleNode(const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)  
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            m_deviceId = deviceId;
+            MoveMatricesToDevice(deviceId);
+            InitRecurrentNode();
+        }
+
+        ScaleNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            LoadFromFile(fstream, modelVersion, deviceId);
+        }
+
+        // copy constructor
+        ScaleNode(const ScaleNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags) : ComputationNode<ElemType>(node->m_deviceId)
+        {
+            node->CopyTo(this, newName, flags);
+        }
+
+        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            const std::wstring& name = (newName == L"")?NodeName():newName;
+                
+            ComputationNodePtr node = new ScaleNode<ElemType>(this, name, flags);
+            return node;
+        }
+
+        virtual const std::wstring OperationName() const {return TypeName();}
+        static const std::wstring TypeName() {return L"Scale";} 
+
+        virtual void ComputeInputPartial(const size_t inputIndex)
+        {
+            if (inputIndex > 1)
+                throw std::invalid_argument("ScaleNode operation only takes two inputs.");
+
+            //left Node must be a scalar
+            if (inputIndex == 0)  //left derivative
+            {
+                ComputeInputPartialLeft(Inputs(1)->FunctionValues(), Inputs(0)->GradientValues(), GradientValues());
+            }
+            else
+            {
+                ComputeInputPartialRight(Inputs(0)->FunctionValues(), Inputs(1)->GradientValues(), GradientValues());
+            }
+        }
+
+        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
+        {
+            if (inputIndex > 1)
+                throw std::invalid_argument("ScaleNode operation only takes two inputs.");
+
+            //left Node must be a scalar
+            if (inputIndex == 0)  //left derivative
+            {
+                Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+                Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+                ComputeInputPartialLeft(sliceInput1Value, Inputs(0)->GradientValues(), sliceOutputGrad);
+            }
+            else
+            {
+                Matrix<ElemType> sliceInput1Grad = Inputs(1)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+                Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+                ComputeInputPartialRight(Inputs(0)->FunctionValues(), sliceInput1Grad, sliceOutputGrad);
+            }
+        }
+
+        static void WINAPI ComputeInputPartialLeft(const Matrix<ElemType>& inputFunctionValues, Matrix<ElemType>& inputGradientValues, const Matrix<ElemType>& gradientValues)  
+        {
+            inputGradientValues += Matrix<ElemType>::InnerProductOfMatrices(gradientValues, inputFunctionValues);
+        }
+
+        static void WINAPI ComputeInputPartialRight(const Matrix<ElemType>& inputFunctionValues, Matrix<ElemType>& inputGradientValues, const Matrix<ElemType>& gradientValues)  
+        {
+            Matrix<ElemType>::ScaleAndAdd(inputFunctionValues.Get00Element(), gradientValues, inputGradientValues);
+        }
+
+        virtual void EvaluateThisNode()  
+        {
+            EvaluateThisNodeS(FunctionValues(), Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues());
+        }
+
+        virtual void EvaluateThisNode(const size_t timeIdxInSeq)  
+        {
+            Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            EvaluateThisNodeS(sliceOutputValue, Inputs(0)->FunctionValues(), sliceInput1Value);
+        }
+
+        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, const Matrix<ElemType>& input0, const Matrix<ElemType>& input1)  
+        {
+            functionValues.AssignProductOf(input0.Get00Element(), input1);
+#if NANCHECK
+            functionValues.HasNan("Scale");
+#endif
+        }
+
+        virtual void Validate()
+        {
+            PrintSelfBeforeValidation();
+
+            if (m_children.size() != 2) 
+                throw std::logic_error("Scale operation requires two inputs.");
+
+            if (Inputs(0)->FunctionValues().GetNumElements() == 0 || Inputs(1)->FunctionValues().GetNumElements() == 0)
+                throw std::logic_error("Scale operation: one of the operands has 0 element.");
+
+            if (Inputs(0)->FunctionValues().GetNumRows() != 1 || Inputs(0)->FunctionValues().GetNumCols() != 1)
+                throw std::logic_error("The left value of ScaleNode must be a scalar value.");
+
+            FunctionValues().Resize(Inputs(1)->FunctionValues().GetNumRows(), Inputs(1)->FunctionValues().GetNumCols());
+            //left Node must be a scalar
+            CopyImageSizeFromInputs(); 
+        }
+
+        virtual void CopyImageSizeFromInputs()
+        {
+            CopyImageSizeFromInput(1); 
+        }
+
+        virtual void AttachInputs(const ComputationNodePtr scalarValue, const ComputationNodePtr Value) 
+        {
+            m_children.resize(2);
+            m_children[0] = scalarValue;
+            m_children[1] = Value;
+        }
+    };
+
+    template class ScaleNode<float>; 
+    template class ScaleNode<double>;
+
+    template<class ElemType>
+    class TimesNode : public ComputationNode<ElemType>
+    {
+        UsingComputationNodeMembers;
+    public:
+        TimesNode(const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)  
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            m_deviceId = deviceId;
+            MoveMatricesToDevice(deviceId);
+            InitRecurrentNode();
+        }
+
+        TimesNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            LoadFromFile(fstream, modelVersion, deviceId);
+        }
+
+        // copy constructor
+        TimesNode(const TimesNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags) : ComputationNode<ElemType>(node->m_deviceId)
+        {
+            node->CopyTo(this, newName, flags);
+        }
+
+        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            const std::wstring& name = (newName == L"")?NodeName():newName;
+                
+            ComputationNodePtr node = new TimesNode<ElemType>(this, name, flags);
+            return node;
+        }
+
+        virtual const std::wstring OperationName() const {return TypeName();}
+        static const std::wstring TypeName() {return L"Times";} 
+
+        virtual void ComputeInputPartial(const size_t inputIndex)
+        {
+            if (inputIndex > 1)
+                throw std::invalid_argument("Times operation only takes two inputs.");
+
+            if (inputIndex == 0)  //left derivative
+            {
+                ComputeInputPartialLeft(Inputs(1)->FunctionValues(), Inputs(0)->GradientValues(), GradientValues());
+            }
+            else  //right derivative
+            {
+                ComputeInputPartialRight(Inputs(0)->FunctionValues(), Inputs(1)->GradientValues(), GradientValues());
+            }
+        }
+
+        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
+        {
+            if (inputIndex > 1)
+                throw std::invalid_argument("Times operation only takes two inputs.");
+
+            if (inputIndex == 0)  //left derivative
+            {
+                Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+                Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+                ComputeInputPartialLeft(sliceInput1Value, Inputs(0)->GradientValues(), sliceOutputGrad);
+            }
+            else  //right derivative
+            {
+                Matrix<ElemType> sliceInput1Grad = Inputs(1)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+                Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+                ComputeInputPartialRight(Inputs(0)->FunctionValues(), sliceInput1Grad, sliceOutputGrad);
+            }
+        }
+
+        static void WINAPI ComputeInputPartialLeft(Matrix<ElemType>& inputFunctionValues, Matrix<ElemType>& inputGradientValues, const Matrix<ElemType>& gradientValues)  
+            {
+#if DUMPOUTPUT
+            gradientValues.Print("Gradient-in");
+            inputGradientValues.Print("child Gradient-in/out");
+            inputFunctionValues.Print("child Function values");
+#endif
+            //currently we only support one combination when the input is sparse.
+            if (inputFunctionValues.GetMatrixType() == SPARSE && inputGradientValues.GetMatrixType() == DENSE && gradientValues.GetMatrixType() == DENSE)
+                inputGradientValues.SwitchToMatrixType(SPARSE, MatrixFormat::matrixFormatSparseBlockCol, false);
+
+                Matrix<ElemType>::MultiplyAndAdd(gradientValues, false, inputFunctionValues, true, inputGradientValues);
+#if DUMPOUTPUT
+            inputGradientValues.Print("child Gradient-out");
+#endif
+        }
+
+        static void WINAPI ComputeInputPartialRight(Matrix<ElemType>& inputFunctionValues, Matrix<ElemType>& inputGradientValues, const Matrix<ElemType>& gradientValues)  
+            {
+#if DUMPOUTPUT
+            gradientValues.Print("Gradient-in");
+            inputGradientValues.Print("child Gradient-in/out");
+            inputFunctionValues.Print("child Function values");
+#endif
+                Matrix<ElemType>::MultiplyAndAdd(inputFunctionValues, true, gradientValues, false, inputGradientValues);
+#if DUMPOUTPUT
+            inputGradientValues.Print("child Gradient-out");
+#endif
+        }
+
+
+        virtual void EvaluateThisNode()  
+        {
+            EvaluateThisNodeS(FunctionValues(), Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues());
+        }
+
+        virtual void EvaluateThisNode(const size_t timeIdxInSeq)  
+        {
+            Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            EvaluateThisNodeS(sliceOutputValue, Inputs(0)->FunctionValues(), sliceInput1Value);
+        }
+
+        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, const Matrix<ElemType>& input0, const Matrix<ElemType>& input1)  
+        {
+#if DUMPOUTPUT
+            input0.Print("TimesNode - Input0");
+#endif
+            functionValues.AssignProductOf(input0, false, input1, false);
+#if NANCHECK
+            functionValues.HasNan("Times");
+#endif
+#if DUMPOUTPUT
+            functionValues.Print("TimesNode");
+#endif
+        }
+
+        virtual void Validate()
+        {
+            PrintSelfBeforeValidation();
+
+            if (m_children.size() != 2) 
+                throw std::logic_error("Times operation requires two inputs.");
+
+            //support automatic dimention inference for learnable parameters
+            size_t rows0 = Inputs(0)->FunctionValues().GetNumRows(), cols0 = Inputs(0)->FunctionValues().GetNumCols();
+            size_t rows1 = Inputs(1)->FunctionValues().GetNumRows(), cols1 = Inputs(1)->FunctionValues().GetNumCols();
+
+            if ((rows0 == 0 || cols1 == 0 ) && this->LoopId() < 0)
+                throw logic_error("Times operation: Inputs(0)->FunctionValues().GetNumRows() and Inputs(1)->FunctionValues().GetNumCols() should not be 0 since it cannot be automatically inferred");
+
+            if ((Inputs(0)->OperationName() == LearnableParameter<ElemType>::TypeName() && cols0 == 0 && rows1 != 0) && this->LoopId() < 0)
+                Inputs(0)->FunctionValues().Resize(rows0, rows1);
+
+            if (Inputs(1)->OperationName() == LearnableParameter<ElemType>::TypeName() && cols0 != 0 && rows1 == 0)
+                Inputs(1)->FunctionValues().Resize(cols0, cols1);
+
+            if ((Inputs(0)->FunctionValues().GetNumElements() == 0 || Inputs(1)->FunctionValues().GetNumElements() == 0)&& this->LoopId() < 0)
+                throw std::logic_error("Times operation: One of the operants has 0 elements.");
+
+            //cols0 and rows1 may have been changed so don't use them in the following check
+            if ((Inputs(1)->FunctionValues().GetNumRows() != Inputs(0)->FunctionValues().GetNumCols()) && this->LoopId() < 0)
+            {
+                throw std::logic_error("The Matrix dimension in the Times operation does not match.");
+            }
+            FunctionValues().Resize(rows0, cols1);
+            CopyImageSizeFromInputs(); 
+        }
+
+        virtual void CopyImageSizeFromInputs()  
+        {
+            CopyImageSizeFromInput(1, false); //the second one is the input since it's column wize
+
+            //after multiplication the structure is lost
+            m_outputWidth = 1;
+            m_outputHeight = Inputs(0)->FunctionValues().GetNumRows();
+            m_outputChannels =  1;
+        }
+
+        virtual void AttachInputs(const ComputationNodePtr leftNode, const ComputationNodePtr rightNode) 
+        {
+            m_children.resize(2);
+            m_children[0] = leftNode;
+            m_children[1] = rightNode;
+        }
+    };
+
+    template class TimesNode<float>; 
+    template class TimesNode<double>;
+
+    template<class ElemType>
+    class ElementTimesNode : public ComputationNode<ElemType>
+    {
+        UsingComputationNodeMembers;
+    public:
+        ElementTimesNode(const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)  
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            m_deviceId = deviceId;
+            MoveMatricesToDevice(deviceId);
+            InitRecurrentNode();
+        }
+
+        ElementTimesNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            LoadFromFile(fstream, modelVersion, deviceId);
+        }
+
+        // copy constructor
+        ElementTimesNode(const ElementTimesNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags) : ComputationNode<ElemType>(node->m_deviceId)
+        {
+            node->CopyTo(this, newName, flags);
+        }
+
+        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            const std::wstring& name = (newName == L"")?NodeName():newName;
+                
+            ComputationNodePtr node = new ElementTimesNode<ElemType>(this, name, flags);
+            return node;
+        }
+
+        virtual const std::wstring OperationName() const {return TypeName();}
+        static const std::wstring TypeName() {return L"ElementTimes";} 
+
+        virtual void ComputeInputPartial(const size_t inputIndex)  
+        {
+            if (inputIndex > 1)
+                throw std::invalid_argument("ElementTimes operation only takes two inputs.");
+
+            ComputeInputPartialS(Inputs(1-inputIndex)->FunctionValues(), Inputs(inputIndex)->GradientValues(), GradientValues());
+        }
+
+        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)  
+        {
+            if (inputIndex > 1)
+                throw std::invalid_argument("ElementTimes operation only takes two inputs.");
+
+            Matrix<ElemType> sliceInput0Grad = Inputs(inputIndex)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            Matrix<ElemType> sliceInput1Value = Inputs(1-inputIndex)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            ComputeInputPartialS(sliceInput1Value, sliceInput0Grad, sliceOutputGrad);
+        }
+
+        // depending on inputIndex, all the input variables change meaning
+        // inputIndex == 0 (left) -  inputGradientValues[0], inputFunctionValues[1]
+        // inputIndex == 1 (right) - inputGradientValues[1], inputFunctionValues[0]
+        static void WINAPI ComputeInputPartialS(Matrix<ElemType>& inputFunctionValues, Matrix<ElemType>& inputGradientValues, const Matrix<ElemType>& gradientValues)  
+        {
+            inputGradientValues.AddElementProductOf(gradientValues, inputFunctionValues);
+#if NANCHECK
+            inputGradientValues.HasNan("ElementTimes");
+#endif
+        }
+
+
+        virtual void EvaluateThisNode()  
+        {
+            EvaluateThisNodeS(FunctionValues(), Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues());
+        }
+
+        virtual void EvaluateThisNode(const size_t timeIdxInSeq)  
+        {
+            Matrix<ElemType> sliceInput0Value = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            EvaluateThisNodeS(sliceOutputValue, sliceInput0Value, sliceInput1Value);
+        }
+
+        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, const Matrix<ElemType>& input0, const Matrix<ElemType>& input1)  
+        {
+            functionValues.AssignElementProductOf(input0, input1);
+#if NANCHECK
+            functionValues.HasNan("ElementTimes");
+#endif
+        }
+
+        virtual void Validate()
+        {
+            PrintSelfBeforeValidation();
+
+            if (m_children.size() != 2) 
+                throw std::logic_error("ElementTimes operation requires two inputs.");
+
+            size_t index = 0;
+            if (Inputs(index)->OperationName() == LearnableParameter<ElemType>::TypeName())
+            {
+                size_t rows = Inputs(index)->FunctionValues().GetNumRows() == 0? Inputs(1-index)->FunctionValues().GetNumRows() : Inputs(index)->FunctionValues().GetNumRows();
+                size_t cols = Inputs(index)->FunctionValues().GetNumCols() == 0? Inputs(1-index)->FunctionValues().GetNumCols() : Inputs(index)->FunctionValues().GetNumCols();
+                Inputs(index)->FunctionValues().Resize(rows, cols);
+            }
+
+            index = 1;
+            if (Inputs(index)->OperationName() == LearnableParameter<ElemType>::TypeName())
+            {
+                size_t rows = Inputs(index)->FunctionValues().GetNumRows() == 0? Inputs(1-index)->FunctionValues().GetNumRows() : Inputs(index)->FunctionValues().GetNumRows();
+                size_t cols = Inputs(index)->FunctionValues().GetNumCols() == 0? Inputs(1-index)->FunctionValues().GetNumCols() : Inputs(index)->FunctionValues().GetNumCols();
+                Inputs(index)->FunctionValues().Resize(rows, cols);
+            }
+
+            if (Inputs(0)->FunctionValues().GetNumElements() == 0 || Inputs(1)->FunctionValues().GetNumElements() == 0)
+                throw std::logic_error("ElementTimes operation: one of the operants has 0 element.");
+
+            if (Inputs(1)->FunctionValues().GetNumRows() != Inputs(0)->FunctionValues().GetNumRows() ||
+                Inputs(1)->FunctionValues().GetNumCols() != Inputs(0)->FunctionValues().GetNumCols())
+                throw std::logic_error("The Matrix<ElemType> dimension in the ElementTimes operation does not match.");
+
+            FunctionValues().Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(0)->FunctionValues().GetNumCols());
+            CopyImageSizeFromInputs(); 
+        }
+
+        virtual void CopyImageSizeFromInputs()
+        {
+            if (IsChildAnImage(0))  //when conflict, give priority to child 0
+                CopyImageSizeFromInput(0);
+            else
+                CopyImageSizeFromInput(1);
+        }
+
+        virtual void AttachInputs(const ComputationNodePtr leftNode, const ComputationNodePtr rightNode) 
+        {
+            m_children.resize(2);
+            m_children[0] = leftNode;
+            m_children[1] = rightNode;
+        }
+    };
+
+    template class ElementTimesNode<float>; 
+    template class ElementTimesNode<double>;
+
+    template<class ElemType>
+    class PlusNode : public ComputationNode<ElemType>
+    {
+        UsingComputationNodeMembers;
+    public:
+        PlusNode(const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)  
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            m_deviceId = deviceId;
+            MoveMatricesToDevice(deviceId);
+            InitRecurrentNode();
+        }
+
+        PlusNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            LoadFromFile(fstream, modelVersion, deviceId);
+        }
+
+        // copy constructor
+        PlusNode(const PlusNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags) : ComputationNode<ElemType>(node->m_deviceId)
+        {
+            node->CopyTo(this, newName, flags);
+        }
+
+        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            const std::wstring& name = (newName == L"")?NodeName():newName;
+                
+            ComputationNodePtr node = new PlusNode<ElemType>(this, name, flags);
+            return node;
+        }
+
+        virtual const std::wstring OperationName() const {return TypeName();}
+        static const std::wstring TypeName() {return L"Plus";} 
+
+        virtual void ComputeInputPartial(const size_t inputIndex)
+        {
+            if (inputIndex > 1)
+                throw std::invalid_argument("Plus operation only takes two inputs.");
+            ComputationNodePtr child = Inputs(inputIndex);
+            ComputeInputPartialS(FunctionValues(), GradientValues(), child->FunctionValues(), child->GradientValues());
+        }
+
+        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
+        {
+            if (inputIndex > 1)
+                throw std::invalid_argument("Plus operation only takes two inputs.");
+
+            //only the one with more columns can be sliced, if both have same columns both are sliced
+            size_t cols0 = Inputs(inputIndex)->FunctionValues().GetNumCols(), cols1=Inputs(1-inputIndex)->FunctionValues().GetNumCols();
+
+            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            if (cols0 >= cols1)
+            {
+                Matrix<ElemType> sliceInput0Grad = Inputs(inputIndex)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+                Matrix<ElemType> sliceInput0Value = Inputs(inputIndex)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+                ComputeInputPartialS(sliceOutputValue, sliceOutputGrad, sliceInput0Value, sliceInput0Grad);
+            }
+            else 
+            {
+                ComputeInputPartialS(sliceOutputValue, sliceOutputGrad, Inputs(inputIndex)->FunctionValues(), Inputs(inputIndex)->GradientValues());
+            }
+        }
+
+        static void WINAPI ComputeInputPartialS(Matrix<ElemType>& functionValues, Matrix<ElemType>& gradientValues, Matrix<ElemType>& inputFunctionValues, Matrix<ElemType>& inputGradientValues)
+        {
+#if DUMPOUTPUT
+
+            functionValues.Print("PlusNode");
+#endif
+
+            size_t rowsc = inputFunctionValues.GetNumRows(), colsc = inputFunctionValues.GetNumCols();
+            size_t rowsp = functionValues.GetNumRows(), colsp = functionValues.GetNumCols();
+#if DUMPOUTPUT
+            fprintf(stderr, "input dimensions %lld x %lld,  this node dimensions %lld x %lld\n", rowsc, colsc, rowsp, colsp);
+            gradientValues.Print("Gradient-in");
+            inputGradientValues.Print("child Gradient-in/out");
+#endif
+
+            if (colsc == colsp && rowsc == rowsp)
+                inputGradientValues += gradientValues;
+            else if (colsc == 1 && rowsc == 1)
+                inputGradientValues += gradientValues.SumOfElements();
+            else if (colsc == 1 && colsp != 1)
+            {
+                size_t colspExpand = rowsp*colsp/rowsc;
+                gradientValues.Reshape(rowsc, colspExpand);
+                Matrix<ElemType>::MultiplyAndAdd(gradientValues, false, ConstOnes(colspExpand, 1, functionValues.GetDeviceId()), false, inputGradientValues);
+                gradientValues.Reshape(rowsp, colsp);
+            }
+            else if (rowsc == 1 && rowsp != 1)
+                Matrix<ElemType>::MultiplyAndAdd(ConstOnes(1, rowsp,functionValues.GetDeviceId()), false, gradientValues, false, inputGradientValues);
+            else
+                throw std::runtime_error("Plus partial: unexpected condition.");
+#if DUMPOUTPUT
+            inputGradientValues.Print("child Gradient-out");
+#endif
+                }
+
+
+        virtual void EvaluateThisNode()  
+        {
+            EvaluateThisNodeS(FunctionValues(), Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues());
+        }
+
+        virtual void EvaluateThisNode(const size_t timeIdxInSeq)  
+        {
+            size_t cols0 = Inputs(0)->FunctionValues().GetNumCols(), cols1=Inputs(1)->FunctionValues().GetNumCols();
+
+            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            //only the one with more columns can be sliced, if both have same columns both are sliced
+            if (cols0 == cols1)
+            {
+                Matrix<ElemType> sliceInput0Value = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+                Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+                EvaluateThisNodeS(sliceOutputValue, sliceInput0Value, sliceInput1Value);
+            }
+            else if (cols0 > cols1)
+            {
+                Matrix<ElemType> sliceInput0Value = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+                EvaluateThisNodeS(sliceOutputValue, sliceInput0Value, Inputs(1)->FunctionValues());
+            }
+            else //cols0 < cols1)
+            {
+                Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+                EvaluateThisNodeS(sliceOutputValue, Inputs(0)->FunctionValues(), sliceInput1Value);
+            }
+        }
+
+        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, Matrix<ElemType>& inputFunctionValues0, Matrix<ElemType>& inputFunctionValues1)  
+        {
+            size_t rows0 = inputFunctionValues0.GetNumRows(), cols0 = inputFunctionValues0.GetNumCols();
+            size_t rows1 = inputFunctionValues1.GetNumRows(), cols1 = inputFunctionValues1.GetNumCols();
+            functionValues.Resize(max(rows0, rows1), max(cols0,cols1));
+
+            if ((rows0 == rows1 && cols0 == cols1) || ((rows0 == 1 || rows1 == 1) && cols0 == cols1))
+            {
+                functionValues.AssignSumOf(inputFunctionValues0, inputFunctionValues1);
+            }
+            else if (cols0 == 1 && rows1 % rows0 == 0)  //one is col vec with divisable rows, including scalar
+            {
+                inputFunctionValues1.Reshape(rows0, rows1 * cols1 / rows0);
+                functionValues.AssignSumOf(inputFunctionValues0, inputFunctionValues1);
+                inputFunctionValues1.Reshape(rows1, cols1);
+                functionValues.Reshape(max(rows0, rows1), max(cols0,cols1));
+            }
+            else if (cols1 == 1 && rows0 % rows1 == 0)  //one is col vec with divisable rows, including scalar
+            {
+                inputFunctionValues0.Reshape(rows1, rows0 * cols0 / rows1);
+                functionValues.AssignSumOf(inputFunctionValues0, inputFunctionValues1);
+                inputFunctionValues0.Reshape(rows0, cols0);
+                functionValues.Reshape(max(rows0, rows1), max(cols0,cols1));
+            }       
+
+#if NANCHECK
+            functionValues.HasNan("Plus");
+#endif
+#if DUMPOUTPUT
+            functionValues.Print("PlusNode");
+#endif
+        }
+
+        virtual void Validate()
+        {
+            PrintSelfBeforeValidation();
+
+            if (m_children.size() != 2) 
+                throw std::logic_error("Plus operation requires two inputs.");
+
+            //if dimention not specified we assume two operants' dimentions should be the same
+            size_t index = 0;
+            if (Inputs(index)->OperationName() == LearnableParameter<ElemType>::TypeName())
+            {
+                size_t rows = Inputs(index)->FunctionValues().GetNumRows() == 0? Inputs(1-index)->FunctionValues().GetNumRows() : Inputs(index)->FunctionValues().GetNumRows();
+                size_t cols = Inputs(index)->FunctionValues().GetNumCols() == 0? Inputs(1-index)->FunctionValues().GetNumCols() : Inputs(index)->FunctionValues().GetNumCols();
+                Inputs(index)->FunctionValues().Resize(rows, cols);
+            }
+
+            index = 1;
+            if (Inputs(index)->OperationName() == LearnableParameter<ElemType>::TypeName())
+            {
+                size_t rows = Inputs(index)->FunctionValues().GetNumRows() == 0? Inputs(1-index)->FunctionValues().GetNumRows() : Inputs(index)->FunctionValues().GetNumRows();
+                size_t cols = Inputs(index)->FunctionValues().GetNumCols() == 0? Inputs(1-index)->FunctionValues().GetNumCols() : Inputs(index)->FunctionValues().GetNumCols();
+                Inputs(index)->FunctionValues().Resize(rows, cols);
+            }
+
+            if ((Inputs(0)->FunctionValues().GetNumElements() == 0 || Inputs(1)->FunctionValues().GetNumElements() == 0) && this->LoopId() < 0)
+                throw std::logic_error("Plus operation: one of the operants has 0 element.");
+
+            size_t rows0 = Inputs(0)->FunctionValues().GetNumRows(), cols0 = Inputs(0)->FunctionValues().GetNumCols();
+            size_t rows1 = Inputs(1)->FunctionValues().GetNumRows(), cols1 = Inputs(1)->FunctionValues().GetNumCols();
+
+            if ((!(rows0 == rows1 && cols0 == cols1) &&  //match size
+                !((rows0 == 1 || rows1 == 1) && cols0 == cols1) && //one is row vec
+                !((cols0 == 1 && rows1 % rows0 == 0) || (cols1 == 1 && rows0 % rows1 == 0)))&& this->LoopId() < 0) //one is col vec with divisable rows, including scalar
+            {
+                throw std::logic_error("The Matrix dimension in the Plus operation does not match.");
+            }       
+
+            FunctionValues().Resize(max(rows0, rows1), max(cols0,cols1) );
+            CopyImageSizeFromInputs(); 
+        }
+
+        virtual void CopyImageSizeFromInputs() //based on the matrix with larger size
+        {
+            size_t rows0 = Inputs(0)->FunctionValues().GetNumRows(), cols0 = Inputs(0)->FunctionValues().GetNumCols();
+            size_t rows1 = Inputs(1)->FunctionValues().GetNumRows(), cols1 = Inputs(1)->FunctionValues().GetNumCols();
+
+            if (rows0 > rows1 || cols0 > cols1) //child 0 is larger
+                CopyImageSizeFromInput(0);
+            else if (rows0 < rows1 || cols0 < cols1) //child 1 is larger
+                CopyImageSizeFromInput(1);
+            else //same size
+            {
+                if (IsChildAnImage(0))  //when conflict, give priority to child 0
+                    CopyImageSizeFromInput(0);
+                else
+                    CopyImageSizeFromInput(1);
+            }
+        }
+
+        virtual void AttachInputs(const ComputationNodePtr leftNode, const ComputationNodePtr rightNode) 
+        {
+            m_children.resize(2);
+            m_children[0] = leftNode;
+            m_children[1] = rightNode;
+        }
+    };
+
+    template class PlusNode<float>; 
+    template class PlusNode<double>;
+
+    template<class ElemType>
+    class MinusNode : public ComputationNode<ElemType>
+    {
+        UsingComputationNodeMembers;
+    public:
+        MinusNode(const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)  
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            m_deviceId = deviceId;
+            MoveMatricesToDevice(deviceId);
+            InitRecurrentNode();
+        }
+
+        MinusNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            LoadFromFile(fstream, modelVersion, deviceId);
+        }
+
+        // copy constructor
+        MinusNode(const MinusNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags) : ComputationNode<ElemType>(node->m_deviceId)
+        {
+            node->CopyTo(this, newName, flags);
+        }
+
+        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            const std::wstring& name = (newName == L"")?NodeName():newName;
+                
+            ComputationNodePtr node = new MinusNode<ElemType>(this, name, flags);
+            return node;
+        }
+
+        virtual const std::wstring OperationName() const {return TypeName();}
+        static const std::wstring TypeName() {return L"Minus";}
+
+        virtual void ComputeInputPartial(const size_t inputIndex)
+        {
+            if (inputIndex > 1)
+                throw std::invalid_argument("Minus operation only takes two inputs.");
+
+            // prepare a matrix of ones as needed
+            ComputationNodePtr child = Inputs(inputIndex);
+            size_t rowsc = child->FunctionValues().GetNumRows(), colsc = child->FunctionValues().GetNumCols();
+            size_t rowsp = FunctionValues().GetNumRows(), colsp = FunctionValues().GetNumCols();
+
+            Matrix<ElemType> ones = Matrix<ElemType>();
+            if (colsc == 1 && colsp != 1)
+            {
+                size_t colspExpand = rowsp*colsp/rowsc;
+                ones = ConstOnes(colspExpand, 1,FunctionValues().GetDeviceId());
+            }
+            else if (rowsc == 1 && rowsp != 1)
+            {
+                ones = ConstOnes(1, rowsp,FunctionValues().GetDeviceId());
+            }
+
+            if (inputIndex == 0)  //left derivative
+            {
+                ComputeInputPartialLeft(child->FunctionValues(), child->GradientValues(), FunctionValues(), GradientValues(), ones); 
+            }
+            else  //right derivative
+        {
+                ComputeInputPartialRight(child->FunctionValues(), child->GradientValues(), FunctionValues(), GradientValues(), ones); 
+            }
+        }
+
+        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq) 
+        {
+            //only the one with more columns can be sliced, if both have same columns both are sliced
+            size_t cols0 = Inputs(inputIndex)->FunctionValues().GetNumCols(), cols1=Inputs(1-inputIndex)->FunctionValues().GetNumCols();
+
+            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            Matrix<ElemType> sliceInput0Grad = Inputs(inputIndex)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceInput0Value = Inputs(inputIndex)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            Matrix<ElemType> ones = Matrix<ElemType>();
+
+            size_t rowsc = Inputs(inputIndex)->FunctionValues().GetNumRows(), rowsp = FunctionValues().GetNumRows();
+            size_t colsp = FunctionValues().GetNumCols();
+
+            if (cols0 >= cols1) //indicates cols0 == functionValue.cols
+            {
+
+                if (rowsc == 1 && rowsp != 1)
+        {
+                    ones = ConstOnes(1, rowsp, FunctionValues().GetDeviceId());
+                }
+    
+                if (inputIndex == 0)  //left derivative
+            {
+                    ComputeInputPartialLeft(sliceInput0Value, sliceInput0Grad, sliceOutputValue, sliceOutputGrad, ones); 
+            }
+                else  //right derivativeAzqz
+            {
+                    ComputeInputPartialRight(sliceInput0Value, sliceInput0Grad, sliceOutputValue, sliceOutputGrad, ones); 
+            }
+            }
+            else // cols0 < cols1 -> cols0=1
+            {
+                if (cols0 == 1 && colsp != 1)
+                {
+                    size_t colspExpand = rowsp*colsp/rowsc;
+                    ones = ConstOnes(colspExpand, 1,FunctionValues().GetDeviceId());
+                }
+
+                if (inputIndex == 0)  //left derivative
+            {
+                    ComputeInputPartialLeft(sliceInput0Value, sliceInput0Grad, sliceOutputValue, sliceOutputGrad, ones); 
+                }
+                else  //right derivative
+                {
+                    ComputeInputPartialRight(sliceInput0Value, sliceInput0Grad, sliceOutputValue, sliceOutputGrad, ones); 
+                }
+            }
+        }
+
+        static void WINAPI ComputeInputPartialLeft(Matrix<ElemType>& childFunctionValues, Matrix<ElemType>& childGradientValues, const Matrix<ElemType>& functionValues, /*const*/ Matrix<ElemType>& gradientValues, /*const*/ Matrix<ElemType>& ones)
+            {
+            ComputeInputPartialS(0, childFunctionValues, childGradientValues, functionValues, gradientValues, ones);
+        }
+
+        static void WINAPI ComputeInputPartialRight(Matrix<ElemType>& childFunctionValues, Matrix<ElemType>& childGradientValues, const Matrix<ElemType>& functionValues, /*const*/ Matrix<ElemType>& gradientValues, /*const*/ Matrix<ElemType>& ones)  
+                {
+            ComputeInputPartialS(1, childFunctionValues, childGradientValues, functionValues, gradientValues, ones);
+        }
+
+        static void WINAPI ComputeInputPartialS(const size_t inputIndex, Matrix<ElemType>& childFunctionValues, Matrix<ElemType>& childGradientValues, const Matrix<ElemType>& functionValues, /*const*/ Matrix<ElemType>& gradientValues, /*const*/ Matrix<ElemType>& ones)
+        {
+            ElemType weight = ElemType(inputIndex == 0? 1:-1);
+            size_t rowsc = childFunctionValues.GetNumRows(), colsc = childFunctionValues.GetNumCols();
+            size_t rowsp = functionValues.GetNumRows(), colsp = functionValues.GetNumCols();
+
+            if (colsc == 1 && colsp != 1)
+            {
+                size_t colspExpand = rowsp*colsp/rowsc;
+                ones.Resize(colspExpand, 1);
+                }
+            else if (rowsc == 1 && rowsp != 1)
+            {
+                ones.Resize(1, rowsp);
+            }
+
+            if (colsc == colsp && rowsc == rowsp)
+            {
+                if (inputIndex == 0)
+                    childGradientValues += gradientValues;
+                else
+                    childGradientValues -= gradientValues;
+            }
+            else if (colsc == 1 && rowsc == 1)
+                {
+                if (inputIndex == 0)
+                    childGradientValues += gradientValues.SumOfElements();
+                else
+                    childGradientValues -= gradientValues.SumOfElements();
+                }
+            else if (colsc == 1 && colsp != 1)
+            {
+                size_t colspExpand = rowsp*colsp/rowsc;
+                gradientValues.Reshape(rowsc, colspExpand);
+                Matrix<ElemType>::MultiplyAndWeightedAdd(weight, gradientValues, false, ones, false, 1, childGradientValues);
+                gradientValues.Reshape(rowsp, colsp);
+            }
+            else if (rowsc == 1 && rowsp != 1)
+                Matrix<ElemType>::MultiplyAndWeightedAdd(weight, ones, false, gradientValues, false, 1, childGradientValues);
+            else
+                throw std::runtime_error("Minus partial: unexpected condition.");
+        }
+
+
+        virtual void EvaluateThisNode()  
+        {
+            EvaluateThisNodeS(FunctionValues(), Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues());  
+        }
+
+        virtual void EvaluateThisNode(const size_t timeIdxInSeq)
+        {
+            size_t cols0 = Inputs(0)->FunctionValues().GetNumCols(), cols1=Inputs(1)->FunctionValues().GetNumCols();
+
+            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            //only the one with more columns can be sliced, if both have same columns both are sliced
+            if (cols0 == cols1)
+            {
+                Matrix<ElemType> sliceInput0Value = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+                Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+                EvaluateThisNodeS(sliceOutputValue, sliceInput0Value, sliceInput1Value);
+            }
+            else if (cols0 > cols1)
+            {
+                Matrix<ElemType> sliceInput0Value = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+                EvaluateThisNodeS(sliceOutputValue, sliceInput0Value, Inputs(1)->FunctionValues());
+            }
+            else //cols0 < cols1)
+            {
+                Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+                EvaluateThisNodeS(sliceOutputValue, Inputs(0)->FunctionValues(), sliceInput1Value);
+            }
+        }
+
+        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, Matrix<ElemType>& in0, Matrix<ElemType>& in1)  
+        {
+            size_t rows0 = in0.GetNumRows(), cols0 = in0.GetNumCols();
+            size_t rows1 = in1.GetNumRows(), cols1 = in1.GetNumCols();
+            functionValues.Resize(max(rows0, rows1), max(cols0,cols1));
+
+            if ((rows0 == rows1 && cols0 == cols1) || ((rows0 == 1 || rows1 == 1) && cols0 == cols1))
+            {
+                functionValues.AssignDifferenceOf(in0, in1);
+            }
+            else if (cols0 == 1 && rows1 % rows0 == 0)  //one is col vec with divisable rows, including scalar
+            {
+                in1.Reshape(rows0, rows1 * cols1 / rows0);
+                functionValues.AssignDifferenceOf(in0, in1);
+                in1.Reshape(rows1, cols1);
+                functionValues.Reshape(max(rows0, rows1), max(cols0,cols1));
+            }
+            else if (cols1 == 1 && rows0 % rows1 == 0)  //one is col vec with divisable rows, including scalar
+            {
+                in0.Reshape(rows1, rows0 * cols0 / rows1);
+                functionValues.AssignDifferenceOf(in0, in1);
+                in0.Reshape(rows0, cols0);
+                functionValues.Reshape(max(rows0, rows1), max(cols0,cols1));
+            }      
+#if NANCHECK
+            functionValues.HasNan("Minus");
+#endif
+        }
+
+        virtual void Validate()
+        {
+            PrintSelfBeforeValidation();
+
+            if (m_children.size() != 2) 
+                throw std::logic_error("Minus operation requires two inputs.");
+
+            //if dimention is missing make the two operatants to have same size
+            size_t index = 0;
+            if (Inputs(index)->OperationName() == LearnableParameter<ElemType>::TypeName())
+            {
+                size_t rows = Inputs(index)->FunctionValues().GetNumRows() == 0? Inputs(1-index)->FunctionValues().GetNumRows() : Inputs(index)->FunctionValues().GetNumRows();
+                size_t cols = Inputs(index)->FunctionValues().GetNumCols() == 0? Inputs(1-index)->FunctionValues().GetNumCols() : Inputs(index)->FunctionValues().GetNumCols();
+                Inputs(index)->FunctionValues().Resize(rows, cols);
+            }
+
+            index = 1;
+            if (Inputs(index)->OperationName() == LearnableParameter<ElemType>::TypeName())
+            {
+                size_t rows = Inputs(index)->FunctionValues().GetNumRows() == 0? Inputs(1-index)->FunctionValues().GetNumRows() : Inputs(index)->FunctionValues().GetNumRows();
+                size_t cols = Inputs(index)->FunctionValues().GetNumCols() == 0? Inputs(1-index)->FunctionValues().GetNumCols() : Inputs(index)->FunctionValues().GetNumCols();
+                Inputs(index)->FunctionValues().Resize(rows, cols);
+            }
+
+            if (Inputs(0)->FunctionValues().GetNumElements() == 0 || Inputs(1)->FunctionValues().GetNumElements() == 0)
+                throw std::logic_error("Minus operation: one of the operants has 0 element.");
+
+            size_t rows0 = Inputs(0)->FunctionValues().GetNumRows(), cols0 = Inputs(0)->FunctionValues().GetNumCols();
+            size_t rows1 = Inputs(1)->FunctionValues().GetNumRows(), cols1 = Inputs(1)->FunctionValues().GetNumCols();
+
+            if (!(rows0 == rows1 && cols0 == cols1) &&  //match size
+                !((rows0 == 1 || rows1 == 1) && cols0 == cols1) && //one is row vec
+                !((cols0 == 1 && rows1 % rows0 == 0) || (cols1 == 1 && rows0 % rows1 == 0)))  //one is col vec with divisable rows, including scalar
+            {
+                throw std::logic_error("The Matrix dimension in the Minus operation does not match.");
+            }       
+
+            FunctionValues().Resize(max(rows0, rows1), max(cols0,cols1) );
+            CopyImageSizeFromInputs(); 
+        }
+
+        virtual void CopyImageSizeFromInputs() //based on the matrix with larger size
+        {
+            size_t rows0 = Inputs(0)->FunctionValues().GetNumRows(), cols0 = Inputs(0)->FunctionValues().GetNumCols();
+            size_t rows1 = Inputs(1)->FunctionValues().GetNumRows(), cols1 = Inputs(1)->FunctionValues().GetNumCols();
+
+            if (rows0 > rows1 || cols0 > cols1) //child 0 is larger
+                CopyImageSizeFromInput(0);
+            else if (rows0 < rows1 || cols0 < cols1) //child 1 is larger
+                CopyImageSizeFromInput(1);
+            else //same size
+            {
+                if (IsChildAnImage(0))  //when conflict, give priority to child 0
+                    CopyImageSizeFromInput(0);
+                else
+                    CopyImageSizeFromInput(1);
+            }
+        }
+
+        virtual void AttachInputs(const ComputationNodePtr leftNode, const ComputationNodePtr rightNode) 
+        {
+            m_children.resize(2);
+            m_children[0] = leftNode;
+            m_children[1] = rightNode;
+        }
+    };
+
+    template class MinusNode<float>; 
+    template class MinusNode<double>;
+
+    //The first matrix should be a vector regpresting the diagonal of a square matrix in the DiagTimes operation
+    template<class ElemType>
+    class DiagTimesNode : public ComputationNode<ElemType>
+    {
+        UsingComputationNodeMembers;
+    public:
+        DiagTimesNode(const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"")  
+            : ComputationNode<ElemType>(deviceId), m_innerproduct(deviceId), m_rightGradient(deviceId)
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            m_deviceId = deviceId;
+            MoveMatricesToDevice(deviceId);
+            InitRecurrentNode();
+        }
+
+        DiagTimesNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"")
+            : ComputationNode<ElemType>(deviceId), m_innerproduct(deviceId), m_rightGradient(deviceId)
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            LoadFromFile(fstream, modelVersion, deviceId);
+        }
+
+        virtual const std::wstring OperationName() const {return TypeName();}
+        static const std::wstring TypeName() {return L"DiagTimes";} 
+
+        virtual void ComputeInputPartial(const size_t inputIndex)
+        {
+            if (inputIndex > 1)
+                throw std::invalid_argument("DiagTimes operation only takes two inputs.");
+
+            if (inputIndex == 0)  //left derivative
+            {
+                ComputeInputPartialLeft(m_innerproduct, Inputs(1)->FunctionValues(), Inputs(0)->GradientValues(), GradientValues());
+            }
+            else  //right derivative
+            {
+                ComputeInputPartialRight(m_rightGradient, Inputs(0)->FunctionValues(), Inputs(1)->GradientValues(), GradientValues());
+            }
+        }
+
+        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
+        {
+            if (inputIndex > 1)
+                throw std::invalid_argument("DiagTimes operation only takes two inputs.");
+
+            //left parameter (diag matix cannot be sliced)
+            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            if (inputIndex == 0)  //left derivative
+            {
+                Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+                ComputeInputPartialLeft(m_innerproduct, sliceInput1Value, Inputs(0)->GradientValues(), sliceOutputGrad);
+            }
+            else  //right derivative
+            {
+                Matrix<ElemType> sliceInput1Grad = Inputs(1)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+                ComputeInputPartialRight(m_rightGradient, Inputs(0)->FunctionValues(), sliceInput1Grad, sliceOutputGrad);
+            }
+        }
+
+        static void WINAPI ComputeInputPartialLeft(Matrix<ElemType>& temp, const Matrix<ElemType>& inputFunctionValues, Matrix<ElemType>& inputGradientValues, const Matrix<ElemType>& gradientValues)  
+        {
+            temp.AssignInnerProductOf(gradientValues, inputFunctionValues, false);
+            inputGradientValues += temp;
+        }
+
+        static void WINAPI ComputeInputPartialRight(Matrix<ElemType>& temp, const Matrix<ElemType>& inputFunctionValues, Matrix<ElemType>& inputGradientValues, const Matrix<ElemType>& gradientValues)  
+        {
+            temp.SetValue(gradientValues);
+            temp.ColumnElementMultiplyWith(inputFunctionValues);
+            inputGradientValues += temp;
+        }
+
+
+        virtual void EvaluateThisNode()  
+        {
+            EvaluateThisNodeS(FunctionValues(), Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues()); 
+        }
+
+        virtual void EvaluateThisNode(const size_t timeIdxInSeq)  
+        {
+            Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            EvaluateThisNodeS(sliceOutputValue, Inputs(0)->FunctionValues(), sliceInput1Value); 
+        }
+
+        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, const Matrix<ElemType>& inputFunctionValues0, const Matrix<ElemType>& inputFunctionValues1)  
+        {
+            functionValues.SetValue(inputFunctionValues1);
+            functionValues.ColumnElementMultiplyWith(inputFunctionValues0);
+        }
+
+        virtual void Validate()
+        {
+            PrintSelfBeforeValidation();
+
+            if (m_children.size() != 2) 
+                throw std::logic_error("DiagTimes operation requires two inputs.");
+
+            //if dimention not specified we assume two operants' dimentions should match
+            if (Inputs(0)->OperationName() == LearnableParameter<ElemType>::TypeName() && Inputs(0)->FunctionValues().GetNumRows() == 0 && Inputs(1)->FunctionValues().GetNumRows() != 0)
+            {
+                Inputs(0)->FunctionValues().Resize(Inputs(1)->FunctionValues().GetNumRows(), 1);
+            }
+
+            if (Inputs(1)->OperationName() == LearnableParameter<ElemType>::TypeName() && Inputs(0)->FunctionValues().GetNumRows() != 0 && Inputs(1)->FunctionValues().GetNumRows() == 0)
+            {
+                Inputs(1)->FunctionValues().Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(1)->FunctionValues().GetNumCols());
+            }
+
+            if (Inputs(0)->FunctionValues().GetNumElements() == 0 || Inputs(1)->FunctionValues().GetNumElements() == 0)
+                throw std::logic_error("DiagTimes operation: one of the operants has 0 element.");
+
+            if (Inputs(1)->FunctionValues().GetNumRows() != Inputs(0)->FunctionValues().GetNumRows())
+                throw std::logic_error("The Matrix dimension in the DiagTimes operation does not match.");
+
+            if (1 != Inputs(0)->FunctionValues().GetNumCols())
+                throw std::logic_error("The first matrix should be a vector regpresting the diagonal of a square matrix in the DiagTimes operation.");
+
+            FunctionValues().Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(1)->FunctionValues().GetNumCols());
+            m_innerproduct.Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(1)->FunctionValues().GetNumCols());
+            m_rightGradient.Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(1)->FunctionValues().GetNumCols());
+
+            CopyImageSizeFromInputs(); 
+        }
+
+        virtual void CopyImageSizeFromInputs() //this is element wise scaling, so based on child 1
+        {
+            CopyImageSizeFromInput(1);
+        }
+
+        virtual void AttachInputs(const ComputationNodePtr leftNode, const ComputationNodePtr rightNode) 
+        {
+            m_children.resize(2);
+            m_children[0] = leftNode;
+            m_children[1] = rightNode;
+        }
+
+        virtual void MoveMatricesToDevice(const DEVICEID_TYPE deviceId)
+        {
+            ComputationNode<ElemType>::MoveMatricesToDevice(deviceId);
+
+            if (deviceId != AUTOPLACEMATRIX)
+            {
+                if (m_innerproduct.GetDeviceId() != deviceId)
+                    m_innerproduct.TransferFromDeviceToDevice(m_innerproduct.GetDeviceId(), deviceId);
+                if (m_rightGradient.GetDeviceId() != deviceId)
+                    m_rightGradient.TransferFromDeviceToDevice(m_rightGradient.GetDeviceId(), deviceId);
+            }
+        }
+
+        virtual void CopyTo(const ComputationNodePtr nodeP, const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            ComputationNode<ElemType>::CopyTo(nodeP, newName, flags);
+            DiagTimesNode<ElemType>* node = (DiagTimesNode<ElemType>*) nodeP;
+
+            if (flags & CopyNodeFlags::copyNodeValue)
+            {
+                node->m_innerproduct = m_innerproduct;
+                node->m_rightGradient = m_rightGradient;
+            }
+        }
+
+        // copy constructor
+        DiagTimesNode(const DiagTimesNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags)
+            : ComputationNode<ElemType>(node->m_deviceId), m_innerproduct(node->m_deviceId), m_rightGradient(node->m_deviceId)
+        {
+            node->CopyTo(this, newName, flags);
+        }
+
+        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            const std::wstring& name = (newName == L"")?NodeName():newName;
+                
+            ComputationNodePtr node = new DiagTimesNode<ElemType>(this, name, flags);
+            return node;
+        }
+
+    private:
+        Matrix<ElemType> m_innerproduct;
+        Matrix<ElemType> m_rightGradient;
+    };
+
+    template class DiagTimesNode<float>; 
+    template class DiagTimesNode<double>;
+
+    //The first matrix should be a vector regpresting the diagonal of a square matrix in the DiagTimes operation
+    template<class ElemType>
+    class CosDistanceNode : public ComputationNode<ElemType>
+    {
+        UsingComputationNodeMembers;
+    public:
+        CosDistanceNode(const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"")  
+            : ComputationNode<ElemType>(deviceId), m_invNorm0(deviceId), m_invNorm1(deviceId), m_leftTerm(deviceId), m_rightTerm(deviceId), m_temp(deviceId)
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            m_deviceId = deviceId;
+            MoveMatricesToDevice(deviceId);
+            InitRecurrentNode();
+        }
+
+        CosDistanceNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"")
+            : ComputationNode<ElemType>(deviceId), m_invNorm0(deviceId), m_invNorm1(deviceId), m_leftTerm(deviceId), m_rightTerm(deviceId), m_temp(deviceId)
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            LoadFromFile(fstream, modelVersion, deviceId);
+        }
+
+        virtual const std::wstring OperationName() const {return TypeName();}
+        static const std::wstring TypeName() {return L"CosDistance";} 
+
+        virtual void ComputeInputPartial(const size_t inputIndex)
+        {
+            if (inputIndex > 1)
+                throw std::invalid_argument("CosDistance operation only takes two inputs.");
+
+            if (inputIndex == 0)  //left derivative
+            {
+                ComputeInputPartialLeft(m_invNorm0, m_invNorm1, FunctionValues(), m_temp, m_rightTerm, m_leftTerm, Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues(), GradientValues(), Inputs(inputIndex)->GradientValues());
+            }
+            else  //right derivative
+            {
+                ComputeInputPartialRight(m_invNorm0, m_invNorm1, FunctionValues(), m_temp, m_rightTerm, m_leftTerm, Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues(), GradientValues(), Inputs(inputIndex)->GradientValues());
+            }
+        }
+
+        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq) 
+        {
+            if (inputIndex > 1)
+                throw std::invalid_argument("CosDistance operation only takes two inputs.");
+
+            Matrix<ElemType> sliceInput0Value = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceInputGrad = Inputs(inputIndex)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputGrad = this->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            if (inputIndex == 0)  //left derivative
+            {
+                ComputeInputPartialLeft(m_invNorm0, m_invNorm1, sliceOutputValue, m_temp, m_rightTerm, m_leftTerm, sliceInput0Value, sliceInput1Value, sliceOutputGrad, sliceInputGrad);
+            }
+            else  //right derivative
+            {
+                ComputeInputPartialRight(m_invNorm0, m_invNorm1, sliceOutputValue, m_temp, m_rightTerm, m_leftTerm, sliceInput0Value, sliceInput1Value, sliceOutputGrad, sliceInputGrad);
+            }
+        }
+
+        static void WINAPI ComputeInputPartialLeft(const Matrix<ElemType>& invNorm0, const Matrix<ElemType>& invNorm1, const Matrix<ElemType>& functionValues, 
+            Matrix<ElemType>& temp, Matrix<ElemType>& rightTerm, Matrix<ElemType>& leftTerm, // the temporary variables
+            const Matrix<ElemType>& in0, const Matrix<ElemType>& in1, const Matrix<ElemType>& gradientValues,
+            Matrix<ElemType>& inputGradientValues)
+        {
+            ComputeInputPartialS(0, invNorm0, invNorm1, functionValues, temp, rightTerm, leftTerm, in0, in1, gradientValues, inputGradientValues);
+        }
+
+        static void WINAPI ComputeInputPartialRight(const Matrix<ElemType>& invNorm0, const Matrix<ElemType>& invNorm1, const Matrix<ElemType>& functionValues, 
+            Matrix<ElemType>& temp, Matrix<ElemType>& rightTerm, Matrix<ElemType>& leftTerm, // the temporary variables
+            const Matrix<ElemType>& in0, const Matrix<ElemType>& in1, const Matrix<ElemType>& gradientValues,
+            Matrix<ElemType>& inputGradientValues)  
+        {
+            ComputeInputPartialS(1, invNorm0, invNorm1, functionValues, temp, rightTerm, leftTerm, in0, in1, gradientValues, inputGradientValues);  
+        }
+
+        // functionValues, invNorm0, invNorm1 - output from the EvaluateNode() method
+        // temp, rightTerm, leftTerm - temporary matrices
+        // in0, in1 - input functionValues from other nodes
+        // inputGradientValues(x) - gradients to update, where x matches inputIndex
+        static void WINAPI ComputeInputPartialS(const size_t inputIndex, const Matrix<ElemType>& invNorm0, const Matrix<ElemType>& invNorm1, const Matrix<ElemType>& functionValues, 
+            Matrix<ElemType>& temp, Matrix<ElemType>& rightTerm, Matrix<ElemType>& leftTerm, // the temporary variables
+            const Matrix<ElemType>& in0, const Matrix<ElemType>& in1, const Matrix<ElemType>& gradientValues,
+            Matrix<ElemType>& inputGradientValues)  
+        {
+            if (inputIndex == 0)  //left derivative
+            {
+                temp.AssignElementProductOf(invNorm0, invNorm0);
+            }
+            else  //right derivative
+            {
+                temp.AssignElementProductOf(invNorm1, invNorm1);
+            }
+
+            temp.ElementMultiplyWith(functionValues);
+            rightTerm.SetValue(inputIndex?in1:in0);
+            rightTerm.RowElementMultiplyWith(temp);
+
+            temp.AssignElementProductOf(invNorm0, invNorm1);
+            leftTerm.SetValue(inputIndex?in0:in1);
+            leftTerm.RowElementMultiplyWith(temp);
+
+            leftTerm -= rightTerm;
+            leftTerm.RowElementMultiplyWith(gradientValues);
+            inputGradientValues += leftTerm;
+            
+            //alternatively the above three lines can be replaced by
+            //leftTerm.RowElementMultiplyWith(gradientValues);
+            //rightTerm.RowElementMultiplyWith(gradientValues);
+            //Matrix<ElemType>::AddScaledDifference(1, leftTerm, rightTerm, inputGradientValues);
+        }
+
+        virtual void EvaluateThisNode()  
+        {
+            EvaluateThisNodeS(m_invNorm0, m_invNorm1, FunctionValues(), Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues());  
+        }
+
+        virtual void EvaluateThisNode(const size_t timeIdxInSeq) 
+        {
+            Matrix<ElemType> sliceInput0Value = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            EvaluateThisNodeS(m_invNorm0, m_invNorm1, sliceOutputValue, sliceInput0Value, sliceInput1Value);  
+        }
+
+        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& invNorm0, Matrix<ElemType>& invNorm1, 
+            Matrix<ElemType>& functionValues, Matrix<ElemType>& in0, Matrix<ElemType>& in1)  
+        {
+            invNorm0.AssignVectorNorm2Of(in0, true); // seems to modify input (in0)
+            invNorm0.AssignElementInverseOf(invNorm0);
+
+            invNorm1.AssignVectorNorm2Of(in1, true); // seems to modify the input (in1)
+            invNorm1.AssignElementInverseOf(invNorm1);
+
+            functionValues.AssignInnerProductOf(in0, in1, true);
+            functionValues.ElementMultiplyWith(invNorm0);
+            functionValues.ElementMultiplyWith(invNorm1);
+        }
+
+        virtual void Validate()
+        {
+            PrintSelfBeforeValidation();
+
+            if (m_children.size() != 2) 
+                throw std::logic_error("CosDistance operation requires two inputs.");
+
+            //if dimention is missing make the two operatants to have same size
+            size_t index = 0;
+            if (Inputs(index)->OperationName() == LearnableParameter<ElemType>::TypeName())
+            {
+                size_t rows = Inputs(index)->FunctionValues().GetNumRows() == 0? Inputs(1-index)->FunctionValues().GetNumRows() : Inputs(index)->FunctionValues().GetNumRows();
+                size_t cols = Inputs(index)->FunctionValues().GetNumCols() == 0? Inputs(1-index)->FunctionValues().GetNumCols() : Inputs(index)->FunctionValues().GetNumCols();
+                Inputs(index)->FunctionValues().Resize(rows, cols);
+            }
+
+            index = 1;
+            if (Inputs(index)->OperationName() == LearnableParameter<ElemType>::TypeName())
+            {
+                size_t rows = Inputs(index)->FunctionValues().GetNumRows() == 0? Inputs(1-index)->FunctionValues().GetNumRows() : Inputs(index)->FunctionValues().GetNumRows();
+                size_t cols = Inputs(index)->FunctionValues().GetNumCols() == 0? Inputs(1-index)->FunctionValues().GetNumCols() : Inputs(index)->FunctionValues().GetNumCols();
+                Inputs(index)->FunctionValues().Resize(rows, cols);
+            }
+
+            if (Inputs(0)->FunctionValues().GetNumElements() == 0 || Inputs(1)->FunctionValues().GetNumElements() == 0)
+                throw std::logic_error("CosDistance operation: one of the operants has 0 element.");
+
+            if (Inputs(1)->FunctionValues().GetNumRows() != Inputs(0)->FunctionValues().GetNumRows() || 
+                Inputs(1)->FunctionValues().GetNumCols() != Inputs(0)->FunctionValues().GetNumCols())
+                throw std::logic_error("The Matrix dimension in the CosDistance operation does not match.");
+
+            FunctionValues().Resize(1, Inputs(1)->FunctionValues().GetNumCols());
+
+            CopyImageSizeFromInputs(); 
+        }
+
+        virtual void CopyImageSizeFromInputs() 
+        {
+            CopyImageSizeFromInput(0, false);
+
+            m_outputChannels = 1;
+            m_outputWidth = 1;
+            m_outputHeight = 1;        
+        }
+
+        virtual void AttachInputs(const ComputationNodePtr leftNode, const ComputationNodePtr rightNode) 
+        {
+            m_children.resize(2);
+            m_children[0] = leftNode;
+            m_children[1] = rightNode;
+        }
+
+        virtual void MoveMatricesToDevice(const DEVICEID_TYPE deviceId)
+        {
+            ComputationNode<ElemType>::MoveMatricesToDevice(deviceId);
+
+            if (deviceId != AUTOPLACEMATRIX)
+            {
+                if (m_invNorm0.GetDeviceId() != deviceId)
+                    m_invNorm0.TransferFromDeviceToDevice(m_invNorm0.GetDeviceId(), deviceId);
+                if (m_invNorm1.GetDeviceId() != deviceId)
+                    m_invNorm1.TransferFromDeviceToDevice(m_invNorm1.GetDeviceId(), deviceId);
+                if (m_leftTerm.GetDeviceId() != deviceId)
+                    m_leftTerm.TransferFromDeviceToDevice(m_leftTerm.GetDeviceId(), deviceId);
+                if (m_rightTerm.GetDeviceId() != deviceId)
+                    m_rightTerm.TransferFromDeviceToDevice(m_rightTerm.GetDeviceId(), deviceId);
+                if (m_temp.GetDeviceId() != deviceId)
+                    m_temp.TransferFromDeviceToDevice(m_temp.GetDeviceId(), deviceId);
+            }
+        }
+
+        virtual void CopyTo(const ComputationNodePtr nodeP, const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            ComputationNode<ElemType>::CopyTo(nodeP, newName, flags);
+            CosDistanceNode<ElemType>* node = (CosDistanceNode<ElemType>*) nodeP;
+
+            if (flags & CopyNodeFlags::copyNodeValue)
+            {
+                node->m_invNorm0 = m_invNorm0;
+                node->m_invNorm1 = m_invNorm1;
+                node->m_leftTerm = m_leftTerm;
+                node->m_rightTerm = m_rightTerm;
+                node->m_temp = m_temp;
+            }
+        }
+
+        // copy constructor
+        CosDistanceNode(const CosDistanceNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags)
+            : ComputationNode<ElemType>(node->m_deviceId), m_invNorm0(node->m_deviceId), m_invNorm1(node->m_deviceId), m_leftTerm(node->m_deviceId), m_rightTerm(node->m_deviceId), m_temp(node->m_deviceId)
+        {
+            node->CopyTo(this, newName, flags);
+        }
+
+        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            const std::wstring& name = (newName == L"")?NodeName():newName;
+                
+            ComputationNodePtr node = new CosDistanceNode<ElemType>(this, name, flags);
+            return node;
+        }
+
+    private:
+        // invNorm nodes tranfer data between EvaluateThisNode and ComputeInputPartial
+        Matrix<ElemType> m_invNorm0;
+        Matrix<ElemType> m_invNorm1;
+        // the rest are temporaries, values don't need to be maintained
+        Matrix<ElemType> m_leftTerm;
+        Matrix<ElemType> m_rightTerm;
+        Matrix<ElemType> m_temp;
+    };
+
+    template class CosDistanceNode<float>; 
+    template class CosDistanceNode<double>;
+
+    template<class ElemType>
+    class KhatriRaoProductNode : public ComputationNode<ElemType>
+    {
+        UsingComputationNodeMembers;
+    public:
+        KhatriRaoProductNode(const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)  
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            m_deviceId = deviceId;
+            MoveMatricesToDevice(deviceId);
+            InitRecurrentNode();
+        }
+
+        KhatriRaoProductNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            LoadFromFile(fstream, modelVersion, deviceId);
+        }
+
+        // copy constructor
+        KhatriRaoProductNode(const KhatriRaoProductNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags) : ComputationNode<ElemType>(node->m_deviceId)
+        {
+            node->CopyTo(this, newName, flags);
+        }
+
+        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            const std::wstring& name = (newName == L"")?NodeName():newName;
+                
+            ComputationNodePtr node = new KhatriRaoProductNode<ElemType>(this, name, flags);
+            return node;
+        }
+
+        virtual const std::wstring OperationName() const {return TypeName();}
+        static const std::wstring TypeName() {return L"KhatriRaoProduct";} 
+
+        virtual void ComputeInputPartial(const size_t inputIndex)
+        {
+            if (inputIndex > 1)
+                throw std::invalid_argument("KhatriRaoProduct operation only takes two inputs.");
+
+            if (inputIndex == 0)  //left derivative
+            {
+                ComputeInputPartialLeft(Inputs(1)->FunctionValues(), Inputs(0)->GradientValues(), GradientValues()); 
+            }
+            else  //right derivative
+            {
+                ComputeInputPartialRight(Inputs(0)->FunctionValues(), Inputs(1)->GradientValues(), GradientValues()); 
+            }
+        }
+
+        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq) 
+        {
+            if (inputIndex > 1)
+                throw std::invalid_argument("KhatriRaoProduct operation only takes two inputs.");
+
+            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            if (inputIndex == 0)  //left derivative
+            {
+                Matrix<ElemType> sliceInput0Grad = Inputs(0)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+                Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+                ComputeInputPartialLeft(sliceInput1Value, sliceInput0Grad, sliceOutputGrad); 
+            }
+            else  //right derivative
+            {
+                Matrix<ElemType> sliceInput0Value = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+                Matrix<ElemType> sliceInput1Grad = Inputs(1)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+                ComputeInputPartialRight(sliceInput0Value, sliceInput1Grad, sliceOutputGrad); 
+            }
+        }
+
+        static void WINAPI ComputeInputPartialLeft(Matrix<ElemType>& childFunctionValues, Matrix<ElemType>& childGradientValues, const Matrix<ElemType>& gradientValues)
+        {
+            childGradientValues.AddColumnReshapeProductOf(gradientValues, childFunctionValues, false);
+        }
+
+        static void WINAPI ComputeInputPartialRight(Matrix<ElemType>& childFunctionValues, Matrix<ElemType>& childGradientValues, const Matrix<ElemType>& gradientValues)  
+        {
+            childGradientValues.AddColumnReshapeProductOf(gradientValues, childFunctionValues, true);
+        }
+
+        virtual void EvaluateThisNode()  
+        {
+            EvaluateThisNodeS(FunctionValues(), Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues());  
+        }
+
+        virtual void EvaluateThisNode(const size_t timeIdxInSeq)  
+        {
+            Matrix<ElemType> sliceInput0Value = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            EvaluateThisNodeS(sliceOutputValue, sliceInput0Value, sliceInput1Value); 
+        }
+
+        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, Matrix<ElemType>& in0, Matrix<ElemType>& in1)  
+        {
+            functionValues.AssignKhatriRaoProductOf(in0,in1);
+#if NANCHECK
+            functionValues.HasNan("KhatriRaoProduct");
+#endif
+        }
+
+        virtual void Validate()
+        {
+            PrintSelfBeforeValidation();
+
+            if (m_children.size() != 2) 
+                throw std::logic_error("KhatriRaoProduct operation requires two inputs.");
+
+            //support automatic dimention inference for learnable parameters
+            size_t rows0 = Inputs(0)->FunctionValues().GetNumRows(), cols0 = Inputs(0)->FunctionValues().GetNumCols();
+            size_t rows1 = Inputs(1)->FunctionValues().GetNumRows(), cols1 = Inputs(1)->FunctionValues().GetNumCols();
+
+            if (rows0 == 0 || rows1 == 0)
+                throw logic_error("KhatriRaoProduct operation: The number of rows in the input should not be 0.");
+
+            if (Inputs(0)->OperationName() == LearnableParameter<ElemType>::TypeName() && cols0 == 0 && cols1 != 0)
+                Inputs(0)->FunctionValues().Resize(rows0, cols1);
+
+            if (Inputs(1)->OperationName() == LearnableParameter<ElemType>::TypeName() && cols0 != 0 && cols1 == 0)
+                Inputs(1)->FunctionValues().Resize(rows1, cols0);
+
+            //cols may be changed before this line and so cannot use cached cols values below
+            if (Inputs(0)->FunctionValues().GetNumElements() == 0 || Inputs(1)->FunctionValues().GetNumElements() == 0)
+                throw std::logic_error("KhatriRaoProduct operation: One of the operants has 0 elements.");
+
+            if (Inputs(1)->FunctionValues().GetNumCols() != Inputs(0)->FunctionValues().GetNumCols())
+            {
+                throw std::logic_error("The Matrices should have same number of columns.");
+            }
+
+            FunctionValues().Resize(rows0 * rows1, Inputs(0)->FunctionValues().GetNumCols());
+            CopyImageSizeFromInputs(); 
+        }
+
+        virtual void CopyImageSizeFromInputs()  
+        {
+            //since it's symmetrical any one of the input may be the true input. 
+            //since we dont' use the input image size info in the operation, the input part doesn't matter.
+            CopyImageSizeFromInput(1, false); 
+
+            //after KhatriRaoProduct the structure is lost
+            m_outputWidth = 1;
+            m_outputHeight = m_functionValues.GetNumRows();
+            m_outputChannels = 1;
+        }
+
+        virtual void AttachInputs(const ComputationNodePtr leftNode, const ComputationNodePtr rightNode) 
+        {
+            m_children.resize(2);
+            m_children[0] = leftNode;
+            m_children[1] = rightNode;
+        }
+    };
+
+    template class KhatriRaoProductNode<float>; 
+    template class KhatriRaoProductNode<double>;
+
+    template<class ElemType>
+    class CosDistanceWithNegativeSamplesNode : public ComputationNode<ElemType>
+    {
+        //typedef ComputationNode<ElemType>* ComputationNodePtr;
+        UsingComputationNodeMembers;
+
+    public:
+        CosDistanceWithNegativeSamplesNode(const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX, const std::wstring name = L"")
+            : ComputationNode<ElemType>(deviceId), m_invNorm0(deviceId), m_invNorm1(deviceId), m_invNormSquare(deviceId), 
+            m_leftTerm(deviceId), m_rightTerm(deviceId), m_temp(deviceId)
+        {
+            m_nodeName = (name == L"" ? CreateUniqNodeName() : name);
+            m_deviceId = deviceId;
+            MoveMatricesToDevice(deviceId);
+            InitRecurrentNode();
+        }
+
+        CosDistanceWithNegativeSamplesNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX, const std::wstring name = L"")
+            : ComputationNode<ElemType>(deviceId), m_invNorm0(deviceId), m_invNorm1(deviceId), m_invNormSquare(deviceId), 
+            m_leftTerm(deviceId), m_rightTerm(deviceId), m_temp(deviceId)
+        {
+            m_nodeName = (name == L"" ? CreateUniqNodeName() : name);
+            LoadFromFile(fstream, modelVersion, deviceId);
+        }
+
+        virtual const std::wstring OperationName() const { return TypeName(); }
+        static const std::wstring TypeName() { return L"CosDistanceWithNegativeSamples"; }
+
+        virtual void ComputeInputPartial(const size_t inputIndex)
+        {
+            if (inputIndex > 1)
+                throw std::invalid_argument("CosDistanceWithNegativeSamples operation only takes grdients on the first two inputs.");
+
+            ComputeInputPartialS(inputIndex, m_invNorm0, m_invNorm1, FunctionValues(), m_temp, m_rightTerm, m_leftTerm, m_invNormSquare, Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues(), Inputs(2)->FunctionValues(), Inputs(3)->FunctionValues(), Inputs(inputIndex)->GradientValues(), GradientValues());
+        }
+
+        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
+        {
+            if (inputIndex > 1)
+                throw std::invalid_argument("CosDistanceWithNegativeSamples operation only takes grdients on the first two inputs.");
+
+            Matrix<ElemType> sliceInput0Value = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceInputGrad = Inputs(inputIndex)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceThisGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            ComputeInputPartialS(inputIndex, m_invNorm0, m_invNorm1, sliceOutputValue, m_temp, m_rightTerm, m_leftTerm, m_invNormSquare, sliceInput0Value, sliceInput1Value, Inputs(2)->FunctionValues(), Inputs(3)->FunctionValues(), sliceInputGrad, sliceThisGrad);
+        }
+
+        // functionValues, invNorm0, invNorm1 - output from the EvaluateNode() method
+        // temp, rightTerm, leftTerm - temporary matrices
+        // in0, in1, in2, in3 - input functionValues from other nodes
+        // inputGradientValues(x) - gradients to update, where x matches inputIndex
+        static void WINAPI ComputeInputPartialS(const size_t inputIndex, const Matrix<ElemType>& invNorm0, const Matrix<ElemType>& invNorm1, const Matrix<ElemType>& functionValues,
+            Matrix<ElemType>& temp, Matrix<ElemType>& rightTerm, Matrix<ElemType>& leftTerm, Matrix<ElemType>& invNormSquare, // the temporary variables
+            const Matrix<ElemType>& in0, const Matrix<ElemType>& in1, const Matrix<ElemType>& in2, const Matrix<ElemType>& in3,
+            Matrix<ElemType>& inputGradientValues, Matrix<ElemType>& thisGradientValues)
+        {
+            size_t shift = (size_t)in2.Get00Element();
+            size_t negNumber = (size_t)in3.Get00Element();
+            size_t numCols = in0.GetNumCols(); // used in computing right child's graident
+
+            if (inputIndex == 0) // left derivative
+            {
+                invNormSquare.AssignElementProductOf(invNorm0, invNorm0);
+
+                for (long m = 0; m < negNumber + 1; m++)
+                {
+                    temp.GetARowByIndex(functionValues, m); // set this matrx to be the m-th row in functionValues
+                    temp.ElementMultiplyWith(invNormSquare);
+
+                    Matrix<ElemType>::ConductRowElementMultiplyWithShift(temp, in0, rightTerm, 0, true);
+
+                    if (m == 0)
+                    {
+                        temp.AssignElementProductOf(invNorm0, invNorm1);
+
+                        Matrix<ElemType>::ConductRowElementMultiplyWithShift(temp, in1, leftTerm, 0, true);
+                    }
+                    else
+                    {
+                        size_t currshift = m + shift - 1;  // for current line, how much should we shift
+
+                        temp.AssignElementProductOfWithShift(invNorm0, invNorm1, currshift); // this is a row vector
+
+                        Matrix<ElemType>::ConductRowElementMultiplyWithShift(temp, in1, leftTerm, currshift, true);
+                    }
+
+                    leftTerm = leftTerm - rightTerm;
+
+                    temp.GetARowByIndex(thisGradientValues, m);
+
+                    Matrix<ElemType>::ConductRowElementMultiplyWithShift(temp, leftTerm, rightTerm, 0, true);
+
+                    inputGradientValues += rightTerm;
+                }
+            }
+            else // right part
+            {
+                invNormSquare.AssignElementProductOf(invNorm1, invNorm1);  //this matrix should be save and unchanged. It should not be changed
+
+                for (long m = 0; m < negNumber + 1; m++)
+                {
+                    temp.GetARowByIndex(functionValues, m); // set this matrx to be the m-th row in functionValues
+
+                    if (m == 0) // this is the first line. computation should be symmetric
+                    {
+                        // the following is for the right part
+                        temp.ElementMultiplyWith(invNormSquare);
+
+                        Matrix<ElemType>::ConductRowElementMultiplyWithShift(temp, in1, rightTerm, 0, true);
+
+                        // the following is for the left part
+                        temp.AssignElementProductOf(invNorm0, invNorm1);
+
+                        Matrix<ElemType>::ConductRowElementMultiplyWithShift(temp, in0, leftTerm, 0, true);
+
+                        leftTerm = leftTerm - rightTerm;
+
+                        temp.GetARowByIndex(thisGradientValues, m);
+
+                        Matrix<ElemType>::ConductRowElementMultiplyWithShift(temp, leftTerm, rightTerm, 0, true);
+
+                        inputGradientValues += rightTerm;
+                    }
+                    else // this requires shift
+                    {
+                        size_t currshift = (m + shift - 1) % numCols;
+                        size_t reverseshift = numCols - currshift;
+
+                        leftTerm.AssignElementProductOfWithShift(invNormSquare, temp, reverseshift);  //use leftTerm as a temp variable here
+
+                        Matrix<ElemType>::ConductRowElementMultiplyWithShift(leftTerm, in1, rightTerm, 0, true);
+
+                        temp.AssignElementProductOfWithShift(invNorm1, invNorm0, reverseshift);
+
+                        Matrix<ElemType>::ConductRowElementMultiplyWithShift(temp, in0, leftTerm, reverseshift, true);
+
+                        leftTerm = leftTerm - rightTerm;
+
+                        temp.GetARowByIndex(thisGradientValues, m);
+
+                        Matrix<ElemType>::ConductRowElementMultiplyWithShift(temp, leftTerm, rightTerm, reverseshift, false);
+
+                        inputGradientValues += rightTerm;
+                    }
+                }
+            }
+        }
+
+        virtual void EvaluateThisNode()
+        {
+            EvaluateThisNodeS(m_invNorm0, m_invNorm1, FunctionValues(), Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues(), Inputs(2)->FunctionValues(), Inputs(3)->FunctionValues(), m_leftTerm, m_rightTerm);
+        }
+
+        virtual void EvaluateThisNode(const size_t timeIdxInSeq)
+        {
+            Matrix<ElemType> sliceInput0Value = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceInput1Value = Inputs(1)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            EvaluateThisNodeS(m_invNorm0, m_invNorm1, sliceOutputValue, sliceInput0Value, sliceInput1Value, Inputs(2)->FunctionValues(), Inputs(3)->FunctionValues(), m_leftTerm, m_rightTerm);
+        }
+
+        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& invNorm0, Matrix<ElemType>& invNorm1,
+            Matrix<ElemType>& functionValues, Matrix<ElemType>& in0, Matrix<ElemType>& in1, Matrix<ElemType>& in2, Matrix<ElemType>& in3, Matrix<ElemType>& leftTermTemp, Matrix<ElemType>& rightTermTemp)
+        {
+            invNorm0.AssignVectorNorm2Of(in0, true); // seems to modify input (in0)
+            invNorm0.AssignElementInverseOf(invNorm0);
+
+            invNorm1.AssignVectorNorm2Of(in1, true); // seems to modify the input (in1)
+            invNorm1.AssignElementInverseOf(invNorm1);
+
+            size_t shift = (size_t)in2.Get00Element();
+            size_t negNumber = (size_t)in3.Get00Element();
+
+            // mutiply invNorm0 and invNorm1 with shift and neg. 
+            // The result is a matrix of (numberneg+1, invNorm0.Cols)
+            leftTermTemp.AssignElementProductOfWithShiftNeg(invNorm0, invNorm1, shift, negNumber);
+
+            // compute the right values
+            // Again, the ouput is a matrix of (negNumber+1, invNorm0.cols)
+            rightTermTemp.AssignInnerProductOfWithShiftNeg(in0, in1, true, shift, negNumber);
+
+            // compute the evaluation result matrix by multiply these two matrices, element by element
+            // we get a (negNumber+1, n) matrix
+            functionValues.AssignElementProductOf(leftTermTemp, rightTermTemp);
+        }
+
+        virtual void Validate()
+        {
+            PrintSelfBeforeValidation();
+
+            if (m_children.size() != 4)
+                throw std::logic_error("CosDistanceWithNegativeSamples operation requires 4 inputs.");
+
+            //if dimention is missing make the two operatants to have same size
+            size_t index = 0;
+            if (Inputs(index)->OperationName() == LearnableParameter<ElemType>::TypeName())
+            {
+                size_t rows = Inputs(index)->FunctionValues().GetNumRows() == 0 ? Inputs(1 - index)->FunctionValues().GetNumRows() : Inputs(index)->FunctionValues().GetNumRows();
+                size_t cols = Inputs(index)->FunctionValues().GetNumCols() == 0 ? Inputs(1 - index)->FunctionValues().GetNumCols() : Inputs(index)->FunctionValues().GetNumCols();
+                Inputs(index)->FunctionValues().Resize(rows, cols);
+            }
+
+            index = 1;
+            if (Inputs(index)->OperationName() == LearnableParameter<ElemType>::TypeName())
+            {
+                size_t rows = Inputs(index)->FunctionValues().GetNumRows() == 0 ? Inputs(1 - index)->FunctionValues().GetNumRows() : Inputs(index)->FunctionValues().GetNumRows();
+                size_t cols = Inputs(index)->FunctionValues().GetNumCols() == 0 ? Inputs(1 - index)->FunctionValues().GetNumCols() : Inputs(index)->FunctionValues().GetNumCols();
+                Inputs(index)->FunctionValues().Resize(rows, cols);
+            }
+
+            if (Inputs(0)->FunctionValues().GetNumElements() == 0 || Inputs(1)->FunctionValues().GetNumElements() == 0)
+                throw std::logic_error("CosDistanceWithNegativeSamples operation: one of the operants has 0 element.");
+
+            if (Inputs(1)->FunctionValues().GetNumRows() != Inputs(0)->FunctionValues().GetNumRows() ||
+                Inputs(1)->FunctionValues().GetNumCols() != Inputs(0)->FunctionValues().GetNumCols())
+                throw std::logic_error("The Matrix dimension in the CosDistanceWithNegativeSamples operation does not match.");
+
+            // input(2) is shift, input(3) is the #neg
+            size_t negNumber = (size_t)Inputs(3)->FunctionValues()(0, 0);
+
+            FunctionValues().Resize(negNumber + 1, Inputs(1)->FunctionValues().GetNumCols());
+
+            CopyImageSizeFromInputs();
+        }
+
+        virtual void CopyImageSizeFromInputs()
+        {
+            CopyImageSizeFromInput(0, false);
+
+            m_outputChannels = 1;
+            m_outputWidth = 1;
+            m_outputHeight = 1;
+        }
+
+        virtual void AttachInputs(const ComputationNodePtr leftNode, const ComputationNodePtr rightNode, const ComputationNodePtr shiftNode, const ComputationNodePtr negNode)
+        {
+            m_children.resize(4);
+            m_children[0] = leftNode;
+            m_children[1] = rightNode;
+            m_children[2] = shiftNode;
+            m_children[3] = negNode;
+        }
+
+        virtual void MoveMatricesToDevice(const short deviceId)
+        {
+            ComputationNode<ElemType>::MoveMatricesToDevice(deviceId);
+
+            if (deviceId != AUTOPLACEMATRIX)
+            {
+                if (m_invNorm0.GetDeviceId() != deviceId)
+                    m_invNorm0.TransferFromDeviceToDevice(m_invNorm0.GetDeviceId(), deviceId);
+                if (m_invNorm1.GetDeviceId() != deviceId)
+                    m_invNorm1.TransferFromDeviceToDevice(m_invNorm1.GetDeviceId(), deviceId);
+                if (m_invNormSquare.GetDeviceId() != deviceId)
+                    m_invNormSquare.TransferFromDeviceToDevice(m_invNormSquare.GetDeviceId(), deviceId);
+                if (m_leftTerm.GetDeviceId() != deviceId)
+                    m_leftTerm.TransferFromDeviceToDevice(m_leftTerm.GetDeviceId(), deviceId);
+                if (m_rightTerm.GetDeviceId() != deviceId)
+                    m_rightTerm.TransferFromDeviceToDevice(m_rightTerm.GetDeviceId(), deviceId);
+                if (m_temp.GetDeviceId() != deviceId)
+                    m_temp.TransferFromDeviceToDevice(m_temp.GetDeviceId(), deviceId);
+            }
+        }
+
+        virtual void CopyTo(const ComputationNodePtr nodeP, const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            ComputationNode<ElemType>::CopyTo(nodeP, newName, flags);
+            CosDistanceWithNegativeSamplesNode<ElemType>* node = (CosDistanceWithNegativeSamplesNode<ElemType>*) nodeP;
+
+            if (flags & CopyNodeFlags::copyNodeValue)
+            {
+                node->m_invNorm0 = m_invNorm0;
+                node->m_invNorm1 = m_invNorm1;
+                node->m_invNormSquare = m_invNormSquare;
+                node->m_leftTerm = m_leftTerm;
+                node->m_rightTerm = m_rightTerm;
+                node->m_temp = m_temp;
+            }
+        }
+
+        // copy constructor
+        CosDistanceWithNegativeSamplesNode(const CosDistanceWithNegativeSamplesNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags)
+            : ComputationNode<ElemType>(node->m_deviceId), m_invNorm0(node->m_deviceId), m_invNorm1(node->m_deviceId), m_leftTerm(node->m_deviceId), m_rightTerm(node->m_deviceId), m_temp(node->m_deviceId)
+        {
+            node->CopyTo(this, newName, flags);
+        }
+
+        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            const std::wstring& name = (newName == L"") ? NodeName() : newName;
+
+            ComputationNodePtr node = new CosDistanceWithNegativeSamplesNode<ElemType>(this, name, flags);
+            return node;
+        }
+
+    private:
+        // invNorm nodes tranfer data between EvaluateThisNode and ComputeInputPartial
+        Matrix<ElemType> m_invNorm0;
+        Matrix<ElemType> m_invNorm1;
+        // the rest are temporaries, values don't need to be maintained
+        Matrix<ElemType> m_leftTerm;
+        Matrix<ElemType> m_rightTerm;
+        Matrix<ElemType> m_invNormSquare;
+        Matrix<ElemType> m_temp;
+    };
+
+    template class CosDistanceWithNegativeSamplesNode<float>;
+    template class CosDistanceWithNegativeSamplesNode<double>;
+
+}}}
diff --git a/MachineLearning/CNTK/NetworkDescriptionLanguage.cpp b/MachineLearning/CNTK/NetworkDescriptionLanguage.cpp
index 76811c7ce..4f2f2309f 100644
--- a/MachineLearning/CNTK/NetworkDescriptionLanguage.cpp
+++ b/MachineLearning/CNTK/NetworkDescriptionLanguage.cpp
@@ -122,9 +122,9 @@ bool EqualInsensitive(std::wstring& string1, const std::wstring& string2, const
 
 // ++ operator for this enum, so loops work
 NDLPass &operator++(NDLPass &ndlPass) {
-  assert(ndlPass != ndlPassMax);
-  ndlPass = static_cast<NDLPass>(ndlPass + 1);
-  return ndlPass;
+    assert(ndlPass != ndlPassMax);
+    ndlPass = static_cast<NDLPass>(ndlPass + 1);
+    return ndlPass;
 }
 
 // CheckFunction - check to see if we match a function name
diff --git a/MachineLearning/CNTK/NetworkDescriptionLanguage.h b/MachineLearning/CNTK/NetworkDescriptionLanguage.h
index 91e56b271..3a1869b6e 100644
--- a/MachineLearning/CNTK/NetworkDescriptionLanguage.h
+++ b/MachineLearning/CNTK/NetworkDescriptionLanguage.h
@@ -4,13 +4,8 @@
 // </copyright>
 //
 #pragma once
-#include "commandArgUtil.h"
-#include "ComputationNode.h"
-#include "TrainingCriterionNodes.h"
-#include "CompositeComputationNodes.h"
-#include "EvaluationCriterionNodes.h"
+
 #include "ComputationNetwork.h"
-#include <stdarg.h>
 
 namespace Microsoft { namespace MSR { namespace CNTK {
 
diff --git a/MachineLearning/CNTK/NonlinearityNodes.h b/MachineLearning/CNTK/NonlinearityNodes.h
new file mode 100644
index 000000000..032851e96
--- /dev/null
+++ b/MachineLearning/CNTK/NonlinearityNodes.h
@@ -0,0 +1,1617 @@
+//
+// <copyright file="NonlinearityNodes.h" company="Microsoft">
+//     Copyright (c) Microsoft Corporation.  All rights reserved.
+// </copyright>
+//
+#pragma once
+
+#include <unordered_set>
+#include <map>
+#include <string>
+#include <vector>
+#include <stdexcept>
+#include <list>
+#include <memory>
+#include <algorithm>
+#include <assert.h>
+#include <atomic>
+#include <sstream>
+#include <iostream>
+
+#include "Basics.h"
+#include "Matrix.h"
+#include "ComputationNode.h"
+
+namespace Microsoft { namespace MSR { namespace CNTK {
+
+    template<class ElemType>
+    class RectifiedLinearNode : public ComputationNode<ElemType>
+    {
+        UsingComputationNodeMembers;
+    public:
+        RectifiedLinearNode(const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"")  
+            : ComputationNode<ElemType>(deviceId), m_gradientOfRectifiedLinear(deviceId)
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            m_deviceId = deviceId;
+            MoveMatricesToDevice(deviceId);
+            InitRecurrentNode();
+        }
+
+        RectifiedLinearNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"")
+            : ComputationNode<ElemType>(deviceId), m_gradientOfRectifiedLinear(deviceId)
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            LoadFromFile(fstream, modelVersion, deviceId);
+        }
+
+        virtual const std::wstring OperationName() const {return TypeName();}
+
+        virtual void ComputeInputPartial(const size_t inputIndex)
+        {
+            if (inputIndex != 0)
+                throw std::invalid_argument("RectifiedLinear only has one input.");
+            ComputeInputPartialS(m_gradientOfRectifiedLinear, Inputs(0)->FunctionValues(), Inputs(0)->GradientValues(), GradientValues());
+        }
+
+        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
+        {
+            if (inputIndex != 0)
+                throw std::invalid_argument("RectifiedLinear only has one input.");
+
+            Matrix<ElemType> sliceInputGrad = Inputs(0)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            Matrix<ElemType> sliceInputValue = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            ComputeInputPartialS(m_gradientOfRectifiedLinear, sliceInputValue, sliceInputGrad, sliceOutputGrad);
+        }
+
+        static void WINAPI ComputeInputPartialS(Matrix<ElemType>& gradientOfRectifiedLinear, const Matrix<ElemType>& inputFunctionValues, Matrix<ElemType>& inputGradientValues, const Matrix<ElemType>& gradientValues)
+        {
+            gradientOfRectifiedLinear.AssignLinearRectifierDerivativeOf(inputFunctionValues);
+#if DUMPOUTPUT
+            inputGradientValues.Print("RecitifiedLinearNode-Partial-in");
+#endif
+            inputGradientValues.AddElementProductOf(gradientValues, gradientOfRectifiedLinear); 
+#if DUMPOUTPUT
+            inputGradientValues.Print("RecitifiedLinearNode-Partial-out");
+#endif
+        }
+
+        virtual void EvaluateThisNode()  
+        {
+            EvaluateThisNodeS(m_functionValues, Inputs(0)->FunctionValues());
+        }
+
+        virtual void EvaluateThisNode(const size_t timeIdxInSeq)
+        {
+            Matrix<ElemType> sliceInputValue = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            EvaluateThisNodeS(sliceOutputValue, sliceInputValue);
+        }
+
+        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, const Matrix<ElemType>& inputFunctionValues)  
+        {
+            functionValues.AssignTruncateBottomOf(inputFunctionValues, 0);
+#if NANCHECK
+            functionValues.HasNan("RectifiedLinear");
+#endif
+#if DUMPOUTPUT
+            functionValues.Print("RectifiedLinearNode");
+#endif
+        }
+
+        virtual void Validate()
+        {
+            PrintSelfBeforeValidation();
+
+            if (m_children.size() != 1) 
+                throw std::logic_error("RectifiedLinear operation should have one input.");
+
+            if (Inputs(0)->FunctionValues().GetNumElements() == 0)
+                throw std::logic_error("RectifiedLinear operation: the input node has 0 element.");
+
+            FunctionValues().Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(0)->FunctionValues().GetNumCols());
+            m_gradientOfRectifiedLinear.Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(0)->FunctionValues().GetNumCols());
+            CopyImageSizeFromInputs(); 
+        }
+
+        virtual void AttachInputs(const ComputationNodePtr singleInput) 
+        {
+            m_children.resize(1);
+            m_children[0] = singleInput;
+        }
+
+        virtual void MoveMatricesToDevice(const DEVICEID_TYPE deviceId)
+        {
+            ComputationNode<ElemType>::MoveMatricesToDevice(deviceId);
+
+            if (deviceId != AUTOPLACEMATRIX)
+            {
+                if (m_gradientOfRectifiedLinear.GetDeviceId() != deviceId)
+                    m_gradientOfRectifiedLinear.TransferFromDeviceToDevice(m_gradientOfRectifiedLinear.GetDeviceId(), deviceId);
+            }
+        }
+
+        static const std::wstring TypeName() {return L"RectifiedLinear";} 
+
+        virtual void CopyTo(const ComputationNodePtr nodeP, const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            ComputationNode<ElemType>::CopyTo(nodeP, newName, flags);
+            RectifiedLinearNode<ElemType>* node = (RectifiedLinearNode<ElemType>*) nodeP;
+
+            if (flags & CopyNodeFlags::copyNodeValue)
+            {
+                node->m_gradientOfRectifiedLinear = m_gradientOfRectifiedLinear;
+            }
+        }
+
+        // copy constructor
+        RectifiedLinearNode(const RectifiedLinearNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags)
+            : ComputationNode<ElemType>(node->m_deviceId), m_gradientOfRectifiedLinear(node->m_deviceId)
+        {
+            node->CopyTo(this, newName, flags);
+        }
+
+        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            const std::wstring& name = (newName == L"")?NodeName():newName;
+                
+            ComputationNodePtr node = new RectifiedLinearNode<ElemType>(this, name, flags);
+            return node;
+        }
+
+    private:
+        Matrix<ElemType> m_gradientOfRectifiedLinear;
+    };
+
+    template class RectifiedLinearNode<float>; 
+    template class RectifiedLinearNode<double>;
+
+    template<class ElemType>
+    class SigmoidNode : public ComputationNode<ElemType>
+    {
+        UsingComputationNodeMembers;
+    public:
+        SigmoidNode(const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"")  
+            : ComputationNode<ElemType>(deviceId), m_gradientOfSigmoid(deviceId)
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            m_deviceId = deviceId;
+            MoveMatricesToDevice(deviceId);
+            InitRecurrentNode();
+        }
+
+        SigmoidNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"")
+            : ComputationNode<ElemType>(deviceId), m_gradientOfSigmoid(deviceId)
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            LoadFromFile(fstream, modelVersion, deviceId);
+        }
+
+        virtual const std::wstring OperationName() const {return TypeName();}
+        static const std::wstring TypeName() {return L"Sigmoid";} 
+
+        virtual void ComputeInputPartial(const size_t inputIndex)
+        {
+            if (inputIndex != 0)
+                throw std::invalid_argument("Sigmoid only has one input.");
+            ComputeInputPartialS(m_gradientOfSigmoid, Inputs(0)->GradientValues(), GradientValues(), FunctionValues());  
+        }
+
+        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
+        {
+            if (inputIndex != 0)
+                throw std::invalid_argument("Sigmoid only has one input.");
+
+            Matrix<ElemType> sliceInputGrad = Inputs(0)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            ComputeInputPartialS(m_gradientOfSigmoid, sliceInputGrad, sliceOutputGrad, sliceOutputValue);  
+        }
+
+        static void WINAPI ComputeInputPartialS(Matrix<ElemType>& gradientOfSigmoid, Matrix<ElemType>& inputGradientValues, const Matrix<ElemType>& gradientValues, const Matrix<ElemType>& functionValues)  
+        {
+            gradientOfSigmoid.AssignSigmoidDerivativeOf(functionValues);
+
+            inputGradientValues.AddElementProductOf(gradientValues, gradientOfSigmoid);
+        }
+
+        virtual void EvaluateThisNode()  
+        {
+            EvaluateThisNodeS(m_functionValues, Inputs(0)->FunctionValues());
+        }
+
+        virtual void EvaluateThisNode(const size_t timeIdxInSeq)  
+        {
+            Matrix<ElemType> sliceInputValue = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            EvaluateThisNodeS(sliceOutputValue, sliceInputValue);
+        }
+
+        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, const Matrix<ElemType>& inputFunctionValues)  
+        {
+            functionValues.AssignSigmoidOf(inputFunctionValues);
+#if NANCHECK
+            functionValues.HasNan("Sigmoid");
+#endif
+        }
+
+        virtual void Validate()
+        {
+            PrintSelfBeforeValidation();
+
+            if (m_children.size() != 1) 
+                throw std::logic_error("Sigmoid operation should have one input.");
+
+            if (Inputs(0)->FunctionValues().GetNumElements() == 0)
+                throw std::logic_error("Sigmoid operation: the input node has 0 element.");
+
+            FunctionValues().Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(0)->FunctionValues().GetNumCols());
+            m_gradientOfSigmoid.Resize(FunctionValues().GetNumRows(), FunctionValues().GetNumCols());
+            CopyImageSizeFromInputs(); 
+        }
+
+        virtual void AttachInputs(const ComputationNodePtr singleInput) 
+        {
+            m_children.resize(1);
+            m_children[0] = singleInput;
+        }
+
+        virtual void MoveMatricesToDevice(const DEVICEID_TYPE deviceId)
+        {
+            ComputationNode<ElemType>::MoveMatricesToDevice(deviceId);
+
+            if (deviceId != AUTOPLACEMATRIX)
+            {
+                if (m_gradientOfSigmoid.GetDeviceId() != deviceId)
+                    m_gradientOfSigmoid.TransferFromDeviceToDevice(m_gradientOfSigmoid.GetDeviceId(), deviceId);
+            }
+        }
+
+        virtual void CopyTo(const ComputationNodePtr nodeP, const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            ComputationNode<ElemType>::CopyTo(nodeP, newName, flags);
+            SigmoidNode<ElemType>* node = (SigmoidNode<ElemType>*) nodeP;
+
+            if (flags & CopyNodeFlags::copyNodeValue)
+            {
+                node->m_gradientOfSigmoid = m_gradientOfSigmoid;
+            }
+        }
+
+        // copy constructor
+        SigmoidNode(const SigmoidNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags)
+            : ComputationNode<ElemType>(node->m_deviceId), m_gradientOfSigmoid(node->m_deviceId)
+        {
+            node->CopyTo(this, newName, flags);
+        }
+
+        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            const std::wstring& name = (newName == L"")?NodeName():newName;
+                
+            ComputationNodePtr node = new SigmoidNode<ElemType>(this, name, flags);
+            return node;
+        }
+
+    private:
+        Matrix<ElemType> m_gradientOfSigmoid;
+    };
+
+    template class SigmoidNode<float>; 
+    template class SigmoidNode<double>;
+
+    template<class ElemType>
+    class TanhNode : public ComputationNode<ElemType>
+    {
+        UsingComputationNodeMembers;
+    public:
+        TanhNode(const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"")  
+            : ComputationNode<ElemType>(deviceId), m_gradientOfTanh(deviceId)  
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            m_deviceId = deviceId;
+            MoveMatricesToDevice(deviceId);
+            InitRecurrentNode();
+        }
+
+        TanhNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"")
+            : ComputationNode<ElemType>(deviceId), m_gradientOfTanh(deviceId)
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            LoadFromFile(fstream, modelVersion, deviceId);
+        }
+
+        virtual const std::wstring OperationName() const {return TypeName();}
+        static const std::wstring TypeName() {return L"Tanh";} 
+
+        virtual void ComputeInputPartial(const size_t inputIndex)
+        {
+            if (inputIndex != 0)
+                throw std::invalid_argument("Tanh only has one input.");
+            ComputeInputPartialS(m_gradientOfTanh, Inputs(0)->GradientValues(), GradientValues(), FunctionValues());
+        }
+
+        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
+        {
+            if (inputIndex != 0)
+                throw std::invalid_argument("Tanh only has one input.");
+
+            Matrix<ElemType> sliceInputGrad = Inputs(0)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            ComputeInputPartialS(m_gradientOfTanh, sliceInputGrad, sliceOutputGrad, sliceOutputValue);
+        }
+
+        static void WINAPI ComputeInputPartialS(Matrix<ElemType>& gradientOfTanh, Matrix<ElemType>& inputGradientValues, const Matrix<ElemType>& gradientValues, const Matrix<ElemType>& functionValues)  
+        {
+            gradientOfTanh.AssignElementProductOf(functionValues, functionValues); // v .* v
+            gradientOfTanh.AssignDifferenceOf(1, gradientOfTanh); // 1-v^2
+
+            inputGradientValues.AddElementProductOf(gradientValues, gradientOfTanh); // += d .* ((1-v) .* v))
+        }
+
+
+        virtual void EvaluateThisNode()  
+        {
+            EvaluateThisNodeS(m_functionValues, Inputs(0)->FunctionValues());
+        }
+
+        virtual void EvaluateThisNode(const size_t timeIdxInSeq)  
+        {
+            Matrix<ElemType> sliceInputValue = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            EvaluateThisNodeS(sliceOutputValue, sliceInputValue);
+        }
+
+        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, const Matrix<ElemType>& inputFunctionValues)  
+        {
+            functionValues.AssignTanhOf(inputFunctionValues);
+#if NANCHECK
+            functionValues.HasNan("Tanh");
+#endif
+        }
+
+        virtual void Validate()
+        {
+            PrintSelfBeforeValidation();
+
+            if (m_children.size() != 1) 
+                throw std::logic_error("Tanh operation should have one input.");
+
+            if (Inputs(0)->FunctionValues().GetNumElements() == 0)
+                throw std::logic_error("Tanh operation: the input node has 0 element.");
+
+            FunctionValues().Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(0)->FunctionValues().GetNumCols());
+            m_gradientOfTanh.Resize(FunctionValues().GetNumRows(), FunctionValues().GetNumCols());
+            CopyImageSizeFromInputs(); 
+        }
+
+        virtual void AttachInputs(const ComputationNodePtr singleInput) 
+        {
+            m_children.resize(1);
+            m_children[0] = singleInput;
+        }
+
+        virtual void MoveMatricesToDevice(const DEVICEID_TYPE deviceId)
+        {
+            ComputationNode<ElemType>::MoveMatricesToDevice(deviceId);
+
+            if (deviceId != AUTOPLACEMATRIX)
+            {
+                if (m_gradientOfTanh.GetDeviceId() != deviceId)
+                    m_gradientOfTanh.TransferFromDeviceToDevice(m_gradientOfTanh.GetDeviceId(), deviceId);
+            }
+        }
+
+        virtual void CopyTo(const ComputationNodePtr nodeP, const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            ComputationNode<ElemType>::CopyTo(nodeP, newName, flags);
+            TanhNode<ElemType>* node = (TanhNode<ElemType>*) nodeP;
+
+            if (flags & CopyNodeFlags::copyNodeValue)
+            {
+                node->m_gradientOfTanh = m_gradientOfTanh;
+            }
+        }
+
+        // copy constructor
+        TanhNode(const TanhNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags)
+            : ComputationNode<ElemType>(node->m_deviceId), m_gradientOfTanh(node->m_deviceId)
+        {
+            node->CopyTo(this, newName, flags);
+        }
+
+        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            const std::wstring& name = (newName == L"")?NodeName():newName;
+                
+            ComputationNodePtr node = new TanhNode<ElemType>(this, name, flags);
+            return node;
+        }
+
+    private:
+        Matrix<ElemType> m_gradientOfTanh;
+    };
+
+    template class TanhNode<float>; 
+    template class TanhNode<double>;
+
+    template<class ElemType>
+    class LogNode : public ComputationNode<ElemType>
+    {
+                UsingComputationNodeMembers;
+        public:
+        LogNode(const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX, const std::wstring name = L"")
+            : ComputationNode<ElemType>(deviceId), m_gradientOfLog(deviceId)
+        {
+            m_nodeName = (name == L"" ? CreateUniqNodeName() : name);
+            m_deviceId = deviceId;
+            MoveMatricesToDevice(deviceId);
+            InitRecurrentNode();
+        }
+
+        LogNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX, const std::wstring name = L"")
+            : ComputationNode<ElemType>(deviceId), m_gradientOfLog(deviceId)
+        {
+            m_nodeName = (name == L"" ? CreateUniqNodeName() : name);
+            LoadFromFile(fstream, modelVersion, deviceId);
+        }
+
+        virtual const std::wstring OperationName() const { return TypeName(); }
+        static const std::wstring TypeName() { return L"Log"; }
+
+
+        virtual void ComputeInputPartial(const size_t inputIndex)
+        {
+            if (inputIndex != 0)
+                throw std::invalid_argument("Log only has one input.");
+            ComputeInputPartialS(m_gradientOfLog, Inputs(0)->GradientValues(), Inputs(0)->FunctionValues(), GradientValues());
+        }
+
+        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
+        {
+            if (inputIndex != 0)
+                throw std::invalid_argument("Log only has one input.");
+
+            Matrix<ElemType> sliceInputGrad = Inputs(0)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            Matrix<ElemType> sliceInputValue = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            ComputeInputPartialS(m_gradientOfLog, sliceInputGrad, sliceInputValue, sliceOutputGrad);
+        }
+
+        static void WINAPI ComputeInputPartialS(Matrix<ElemType>& gradientOfLog, Matrix<ElemType>& inputGradientValues, const Matrix<ElemType>& inputFunctionValues, const Matrix<ElemType>& gradientValues)
+        {
+            gradientOfLog.AssignElementInverseOf(inputFunctionValues); // 1/x (x is input to log(x))
+
+            inputGradientValues.AddElementProductOf(gradientValues, gradientOfLog);
+        }
+
+        virtual void EvaluateThisNode()
+        {
+            EvaluateThisNodeS(m_functionValues, Inputs(0)->FunctionValues());
+        }
+
+        virtual void EvaluateThisNode(const size_t timeIdxInSeq)
+        {
+            Matrix<ElemType> sliceInputValue = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            EvaluateThisNodeS(sliceOutputValue, sliceInputValue);
+        }
+
+        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, const Matrix<ElemType>& inputFunctionValues)
+        {
+            functionValues.AssignLogOf(inputFunctionValues);
+#if NANCHECK
+            functionValues.HasNan("Log");
+#endif
+        }
+
+        virtual void Validate()
+        {
+            PrintSelfBeforeValidation();
+
+            if (m_children.size() != 1)
+                throw std::logic_error("Log operation should have one input.");
+
+            if (Inputs(0)->FunctionValues().GetNumElements() == 0)
+                throw std::logic_error("Log operation: the input node has 0 element.");
+
+            FunctionValues().Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(0)->FunctionValues().GetNumCols());
+            m_gradientOfLog.Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(0)->FunctionValues().GetNumCols());
+            CopyImageSizeFromInputs();
+        }
+
+        virtual void AttachInputs(const ComputationNodePtr singleInput)
+        {
+            m_children.resize(1);
+            m_children[0] = singleInput;
+        }
+
+        virtual void MoveMatricesToDevice(const DEVICEID_TYPE deviceId)
+        {
+            ComputationNode<ElemType>::MoveMatricesToDevice(deviceId);
+
+            if (deviceId != AUTOPLACEMATRIX)
+            {
+                if (m_gradientOfLog.GetDeviceId() != deviceId)
+                    m_gradientOfLog.TransferFromDeviceToDevice(m_gradientOfLog.GetDeviceId(), deviceId);
+            }
+        }
+
+        virtual void CopyTo(const ComputationNodePtr nodeP, const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            ComputationNode<ElemType>::CopyTo(nodeP, newName, flags);
+            LogNode<ElemType>* node = (LogNode<ElemType>*) nodeP;
+
+            if (flags & CopyNodeFlags::copyNodeValue)
+            {
+                node->m_gradientOfLog = m_gradientOfLog;
+            }
+        }
+
+        // copy constructor
+        LogNode(const LogNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags)
+            : ComputationNode<ElemType>(node->m_deviceId), m_gradientOfLog(node->m_deviceId)
+        {
+            node->CopyTo(this, newName, flags);
+        }
+
+        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            const std::wstring& name = (newName == L"") ? NodeName() : newName;
+
+            ComputationNodePtr node = new LogNode<ElemType>(this, name, flags);
+            return node;
+        }
+
+    private:
+        Matrix<ElemType> m_gradientOfLog;
+    };
+
+    template class LogNode<float>;
+    template class LogNode<double>;
+
+
+    template<class ElemType>
+    class ExpNode : public ComputationNode<ElemType>
+    {
+        UsingComputationNodeMembers;
+    public:
+        ExpNode(const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX, const std::wstring name = L"")
+            : ComputationNode<ElemType>(deviceId), m_gradientOfExp(deviceId)
+        {
+            m_nodeName = (name == L"" ? CreateUniqNodeName() : name);
+            m_deviceId = deviceId;
+            MoveMatricesToDevice(deviceId);
+            InitRecurrentNode();
+        }
+
+        ExpNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX, const std::wstring name = L"")
+            : ComputationNode<ElemType>(deviceId), m_gradientOfExp(deviceId)
+        {
+            m_nodeName = (name == L"" ? CreateUniqNodeName() : name);
+            LoadFromFile(fstream, modelVersion, deviceId);
+        }
+
+        virtual const std::wstring OperationName() const { return TypeName(); }
+        static const std::wstring TypeName() { return L"Exp"; }
+
+
+        virtual void ComputeInputPartial(const size_t inputIndex)
+        {
+            if (inputIndex != 0)
+                throw std::invalid_argument("Exp only has one input.");
+            ComputeInputPartialS(m_gradientOfExp, Inputs(0)->GradientValues(), Inputs(0)->FunctionValues(), GradientValues());
+        }
+
+        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
+        {
+            if (inputIndex != 0)
+                throw std::invalid_argument("Exp only has one input.");
+
+            Matrix<ElemType> sliceInputGrad = Inputs(0)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            Matrix<ElemType> sliceInputValue = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            ComputeInputPartialS(m_gradientOfExp, sliceInputGrad, sliceInputValue, sliceOutputGrad);
+        }
+
+        static void WINAPI ComputeInputPartialS(Matrix<ElemType>& gradientOfExp, Matrix<ElemType>& inputGradientValues, const Matrix<ElemType>& inputFunctionValues, const Matrix<ElemType>& gradientValues)
+        {
+            gradientOfExp.AssignExpOf(inputFunctionValues); // Exp(x) is its own partial
+
+            inputGradientValues.AddElementProductOf(gradientValues, gradientOfExp);
+        }
+
+        virtual void EvaluateThisNode()
+        {
+            EvaluateThisNodeS(m_functionValues, Inputs(0)->FunctionValues());
+        }
+
+        virtual void EvaluateThisNode(const size_t timeIdxInSeq)
+        {
+            Matrix<ElemType> sliceInputValue = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            EvaluateThisNodeS(sliceOutputValue, sliceInputValue);
+        }
+
+        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, const Matrix<ElemType>& inputFunctionValues)
+        {
+            functionValues.AssignExpOf(inputFunctionValues);
+#if NANCHECK
+            functionValues.HasNan("Exp");
+#endif
+        }
+
+        virtual void Validate()
+        {
+            PrintSelfBeforeValidation();
+
+            if (m_children.size() != 1)
+                throw std::logic_error("Exp operation should have one input.");
+
+            if (Inputs(0)->FunctionValues().GetNumElements() == 0)
+                throw std::logic_error("Exp operation: the input node has 0 element.");
+
+            FunctionValues().Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(0)->FunctionValues().GetNumCols());
+            m_gradientOfExp.Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(0)->FunctionValues().GetNumCols());
+            CopyImageSizeFromInputs();
+        }
+
+        virtual void AttachInputs(const ComputationNodePtr singleInput)
+        {
+            m_children.resize(1);
+            m_children[0] = singleInput;
+        }
+
+        virtual void MoveMatricesToDevice(const DEVICEID_TYPE deviceId)
+        {
+            ComputationNode<ElemType>::MoveMatricesToDevice(deviceId);
+
+            if (deviceId != AUTOPLACEMATRIX)
+            {
+                if (m_gradientOfExp.GetDeviceId() != deviceId)
+                    m_gradientOfExp.TransferFromDeviceToDevice(m_gradientOfExp.GetDeviceId(), deviceId);
+            }
+        }
+
+        virtual void CopyTo(const ComputationNodePtr nodeP, const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            ComputationNode<ElemType>::CopyTo(nodeP, newName, flags);
+            ExpNode<ElemType>* node = (ExpNode<ElemType>*) nodeP;
+
+            if (flags & CopyNodeFlags::copyNodeValue)
+            {
+                node->m_gradientOfExp = m_gradientOfExp;
+            }
+        }
+
+        // copy constructor
+        ExpNode(const ExpNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags)
+            : ComputationNode<ElemType>(node->m_deviceId), m_gradientOfExp(node->m_deviceId)
+        {
+            node->CopyTo(this, newName, flags);
+        }
+
+        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            const std::wstring& name = (newName == L"") ? NodeName() : newName;
+
+            ComputationNodePtr node = new ExpNode<ElemType>(this, name, flags);
+            return node;
+        }
+
+    private:
+        Matrix<ElemType> m_gradientOfExp;
+    };
+
+    template class ExpNode<float>;
+    template class ExpNode<double>;
+
+
+    template<class ElemType>
+    class CosineNode : public ComputationNode<ElemType>
+    {
+        UsingComputationNodeMembers;
+    public:
+        CosineNode(const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"")  
+            : ComputationNode<ElemType>(deviceId), m_gradientOfCosine(deviceId)
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            m_deviceId = deviceId;
+            MoveMatricesToDevice(deviceId);
+            InitRecurrentNode();
+        }
+
+        CosineNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"")
+            : ComputationNode<ElemType>(deviceId), m_gradientOfCosine(deviceId)
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            LoadFromFile(fstream, modelVersion, deviceId);
+        }
+
+        virtual const std::wstring OperationName() const {return TypeName();}
+        static const std::wstring TypeName() {return L"Cosine";} 
+
+        virtual void ComputeInputPartial(const size_t inputIndex)
+        {
+            if (inputIndex != 0)
+                throw std::invalid_argument("Cosine only has one input.");
+            ComputeInputPartialS(m_gradientOfCosine, Inputs(0)->GradientValues(), Inputs(0)->FunctionValues(), GradientValues());
+        }
+
+        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
+        {
+            if (inputIndex != 0)
+                throw std::invalid_argument("Cosine only has one input.");
+
+            Matrix<ElemType> sliceInputGrad = Inputs(0)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            Matrix<ElemType> sliceInputValue = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            ComputeInputPartialS(m_gradientOfCosine, sliceInputGrad, sliceInputValue, sliceOutputGrad);
+        }
+
+        static void WINAPI ComputeInputPartialS(Matrix<ElemType>& gradientOfCosine, Matrix<ElemType>& inputGradientValues, const Matrix<ElemType>& inputFunctionValues, const Matrix<ElemType>& gradientValues)  
+        {
+            gradientOfCosine.AssignNegativeSineOf(inputFunctionValues); // -sin(x) (x is input to Cosine(x))
+            inputGradientValues.AddElementProductOf(gradientValues, gradientOfCosine);
+        }
+
+        virtual void EvaluateThisNode()  
+        {
+            EvaluateThisNodeS(m_functionValues, Inputs(0)->FunctionValues());
+        }
+
+        virtual void EvaluateThisNode(const size_t timeIdxInSeq)
+        {
+            Matrix<ElemType> sliceInputValue = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            EvaluateThisNodeS(sliceOutputValue, sliceInputValue);
+        }
+
+        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, const Matrix<ElemType>& inputFunctionValues)  
+        {
+            functionValues.AssignCosineOf(inputFunctionValues);
+#if NANCHECK
+            functionValues.HasNan("Cosine");
+#endif
+        }
+
+
+        virtual void Validate()
+        {
+            PrintSelfBeforeValidation();
+
+            if (m_children.size() != 1) 
+                throw std::logic_error("Cosine operation should have one input.");
+
+            if (Inputs(0)->FunctionValues().GetNumElements() == 0)
+                throw std::logic_error("Cosine operation: the input node has 0 element.");
+
+            FunctionValues().Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(0)->FunctionValues().GetNumCols());
+            m_gradientOfCosine.Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(0)->FunctionValues().GetNumCols());
+            CopyImageSizeFromInputs(); 
+        }
+
+        virtual void AttachInputs(const ComputationNodePtr singleInput) 
+        {
+            m_children.resize(1);
+            m_children[0] = singleInput;
+        }
+
+        virtual void MoveMatricesToDevice(const DEVICEID_TYPE deviceId)
+        {
+            ComputationNode<ElemType>::MoveMatricesToDevice(deviceId);
+
+            if (deviceId != AUTOPLACEMATRIX)
+            {
+                if (m_gradientOfCosine.GetDeviceId() != deviceId)
+                    m_gradientOfCosine.TransferFromDeviceToDevice(m_gradientOfCosine.GetDeviceId(), deviceId);
+            }
+        }
+
+        virtual void CopyTo(const ComputationNodePtr nodeP, const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            ComputationNode<ElemType>::CopyTo(nodeP, newName, flags);
+            CosineNode<ElemType>* node = (CosineNode<ElemType>*) nodeP;
+
+            if (flags & CopyNodeFlags::copyNodeValue)
+            {
+                node->m_gradientOfCosine = m_gradientOfCosine;
+            }
+        }
+
+        // copy constructor
+        CosineNode(const CosineNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags)
+            : ComputationNode<ElemType>(node->m_deviceId), m_gradientOfCosine(node->m_deviceId)
+        {
+            node->CopyTo(this, newName, flags);
+        }
+
+        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            const std::wstring& name = (newName == L"")?NodeName():newName;
+                
+            ComputationNodePtr node = new CosineNode<ElemType>(this, name, flags);
+            return node;
+        }
+
+    private:
+        Matrix<ElemType> m_gradientOfCosine;
+    };
+
+    template class CosineNode<float>; 
+    template class CosineNode<double>;
+
+
+    //we assume it's  column-wise by default
+    //the derivative will increase the Matrix<ElemType> size to the power of column size and should not be used.
+    template<class ElemType>
+    class SoftmaxNode : public ComputationNode<ElemType>
+    {
+        UsingComputationNodeMembers;
+    public:
+        SoftmaxNode(const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"")
+            : ComputationNode<ElemType>(deviceId), m_gradientDotValue(deviceId), m_diff(deviceId)
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            m_deviceId = deviceId;
+            MoveMatricesToDevice(deviceId);
+            InitRecurrentNode();
+        }
+
+        SoftmaxNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"")
+            : ComputationNode<ElemType>(deviceId), m_gradientDotValue(deviceId), m_diff(deviceId)
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            LoadFromFile(fstream, modelVersion, deviceId);
+        }
+
+        virtual const std::wstring OperationName() const {return TypeName();}
+        static const std::wstring TypeName() {return L"Softmax";} 
+
+        virtual void ComputeInputPartial(const size_t inputIndex)
+        {
+            if (inputIndex != 0)
+                throw std::invalid_argument("Softmax only has one input.");
+            ComputeInputPartialS(m_gradientDotValue, m_diff, Inputs(0)->GradientValues(), GradientValues(), FunctionValues());
+        }
+
+        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
+        {
+            if (inputIndex != 0)
+                throw std::invalid_argument("Softmax only has one input.");
+
+            Matrix<ElemType> sliceInputGrad = Inputs(0)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            ComputeInputPartialS(m_gradientDotValue, m_diff, sliceInputGrad, sliceOutputGrad, sliceOutputValue);
+        }
+
+        static void WINAPI ComputeInputPartialS(Matrix<ElemType>& gradientDotValue, Matrix<ElemType>& diff, Matrix<ElemType>& inputGradientValues, 
+            const Matrix<ElemType>& gradientValues, const Matrix<ElemType>& functionValues)  
+        {
+            gradientDotValue.AssignInnerProductOf(gradientValues, functionValues, true);
+            diff.AssignDifferenceOf(gradientValues, gradientDotValue);
+
+            inputGradientValues.AddElementProductOf(diff, functionValues);
+        }
+
+        virtual void EvaluateThisNode()  
+        {
+            EvaluateThisNodeS(m_functionValues, Inputs(0)->FunctionValues());
+        }
+
+        virtual void EvaluateThisNode(const size_t timeIdxInSeq)
+        {
+            Matrix<ElemType> sliceInputValue = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            EvaluateThisNodeS(sliceOutputValue, sliceInputValue);
+        }
+
+        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, const Matrix<ElemType>& inputFunctionValues)  
+        {
+            functionValues.AssignLogSoftmaxOf(inputFunctionValues, true);
+            functionValues.InplaceExp();
+#if NANCHECK
+            functionValues.HasNan("SoftMax");
+#endif
+        }
+
+        virtual void Validate()
+        {
+            PrintSelfBeforeValidation();
+
+            if (m_children.size() != 1) 
+                throw std::logic_error("SoftmaxNode operation should have one input.");
+
+            if (Inputs(0)->FunctionValues().GetNumElements() == 0)
+                throw std::logic_error("SoftmaxNode operation: the input node has 0 element.");
+
+            FunctionValues().Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(0)->FunctionValues().GetNumCols());
+            CopyImageSizeFromInputs(); 
+        }
+
+        virtual void AttachInputs(const ComputationNodePtr singleInput) 
+        {
+            m_children.resize(1);
+            m_children[0] = singleInput;
+        }
+
+        virtual void MoveMatricesToDevice(const DEVICEID_TYPE deviceId)
+        {
+            ComputationNode<ElemType>::MoveMatricesToDevice(deviceId);
+
+            if (deviceId != AUTOPLACEMATRIX)
+            {
+                if (m_gradientDotValue.GetDeviceId() != deviceId)
+                    m_gradientDotValue.TransferFromDeviceToDevice(m_gradientDotValue.GetDeviceId(), deviceId);
+                if (m_diff.GetDeviceId() != deviceId)
+                    m_diff.TransferFromDeviceToDevice(m_diff.GetDeviceId(), deviceId);
+            }
+        }
+
+        virtual void CopyTo(const ComputationNodePtr nodeP, const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            ComputationNode<ElemType>::CopyTo(nodeP, newName, flags);
+            SoftmaxNode<ElemType>* node = (SoftmaxNode<ElemType>*) nodeP;
+
+            if (flags & CopyNodeFlags::copyNodeValue)
+            {
+                node->m_gradientDotValue = m_gradientDotValue;
+                node->m_diff = m_diff;
+            }
+        }
+
+        // copy constructor
+        SoftmaxNode(const SoftmaxNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags)
+            : ComputationNode<ElemType>(node->m_deviceId), m_gradientDotValue(node->m_deviceId), m_diff(node->m_deviceId) 
+        {
+            node->CopyTo(this, newName, flags);
+        }
+
+        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            const std::wstring& name = (newName == L"")?NodeName():newName;
+                
+            ComputationNodePtr node = new SoftmaxNode<ElemType>(this, name, flags);
+            return node;
+        }
+
+    private:
+        Matrix<ElemType> m_gradientDotValue;
+        Matrix<ElemType> m_diff;
+    };
+
+    template class SoftmaxNode<float>; 
+    template class SoftmaxNode<double>;
+
+    template<class ElemType>
+    class LogSoftmaxNode : public ComputationNode<ElemType>
+    {
+        UsingComputationNodeMembers;
+    public:
+        LogSoftmaxNode(const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX, const std::wstring name = L"")
+            : ComputationNode<ElemType>(deviceId), m_gradientDotValue(deviceId), m_softmax(deviceId)
+        {
+            m_nodeName = (name == L"" ? CreateUniqNodeName() : name);
+            m_deviceId = deviceId;
+            MoveMatricesToDevice(deviceId);
+            InitRecurrentNode();
+        }
+
+        LogSoftmaxNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX, const std::wstring name = L"")
+            : ComputationNode<ElemType>(deviceId), m_gradientDotValue(deviceId), m_softmax(deviceId)
+        {
+            m_nodeName = (name == L"" ? CreateUniqNodeName() : name);
+            LoadFromFile(fstream, modelVersion, deviceId);
+        }
+
+        virtual const std::wstring OperationName() const { return TypeName(); }
+        static const std::wstring TypeName() { return L"LogSoftmax"; }
+
+        virtual void ComputeInputPartial(const size_t inputIndex)
+        {
+            if (inputIndex != 0)
+                throw std::invalid_argument("Softmax only has one input.");
+            ComputeInputPartialS(m_gradientDotValue, m_softmax, Inputs(0)->GradientValues(), GradientValues(), FunctionValues());
+        }
+
+        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
+        {
+            if (inputIndex != 0)
+                throw std::invalid_argument("Softmax only has one input.");
+
+            Matrix<ElemType> sliceInputGrad = Inputs(0)->GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputGrad = GradientValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            ComputeInputPartialS(m_gradientDotValue, m_softmax, sliceInputGrad, sliceOutputGrad, sliceOutputValue);
+        }
+
+        static void WINAPI ComputeInputPartialS(Matrix<ElemType>& gradientDotValue, Matrix<ElemType>& softmax, Matrix<ElemType>& inputGradientValues,
+            const Matrix<ElemType>& gradientValues, const Matrix<ElemType>& functionValues)
+        {
+            softmax.AssignExpOf(functionValues);
+            Matrix<ElemType>::VectorSum(gradientValues, gradientDotValue, true);
+            softmax.RowElementMultiplyWith(gradientDotValue);
+            Matrix<ElemType>::AddScaledDifference(1.0, gradientValues, softmax, inputGradientValues);
+        }
+
+        virtual void EvaluateThisNode()
+        {
+            EvaluateThisNodeS(m_functionValues, Inputs(0)->FunctionValues());
+        }
+
+        virtual void EvaluateThisNode(const size_t timeIdxInSeq)
+        {
+            Matrix<ElemType> sliceInputValue = Inputs(0)->FunctionValues().ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(timeIdxInSeq * m_samplesInRecurrentStep, m_samplesInRecurrentStep);
+
+            EvaluateThisNodeS(sliceOutputValue, sliceInputValue);
+        }
+
+        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, const Matrix<ElemType>& inputFunctionValues)
+        {
+            functionValues.AssignLogSoftmaxOf(inputFunctionValues, true);
+#if NANCHECK
+            functionValues.HasNan("LogSoftMax");
+#endif
+        }
+
+        virtual void Validate()
+        {
+            PrintSelfBeforeValidation();
+
+            if (m_children.size() != 1)
+                throw std::logic_error("LogSoftmaxNode operation should have one input.");
+
+            if (Inputs(0)->FunctionValues().GetNumElements() == 0)
+                throw std::logic_error("LogSoftmaxNode operation: the input node has 0 element.");
+
+            FunctionValues().Resize(Inputs(0)->FunctionValues().GetNumRows(), Inputs(0)->FunctionValues().GetNumCols());
+            CopyImageSizeFromInputs();
+        }
+
+        virtual void AttachInputs(const ComputationNodePtr singleInput)
+        {
+            m_children.resize(1);
+            m_children[0] = singleInput;
+        }
+
+        virtual void MoveMatricesToDevice(const DEVICEID_TYPE deviceId)
+        {
+            ComputationNode<ElemType>::MoveMatricesToDevice(deviceId);
+
+            if (deviceId != AUTOPLACEMATRIX)
+            {
+                if (m_gradientDotValue.GetDeviceId() != deviceId)
+                    m_gradientDotValue.TransferFromDeviceToDevice(m_gradientDotValue.GetDeviceId(), deviceId);
+                if (m_softmax.GetDeviceId() != deviceId)
+                    m_softmax.TransferFromDeviceToDevice(m_softmax.GetDeviceId(), deviceId);
+            }
+        }
+
+        virtual void CopyTo(const ComputationNodePtr nodeP, const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            ComputationNode<ElemType>::CopyTo(nodeP, newName, flags);
+            LogSoftmaxNode<ElemType>* node = (LogSoftmaxNode<ElemType>*) nodeP;
+
+            if (flags & CopyNodeFlags::copyNodeValue)
+            {
+                node->m_gradientDotValue = m_gradientDotValue;
+                node->m_softmax = m_softmax;
+            }
+        }
+
+        // copy constructor
+        LogSoftmaxNode(const LogSoftmaxNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags)
+            : ComputationNode<ElemType>(node->m_deviceId), m_gradientDotValue(node->m_deviceId), m_softmax(node->m_deviceId)
+        {
+            node->CopyTo(this, newName, flags);
+        }
+
+        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            const std::wstring& name = (newName == L"") ? NodeName() : newName;
+
+            ComputationNodePtr node = new LogSoftmaxNode<ElemType>(this, name, flags);
+            return node;
+        }
+
+    private:
+        Matrix<ElemType> m_gradientDotValue;
+        Matrix<ElemType> m_softmax;
+    };
+
+    template class LogSoftmaxNode<float>;
+    template class LogSoftmaxNode<double>;
+
+    //calculates: the log likelihood of a feature given GMM parameters
+    template<class ElemType>
+    class GMMLogLikelihoodNode : public ComputationNode<ElemType>
+    {
+        UsingComputationNodeMembers;
+    public:
+        GMMLogLikelihoodNode(const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX, const std::wstring name = L"")
+            : ComputationNode<ElemType>(deviceId), m_prior(deviceId), m_normedDeviation(deviceId), m_normedDeviationVectors(deviceId), m_stddev(deviceId), m_posterior(deviceId), m_temp(deviceId)
+        {
+            m_nodeName = (name == L"" ? CreateUniqNodeName() : name);
+            m_deviceId = deviceId;
+            MoveMatricesToDevice(deviceId);
+            InitRecurrentNode();
+        }
+
+        GMMLogLikelihoodNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX, const std::wstring name = L"")
+            : ComputationNode<ElemType>(deviceId), m_prior(deviceId), m_normedDeviation(deviceId), m_normedDeviationVectors(deviceId), m_stddev(deviceId), m_posterior(deviceId), m_temp(deviceId)
+        {
+            m_nodeName = (name == L"" ? CreateUniqNodeName() : name);
+            LoadFromFile(fstream, modelVersion, deviceId);
+        }
+
+        // copy constructor
+        GMMLogLikelihoodNode(const GMMLogLikelihoodNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags)
+            : ComputationNode<ElemType>(node->m_deviceId), m_prior(node->m_deviceId), m_normedDeviation(node->m_deviceId), m_normedDeviationVectors(node->m_deviceId),
+            m_stddev(node->m_deviceId), m_posterior(node->m_deviceId), m_temp(m_deviceId)
+        {
+            node->CopyTo(this, newName, flags);
+        }
+
+        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            const std::wstring& name = (newName == L"") ? NodeName() : newName;
+
+            ComputationNodePtr node = new GMMLogLikelihoodNode<ElemType>(this, name, flags);
+            return node;
+        }
+
+        virtual const std::wstring OperationName() const { return TypeName(); }
+        static const std::wstring TypeName() { return L"GMMLogLikelihood"; }
+
+        virtual void ComputeInputPartial(const size_t inputIndex)
+        {
+            switch (inputIndex)
+            {
+            case 0:
+                ComputeInputPartialUnnormedPrior(Inputs(0)->GradientValues(), m_gradientValues, m_prior, m_posterior, m_temp);
+                break;
+            case 1:
+                ComputeInputPartialMean(Inputs(1)->GradientValues(), m_gradientValues, m_normedDeviationVectors, m_posterior, m_temp);
+                break;
+            case 2:
+                ComputeInputPartialLogStddev(Inputs(2)->GradientValues(), m_gradientValues, m_normedDeviation, m_posterior, m_temp);
+                break;
+            case 3:
+                ComputeInputPartialFeature(Inputs(3)->GradientValues(), m_gradientValues, m_normedDeviationVectors, m_posterior, m_temp);
+                break;
+            default:
+                throw std::invalid_argument("GMMLogLikelihoodNode only takes four inputs.");
+            }
+        }
+
+        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
+        {
+            //get the right slice 
+            size_t startIndex = timeIdxInSeq * m_samplesInRecurrentStep;
+
+            size_t colsPrior = Inputs(0)->FunctionValues().GetNumCols();
+
+            Matrix<ElemType> sliceGradientValue = m_gradientValues.ColumnSlice(startIndex, m_samplesInRecurrentStep);
+            Matrix<ElemType> slicePosterior = m_posterior.ColumnSlice(startIndex, m_samplesInRecurrentStep);
+                
+            switch (inputIndex)
+            {
+            case 0:
+                {
+                    if (colsPrior == 1)
+                        ComputeInputPartialUnnormedPrior(Inputs(0)->GradientValues(), sliceGradientValue, m_prior, slicePosterior, m_temp);
+                    else
+                    {
+                        Matrix<ElemType> sliceUnnormedPriorGradient = Inputs(0)->GradientValues().ColumnSlice(startIndex, m_samplesInRecurrentStep);
+                        Matrix<ElemType> slicePrior = m_prior.ColumnSlice(startIndex, m_samplesInRecurrentStep);
+                        ComputeInputPartialUnnormedPrior(sliceUnnormedPriorGradient, sliceGradientValue, slicePrior, slicePosterior, m_temp);
+                    }
+                }
+                break;
+            case 1:
+                {
+                      Matrix<ElemType> sliceNormedDeviationVectors = m_normedDeviationVectors.ColumnSlice(startIndex, m_samplesInRecurrentStep);
+                      if (colsPrior == 1)
+                        ComputeInputPartialMean(Inputs(1)->GradientValues(), sliceGradientValue, sliceNormedDeviationVectors, slicePosterior, m_temp);
+                    else
+                    {
+                        Matrix<ElemType> sliceMeanGradient = Inputs(1)->GradientValues().ColumnSlice(startIndex, m_samplesInRecurrentStep);
+                        ComputeInputPartialMean(sliceMeanGradient, sliceGradientValue, sliceNormedDeviationVectors, slicePosterior, m_temp);
+                    }
+                }
+                break;
+            case 2:
+                {
+                    Matrix<ElemType> sliceNormedDeviation = m_normedDeviation.ColumnSlice(startIndex, m_samplesInRecurrentStep);
+                    if (colsPrior == 1)
+                        ComputeInputPartialLogStddev(Inputs(2)->GradientValues(), sliceGradientValue, sliceNormedDeviation, slicePosterior, m_temp);
+                    else
+                    {
+                        Matrix<ElemType> sliceLotStddevGradient = Inputs(2)->GradientValues().ColumnSlice(startIndex, m_samplesInRecurrentStep);
+                        ComputeInputPartialLogStddev(sliceLotStddevGradient, sliceGradientValue, sliceNormedDeviation, slicePosterior, m_temp);
+                    }
+                }
+                break;
+            case 3:
+                {
+                    Matrix<ElemType> sliceNormedDeviationVectors = m_normedDeviationVectors.ColumnSlice(startIndex, m_samplesInRecurrentStep);
+                    Matrix<ElemType> sliceFeatureGradient = Inputs(3)->GradientValues().ColumnSlice(startIndex, m_samplesInRecurrentStep);
+                    ComputeInputPartialFeature(sliceFeatureGradient, sliceGradientValue, sliceNormedDeviationVectors, slicePosterior, m_temp);
+                }
+                break;
+            default:
+                throw std::invalid_argument("GMMLogLikelihoodNode criterion only takes four inputs.");
+            }
+        }
+
+        static void WINAPI ComputeInputPartialUnnormedPrior(Matrix<ElemType>& unnormedPriorGradientValues, const Matrix<ElemType>& gradientValues,
+            const Matrix<ElemType>& prior, const Matrix<ElemType>& posterior, Matrix<ElemType>& temp)
+        {
+            temp.AssignDifferenceOf(posterior, prior);
+            temp.RowElementMultiplyWith(gradientValues);
+            if (prior.GetNumCols() == posterior.GetNumCols())
+            {
+                unnormedPriorGradientValues += temp; 
+            }
+            else if (prior.GetNumCols() == 1)
+            {
+                Matrix<ElemType>::MultiplyAndAdd(temp, false, ConstOnes(posterior.GetNumCols(), 1, unnormedPriorGradientValues.GetDeviceId()), false, unnormedPriorGradientValues);
+            }
+            else
+            {
+                throw std::runtime_error("GMMLogLikelihoodNode: UnnormedPrior should either have same number of columns as the features or have only one column.");
+            }
+        }
+
+        static void WINAPI ComputeInputPartialMean(Matrix<ElemType>& meanGradientValues, const Matrix<ElemType>& gradientValues, const Matrix<ElemType>& normedDeviationVectors,
+            Matrix<ElemType>& posterior, Matrix<ElemType>& temp)
+        {
+            size_t numComponent = posterior.GetNumRows(); 
+            size_t numSamples = posterior.GetNumCols();
+            size_t featureSize = normedDeviationVectors.GetNumRows() / numComponent;
+
+            temp.SetValue(normedDeviationVectors); //recall normedDeviationVectors <-- (x-u_c)/(stddev^2)
+            temp.Reshape(featureSize, numSamples* numComponent);
+
+            posterior.Reshape(1, numSamples* numComponent);
+            temp.RowElementMultiplyWith(posterior); //temp <-- posterior * (x-u_c)/(stddev^2)
+
+            posterior.Reshape(numComponent, numSamples);  //reshape back
+            temp.Reshape(featureSize * numComponent, numSamples); //reshape back
+
+            temp.RowElementMultiplyWith(gradientValues);
+
+            if (numSamples == meanGradientValues.GetNumCols())
+            {
+                meanGradientValues += temp;
+            }
+            else if (meanGradientValues.GetNumCols() == 1)
+            {
+                Matrix<ElemType>::MultiplyAndAdd(temp, false, ConstOnes(numSamples, 1, meanGradientValues.GetDeviceId()), false, meanGradientValues);
+            }
+            else
+            {
+                throw std::runtime_error("GMMLogLikelihoodNode: stddev should either have same number of columns as the features or have only one column.");
+            }
+        }
+
+        static void WINAPI ComputeInputPartialLogStddev(Matrix<ElemType>& logStddevGradientValues, const Matrix<ElemType>& gradientValues, const Matrix<ElemType>& normedDeviation,
+            const Matrix<ElemType>& posterior, Matrix<ElemType>& temp)
+        {
+            size_t numComponent = posterior.GetNumRows();
+            size_t numSamples = posterior.GetNumCols();
+
+            temp.AssignDifferenceOf(normedDeviation, (ElemType)numComponent);
+            temp.ElementMultiplyWith(posterior);
+            temp.RowElementMultiplyWith(gradientValues);
+            if (logStddevGradientValues.GetNumCols() == numSamples)
+            {
+                logStddevGradientValues += temp;
+            }
+            else if (logStddevGradientValues.GetNumCols() == 1)
+            {
+                Matrix<ElemType>::MultiplyAndAdd(temp, false, ConstOnes(numSamples, 1, logStddevGradientValues.GetDeviceId()), false, logStddevGradientValues);
+            }
+            else
+            {
+                throw std::runtime_error("GMMLogLikelihoodNode: stddev should either have same number of columns as the features or have only one column.");
+            }
+        }
+
+        static void WINAPI ComputeInputPartialFeature(Matrix<ElemType>& featureGradientValues, const Matrix<ElemType>& gradientValues, const Matrix<ElemType>& normedDeviationVectors,
+            Matrix<ElemType>& posterior, Matrix<ElemType>& temp)
+        {
+            size_t numComponent = posterior.GetNumRows();
+            size_t numSamples = posterior.GetNumCols();
+            size_t featureSize = normedDeviationVectors.GetNumRows() / numComponent;
+
+            temp.SetValue(normedDeviationVectors);
+            temp *= -1;
+            temp.Reshape(featureSize, numSamples* numComponent);
+            posterior.Reshape(1, numSamples* numComponent);
+            temp.RowElementMultiplyWith(posterior);
+
+            posterior.Reshape(numComponent, numSamples);
+            temp.Reshape(featureSize * numComponent, numSamples);
+            temp.RowElementMultiplyWith(gradientValues);
+
+            for (int i = 0; i < numComponent; i++)
+                featureGradientValues.AddWithRowSliceValuesOf(temp, i*featureSize, featureSize);
+        }
+
+        virtual void SetFunctionAndGradientSize(const int numSamples)
+        {
+            ComputationNode<ElemType>::SetFunctionAndGradientSize(numSamples);
+
+            size_t numComponents = Inputs(0)->FunctionValues().GetNumRows();
+            size_t colsPrior = Inputs(0)->FunctionValues().GetNumCols();
+            //size_t numSamples = Inputs(3)->FunctionValues().GetNumCols();
+            size_t featureSize = Inputs(3)->FunctionValues().GetNumRows();
+
+            m_prior.Resize(numComponents, colsPrior);
+            m_stddev.Resize(numComponents, colsPrior);
+            m_normedDeviation.Resize(numComponents, numSamples);
+            m_normedDeviationVectors.Resize(numComponents * featureSize, numSamples);
+            m_posterior.Resize(numComponents, numSamples);
+        }
+
+        //input0=unnormedPrior, input1=mean, input2=logstddev, input3=feature
+        virtual void EvaluateThisNode()
+        {
+            // all internal matrices will be automatically resized since all of them are assigned to a value so no resize is needed here.
+            EvaluateThisNodeS(FunctionValues(), Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues(), Inputs(2)->FunctionValues(), Inputs(3)->FunctionValues(), 
+                m_prior, m_stddev, m_normedDeviationVectors, m_normedDeviation, m_posterior, m_temp);
+        }
+
+        //input0=unnormedPrior, input1=mean, input2=logstddev, input3=feature
+        virtual void EvaluateThisNode(const size_t timeIdxInSeq)
+        {
+            size_t colsPrior = Inputs(0)->FunctionValues().GetNumCols();
+            size_t numSamples = Inputs(3)->FunctionValues().GetNumCols();
+
+            //get the right slice 
+            size_t startIndex = timeIdxInSeq * m_samplesInRecurrentStep;
+
+            Matrix<ElemType> sliceOutputValue = m_functionValues.ColumnSlice(startIndex, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceFeature = Inputs(3)->FunctionValues().ColumnSlice(startIndex, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceNormedDeviation = m_normedDeviation.ColumnSlice(startIndex, m_samplesInRecurrentStep);
+            Matrix<ElemType> sliceNormedDeviationVectors = m_normedDeviationVectors.ColumnSlice(startIndex, m_samplesInRecurrentStep);
+            Matrix<ElemType> slicePosterior = m_posterior.ColumnSlice(startIndex, m_samplesInRecurrentStep);
+
+            if (colsPrior == 1)
+            {
+                EvaluateThisNodeS(sliceOutputValue, Inputs(0)->FunctionValues(), Inputs(1)->FunctionValues(), Inputs(2)->FunctionValues(), sliceFeature,
+                    m_prior, m_stddev, sliceNormedDeviationVectors, sliceNormedDeviation, slicePosterior, m_temp);
+            }
+            else if (colsPrior == numSamples)
+            {
+                Matrix<ElemType> sliceUnnormedPrior = Inputs(0)->FunctionValues().ColumnSlice(startIndex, m_samplesInRecurrentStep);
+                Matrix<ElemType> sliceMean = Inputs(1)->FunctionValues().ColumnSlice(startIndex, m_samplesInRecurrentStep);
+                Matrix<ElemType> sliceLogstddev = Inputs(2)->FunctionValues().ColumnSlice(startIndex, m_samplesInRecurrentStep);
+
+                Matrix<ElemType> slicePrior = m_prior.ColumnSlice(startIndex, m_samplesInRecurrentStep);
+                Matrix<ElemType> sliceStddev = m_stddev.ColumnSlice(startIndex, m_samplesInRecurrentStep);
+
+                EvaluateThisNodeS(sliceOutputValue, sliceUnnormedPrior, sliceMean, sliceLogstddev, sliceFeature,
+                    slicePrior, sliceStddev, sliceNormedDeviationVectors, sliceNormedDeviation, slicePosterior, m_temp);
+            }
+            else  //should not reach the code since validation should fail already
+            {
+                throw std::runtime_error("GMMLogLikelihoodNode: UnnormedPrior should either have same number of columns as the features or have only one column.");
+            }
+
+        }
+
+        //input0=unnormedPrior, input1=mean, input2=logstddev, input3=feature
+        //If we want to speed up we need to replace following code with a several specialized GPU functions
+        static void WINAPI EvaluateThisNodeS(Matrix<ElemType>& functionValues, const Matrix<ElemType>& unnormedPrior, const Matrix<ElemType>& mean,  Matrix<ElemType>& logstddev,
+            const Matrix<ElemType>& feature, Matrix<ElemType>& prior, Matrix<ElemType>& stddev, Matrix<ElemType>& normedDeviationVectors,
+            Matrix<ElemType>& normedDeviation, Matrix<ElemType>& posterior, Matrix<ElemType>& temp)
+        {
+            int numComponent = unnormedPrior.GetNumRows();
+            size_t numSamples = feature.GetNumCols();
+            size_t featureDim = feature.GetNumRows();
+
+            //compute prior which is softmax of unnormedPrior
+            prior.AssignLogSoftmaxOf(unnormedPrior, true);  //log prior
+
+            prior.InplaceExp();
+
+            //compute stddev
+            stddev.AssignExpOf(logstddev);
+
+#if DUMPOUTPUT
+            unnormedPrior.Print("unnormedPrior", 0, min(5, unnormedPrior.GetNumRows() - 1), 0, min(10, unnormedPrior.GetNumCols() - 1));
+            mean.Print("mean", 0, min(5, mean.GetNumRows() - 1), 0, min(10, mean.GetNumCols() - 1));
+            logstddev.Print("logstddev", 0, min(5, logstddev.GetNumRows() - 1), 0, min(10, logstddev.GetNumCols() - 1));
+
+            prior.Print("prior", 0, min(5, prior.GetNumRows() - 1), 0, min(10, prior.GetNumCols() - 1));
+            stddev.Print("stddev", 0, min(5, stddev.GetNumRows() - 1), 0, min(10, stddev.GetNumCols() - 1));
+#endif
+
+            //compute normedDeviation <-- ||x-u_c||^2/(stddev^2)
+            normedDeviationVectors.AssignRepeatOf(feature, numComponent, 1);
+            normedDeviationVectors -= mean; //each column of the mean has multiple mean components
+            normedDeviationVectors.Reshape(featureDim, numSamples* numComponent);  //now each column is feature-mean_i
+
+            normedDeviation.AssignVectorNorm2Of(normedDeviationVectors, true);
+            normedDeviation ^= 2;
+            temp.AssignRepeatOf(stddev, 1, numSamples / stddev.GetNumCols());  //stddev.GetNumCols() is either 1 or =numSamples
+            temp.Reshape(1, temp.GetNumElements());  //one stddev value for each component for each sample
+            temp ^= 2;
+            normedDeviation.ElementDivideBy(temp);  //normedDeviation and temp have same dim (1, numSamples* numComponent)
+
+            //compute  normedDeviationVectors <-- (x-u_c)/(stddev^2)
+            normedDeviationVectors.RowElementDivideBy(temp);  //divide twice
+            normedDeviationVectors.Reshape(featureDim*numComponent, numSamples);  //reshape back
+
+            //compute per-component likelihood
+            posterior.AssignProductOf(-0.5f, normedDeviation); //posterior  <-- -||x-u_c||^2/(stddev^2)/2 and in (1, numSamples* numComponent) dim
+            temp.InplaceLog();
+            temp *= ((ElemType)numComponent / 2.0f); //temp <-- stddev^c and in (1, numSamples* numComponent) dim
+            posterior -= temp;  // posterior  <-- exp[-||x-u_c||^2/(stddev^2)/2]/(stddev^c)
+            posterior -= (ElemType)(numComponent / 2.0f*log(TWO_PI)); //likelihood for each component and sample is now computed and stored in posterior
+            posterior.InplaceExp(); //posterior  <-- exp(-||x-u_c||^2/(stddev^2)/2)
+
+            normedDeviation.Reshape(numComponent, numSamples);  //reshape back
+            posterior.Reshape(numComponent, numSamples);  //reshape back
+
+            //compute posterior <-- prior_i * likelihood_i
+            if (unnormedPrior.GetNumCols() == numSamples)  //each sample has different prior
+                posterior.ElementMultiplyWith(prior);
+            else  //all samples share the same prior
+                posterior.ColumnElementMultiplyWith(prior);
+
+            //compute GMM log-likelihood
+            Matrix<ElemType>::Multiply(ConstOnes(1, numComponent, posterior.GetDeviceId()), false, posterior, false, functionValues);  //functionValues <-- total likelihood
+            posterior.RowElementDivideBy(functionValues); //posterior <-- per-comp likelihood / total likelihood
+            functionValues.InplaceLog(); //log likelihood
+
+#if DUMPOUTPUT
+            temp.Print("temp", 0, min(5, temp.GetNumRows() - 1), 0, min(10, temp.GetNumCols() - 1));
+            normedDeviation.Print("normedDeviation", 0, min(5, normedDeviation.GetNumRows() - 1), 0, min(10, normedDeviation.GetNumCols() - 1));
+
+            posterior.Print("posterior", 0, min(5, posterior.GetNumRows() - 1), 0, min(10, posterior.GetNumCols() - 1));
+            functionValues.Print("functionValues", 0, min(5, functionValues.GetNumRows() - 1), 0, min(10, functionValues.GetNumCols() - 1));
+
+            functionValues.Print("GMMLogLikelihoodNode");
+#endif
+
+#if NANCHECK
+            functionValues.HasNan("GMMLogLikelihood");
+#endif
+        }
+
+        virtual void Validate()
+        {
+            PrintSelfBeforeValidation();
+
+            if (m_children.size() != 4)
+                throw std::logic_error("GMMLogLikelihoodNode requires four inputs.");
+
+            size_t rows[4], cols[4];
+            for (int i = 0; i < 4; i++)
+            {
+                rows[i] = Inputs(i)->FunctionValues().GetNumRows();
+                cols[i] = Inputs(i)->FunctionValues().GetNumCols();
+            }
+
+            if (cols[0] != cols[1] || cols[0] != cols[2])
+                throw std::logic_error("GMMLogLikelihoodNode: UnnormedPrior (first input), mean (second input), and logStddev (third input) should have same number of columns.");
+
+            if (cols[0] != 1 && cols[0] != cols[3])
+                throw std::logic_error("GMMLogLikelihoodNode: UnnormedPrior (first input) should either have same number of columns as the features (fourth input) or have only one column.");
+
+            if (rows[0] != rows[2])
+                throw std::logic_error("GMMLogLikelihoodNode: UnnormedPrior (first input) should have same dimension as logStddev (third input), i.e., all dimensions in each Gaussian component share the same stddev.");
+
+            if (rows[1] != rows[0]*rows[3])
+                throw std::logic_error("GMMLogLikelihoodNode: the number of rows in mean (second input) should equal rows(unnormedPrior(first input) * rows(feature(fourth input)).");
+
+            FunctionValues().Resize(1, cols[3]);
+            CopyImageSizeFromInputs();
+        }
+
+        virtual void CopyImageSizeFromInputs()
+        {
+            CopyImageSizeFromInput(3, false);
+
+            m_outputChannels = 1;
+            m_outputWidth = 1;
+            m_outputHeight = 1;
+        }
+
+        //leftNode should be the empirical
+        virtual void AttachInputs(const ComputationNodePtr unnormedPrior, const ComputationNodePtr mean, const ComputationNodePtr logStddev, const ComputationNodePtr feature)
+        {
+            m_children.resize(4);
+            m_children[0] = unnormedPrior;
+            m_children[1] = mean;
+            m_children[2] = logStddev;
+            m_children[3] = feature;
+        }
+
+        virtual void MoveMatricesToDevice(const DEVICEID_TYPE deviceId)
+        {
+            ComputationNode<ElemType>::MoveMatricesToDevice(deviceId);
+
+            if (deviceId != AUTOPLACEMATRIX)
+            {
+                if (m_prior.GetDeviceId() != deviceId)
+                {
+                    m_prior.TransferFromDeviceToDevice(m_prior.GetDeviceId(), deviceId, true);
+                }
+                if (m_normedDeviation.GetDeviceId() != deviceId)
+                {
+                    m_normedDeviation.TransferFromDeviceToDevice(m_normedDeviation.GetDeviceId(), deviceId, true);
+                }
+                if (m_normedDeviationVectors.GetDeviceId() != deviceId)
+                {
+                    m_normedDeviationVectors.TransferFromDeviceToDevice(m_normedDeviationVectors.GetDeviceId(), deviceId, true);
+                }
+                if (m_stddev.GetDeviceId() != deviceId)
+                {
+                    m_stddev.TransferFromDeviceToDevice(m_stddev.GetDeviceId(), deviceId, true);
+                }
+                if (m_posterior.GetDeviceId() != deviceId)
+                {
+                    m_posterior.TransferFromDeviceToDevice(m_posterior.GetDeviceId(), deviceId, true);
+                }
+            }
+        }
+
+        virtual void CopyTo(const ComputationNodePtr nodeP, const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            ComputationNode<ElemType>::CopyTo(nodeP, newName, flags);
+            GMMLogLikelihoodNode<ElemType>* node = (GMMLogLikelihoodNode<ElemType>*) nodeP;
+
+            if (flags & CopyNodeFlags::copyNodeValue)
+            {
+                node->m_prior = m_prior;
+                node->m_normedDeviation = m_normedDeviation;
+                node->m_normedDeviationVectors = m_normedDeviationVectors;
+                node->m_stddev = m_stddev;
+                node->m_posterior = m_posterior;
+            }
+        }
+
+    protected:
+        Matrix<ElemType> m_prior;
+        Matrix<ElemType> m_normedDeviation;
+        Matrix<ElemType> m_normedDeviationVectors;
+        Matrix<ElemType> m_stddev;
+        Matrix<ElemType> m_posterior;
+        Matrix<ElemType> m_temp;
+    };
+
+    template class GMMLogLikelihoodNode<float>;
+    template class GMMLogLikelihoodNode<double>;
+
+}}}
diff --git a/MachineLearning/CNTK/RecurrentNodes.h b/MachineLearning/CNTK/RecurrentNodes.h
new file mode 100644
index 000000000..9a0825236
--- /dev/null
+++ b/MachineLearning/CNTK/RecurrentNodes.h
@@ -0,0 +1,378 @@
+//
+// <copyright file="RecurrentNodes.h" company="Microsoft">
+//     Copyright (c) Microsoft Corporation.  All rights reserved.
+// </copyright>
+//
+#pragma once
+
+#include <unordered_set>
+#include <map>
+#include <string>
+#include <vector>
+#include <stdexcept>
+#include <list>
+#include <memory>
+#include <algorithm>
+#include <assert.h>
+#include <atomic>
+#include <sstream>
+#include <iostream>
+
+#include "Basics.h"
+#include "Matrix.h"
+#include "ComputationNode.h"
+
+namespace Microsoft { namespace MSR { namespace CNTK {
+
+    template<class ElemType>
+    class DelayNode : public ComputationNode<ElemType>
+    {
+        ElemType  m_default_activity; 
+
+        UsingComputationNodeMembers;
+    public:
+        DelayNode(const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"")  
+            : ComputationNode<ElemType>(deviceId), m_pastActivity(deviceId)
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            m_deviceId = deviceId;
+            MoveMatricesToDevice(deviceId);
+            m_default_activity = (ElemType)DEFAULT_HIDDEN_ACTIVITY;
+            m_delay = 1;
+            m_functionValues.Resize(1,1);
+            m_pastActivity.Resize(1,1);
+            Reset();
+            InitRecurrentNode();
+        }
+                
+        DelayNode(File& fstream, const size_t modelVersion, const DEVICEID_TYPE deviceId=AUTOPLACEMATRIX, const std::wstring name = L"")
+            : ComputationNode<ElemType>(deviceId), m_pastActivity(deviceId)
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+
+            m_default_activity = (ElemType)DEFAULT_HIDDEN_ACTIVITY;
+            m_delay = 1;
+            m_functionValues.Resize(1,1);
+            m_pastActivity.Resize(1,1);
+            Reset();
+
+            LoadFromFile(fstream, modelVersion, deviceId);
+        }
+
+        void SaveToFile(File& fstream) const
+        {
+            fstream << OperationName() << NodeName();
+            fstream << m_delay; 
+            fstream << FunctionValues().GetNumRows() << FunctionValues().GetNumCols(); 
+        }
+
+        void LoadFromFile(File& fstream, const size_t /*modelVersion*/, const DEVICEID_TYPE deviceId = AUTOPLACEMATRIX)
+        {
+            m_deviceId = deviceId;
+            MoveMatricesToDevice(deviceId);
+            InitRecurrentNode();
+
+            fstream >> m_delay;
+
+            size_t iRow, timeIdxInSeq;
+            fstream >> iRow >> timeIdxInSeq;
+            FunctionValues().Resize(iRow,timeIdxInSeq);
+            m_pastActivity.Resize(iRow, timeIdxInSeq);
+        }
+
+        DelayNode(const DEVICEID_TYPE deviceId, ElemType initHiddenActivity, size_t row_size, size_t col_size, const std::wstring name = L"") : ComputationNode<ElemType>(deviceId)  
+        {
+            m_nodeName = (name == L""? CreateUniqNodeName() : name);
+            m_deviceId = deviceId;
+            MoveMatricesToDevice(deviceId);
+            m_default_activity = initHiddenActivity;
+            m_delay = 1;
+
+            m_functionValues.Resize(row_size, col_size);
+            m_functionValues.SetValue(m_default_activity);
+
+            m_pastActivity.Resize(row_size, col_size);
+            m_pastActivity.SetValue(m_default_activity);
+
+            m_gradientValues.Resize(row_size, col_size);
+            m_gradientValues.SetValue(0.0f);
+
+            Reset();
+            InitRecurrentNode();
+        }
+
+        virtual const std::wstring OperationName() const {return TypeName();}
+
+        virtual void ComputeInputPartial(const size_t inputIndex)
+        {
+            if (inputIndex > 0)
+                throw std::invalid_argument("Delay operation only takes one input.");
+
+            size_t nbrSamples = GradientValues().GetNumCols() / m_samplesInRecurrentStep; 
+            for (int i = nbrSamples - 1; i >= 0; i--)
+            {
+                ComputeInputPartialSR(i, m_delay, Inputs(0)->GradientValues(), GradientValues(), m_samplesInRecurrentStep);
+            }
+        }
+
+        virtual void ComputeInputPartial(const size_t inputIndex, const size_t timeIdxInSeq)
+        {
+            if (inputIndex > 0)
+                throw std::invalid_argument("Delay operation only takes one input.");
+            assert(m_functionValues.GetNumRows() == GradientValues().GetNumRows()); // original used m_functionValues.GetNumRows() for loop dimension
+            if (m_samplesInRecurrentStep == 1)
+            {
+                ComputeInputPartialSR(timeIdxInSeq, m_delay, Inputs(0)->GradientValues(), GradientValues(), m_samplesInRecurrentStep);
+            }else
+            {
+                for (size_t i = 0 ; i < m_samplesInRecurrentStep; i++)
+                {
+                    bool reset = false;
+
+                    if ((((int)m_sentenceEnd[i] +(int)m_delay - 1) >= (int)timeIdxInSeq) && (m_sentenceEnd[i] <= timeIdxInSeq))
+                    {
+                        reset = true;
+                    }
+
+                    ComputeInputPartialSRP(timeIdxInSeq, m_delay, reset, Inputs(0)->GradientValues(), GradientValues(), i, m_samplesInRecurrentStep);
+                }
+            }
+        }
+
+        static void WINAPI ComputeInputPartialSR(int timeIdxInSeq, int delay,  
+            Matrix<ElemType>& inputGradientValues, const Matrix<ElemType>& gradientValues, const size_t mNbr)
+        {
+            assert(timeIdxInSeq >= 0);
+            if ((timeIdxInSeq - delay) >= 0 && (timeIdxInSeq - delay) * mNbr <= inputGradientValues.GetNumCols())
+            {
+                Matrix<ElemType> to = inputGradientValues.ColumnSlice((timeIdxInSeq - delay)*mNbr, mNbr);
+                Matrix<ElemType> frm= gradientValues.ColumnSlice(timeIdxInSeq * mNbr, mNbr);
+                to += frm; 
+            }
+        }
+
+        static void WINAPI ComputeInputPartialSRP(int timeIdxInSeq, int delay,  bool reset,
+            Matrix<ElemType>& inputGradientValues, const Matrix<ElemType>& gradientValues, const size_t indexInBatch, const size_t mNbr)
+        {
+            assert(timeIdxInSeq >= 0);
+            if ((timeIdxInSeq - delay) >= 0 && (timeIdxInSeq - delay) * mNbr <= inputGradientValues.GetNumCols() && !reset)
+            {
+                Matrix<ElemType> to = inputGradientValues.ColumnSlice((timeIdxInSeq - delay)*mNbr + indexInBatch, 1);
+                Matrix<ElemType> frm= gradientValues.ColumnSlice(timeIdxInSeq * mNbr + indexInBatch, 1);
+                to += frm; 
+            }
+        }
+
+
+        virtual void EvaluateThisNode()  
+        {
+            ASSERT(m_delay > 0);
+            size_t blogSize = Inputs(0)->FunctionValues().GetNumCols();
+
+            for (size_t i = 0; i < blogSize / m_samplesInRecurrentStep; i++)
+                EvaluateThisNodeSR(i, m_delay, m_Reset, m_default_activity, m_functionValues, m_pastActivity, Inputs(0)->FunctionValues(), m_samplesInRecurrentStep);
+            /// reset past activity
+            m_pastActivity = Inputs(0)->FunctionValues();
+        }
+
+        void Reset()
+        {
+            m_Reset = true;
+        }
+
+
+        void NotReset()
+        {
+            m_Reset = false;
+        }
+
+        virtual void EvaluateThisNode(const size_t timeIdxInSeq)  
+        {
+            /// reset past activity as it reached to the begining of a minibatch
+            /// the node pointed hasn't yet updated, so it is the past activity 
+            if (timeIdxInSeq == 0)
+                m_pastActivity = Inputs(0)->FunctionValues();
+            
+            if (m_samplesInRecurrentStep == 1)
+            {
+                //bool reset = (m_sentenceEnd[0] == timeIdxInSeq);
+                bool reset = false;
+
+                if ((((int)m_sentenceEnd[0] +(int)m_delay - 1) >= (int)timeIdxInSeq) && (m_sentenceEnd[0] <= timeIdxInSeq))
+                {
+                    reset = true;
+                }
+                EvaluateThisNodeSR(timeIdxInSeq, m_delay, reset, m_default_activity, m_functionValues, m_pastActivity, Inputs(0)->FunctionValues(), m_samplesInRecurrentStep);
+            } else
+            {
+                for (size_t i = 0 ; i < m_samplesInRecurrentStep; i++)
+                {
+                    // bool reset = (m_sentenceEnd[i] == timeIdxInSeq);
+                    bool reset = false;
+
+                    if ((((int)m_sentenceEnd[i] +(int)m_delay - 1) >= (int)timeIdxInSeq) && (m_sentenceEnd[i] <= timeIdxInSeq))
+                    {
+                        reset = true;
+                    }
+                    EvaluateThisNodeSRP(timeIdxInSeq, m_delay, reset, m_default_activity, m_functionValues, m_pastActivity, Inputs(0)->FunctionValues(), i, m_samplesInRecurrentStep);
+                }
+            }
+
+        }
+
+        static void WINAPI EvaluateThisNodeSR(const size_t timeIdxInSeq, const int delay, const bool reset, const ElemType default_activity, Matrix<ElemType>& functionValues, const Matrix<ElemType>& pastActivity, const Matrix<ElemType>& inputFunctionValues, const size_t mNbr)
+        {
+            ASSERT(delay > 0);
+
+            if (functionValues.GetNumRows() != inputFunctionValues.GetNumRows() ||
+                functionValues.GetNumCols() != inputFunctionValues.GetNumCols())
+                functionValues.Resize(inputFunctionValues.GetNumRows(),
+                    inputFunctionValues.GetNumCols());
+
+            int iPastIndex = (int) (timeIdxInSeq - delay) * mNbr;
+            int d = iPastIndex; 
+            if (d < 0)
+                d = (int)functionValues.Mod((float)iPastIndex, (float)pastActivity.GetNumCols());  
+           /// this can point to the past activity of the previous mninibatch
+
+            Matrix<ElemType> out = functionValues.ColumnSlice(timeIdxInSeq * mNbr, mNbr);
+            Matrix<ElemType> inp((DEVICEID_TYPE)functionValues.GetDeviceId()) ;
+
+            if (reset)
+                out.SetValue(default_activity);
+            else
+            {
+                if (iPastIndex < 0)
+                    inp = pastActivity.ColumnSlice(d, mNbr);
+                else
+                    inp = inputFunctionValues.ColumnSlice(d, mNbr);
+                out.SetValue(inp);
+            }
+        }
+
+        static void WINAPI EvaluateThisNodeSRP(const size_t timeIdxInSeq, const int delay, const bool reset, const ElemType default_activity, Matrix<ElemType>& functionValues, const Matrix<ElemType>& pastActivity, const Matrix<ElemType>& inputFunctionValues, const size_t indexInBatch, const size_t mNbr)
+        {
+            ASSERT(delay > 0);
+
+            if (functionValues.GetNumRows() != inputFunctionValues.GetNumRows() ||
+                functionValues.GetNumCols() != inputFunctionValues.GetNumCols())
+                functionValues.Resize(inputFunctionValues.GetNumRows(),
+                    inputFunctionValues.GetNumCols());
+
+            int iPastIndex = (int) (timeIdxInSeq - delay) * mNbr;
+            int d = iPastIndex; 
+            if (d < 0)
+                d = (int)functionValues.Mod((float)iPastIndex, (float)pastActivity.GetNumCols());  
+            /// this can point to the past activity of the previous mninibatch
+
+            Matrix<ElemType> out = functionValues.ColumnSlice(timeIdxInSeq * mNbr+indexInBatch, 1);
+            Matrix<ElemType> inp((DEVICEID_TYPE)functionValues.GetDeviceId()) ;
+
+            if (reset)
+                out.SetValue(default_activity);
+            else
+            {
+                if (iPastIndex < 0)
+                    inp = pastActivity.ColumnSlice(d+indexInBatch, 1);
+                else
+                    inp = inputFunctionValues.ColumnSlice(d+indexInBatch, 1);
+                out.SetValue(inp);
+            }
+        }
+
+
+
+        virtual const Matrix<ElemType>& FunctionValues() const 
+        {
+            return m_functionValues;
+        }
+
+        virtual Matrix<ElemType>& FunctionValues() 
+        {
+            return m_functionValues;
+        }
+
+        virtual void Validate()
+        {
+            PrintSelfBeforeValidation(true/*allowNulls*/);
+
+            if (m_children.size() != 1) 
+                throw std::logic_error("Delay operation should have one input.");
+
+            if (!(Inputs(0) == nullptr))
+            {
+                size_t rows0 = Inputs(0)->FunctionValues().GetNumRows(), cols0 = Inputs(0)->FunctionValues().GetNumCols();
+
+                if (rows0 > 0 && cols0 > 0) FunctionValues().Resize(rows0, cols0);
+            }
+            CopyImageSizeFromInputs(); 
+        }
+
+        virtual void AttachInputs(const ComputationNodePtr inputNode) 
+        {
+            m_children.resize(1);
+            m_children[0] = inputNode;
+        }
+
+        void SetDelay(const int val)
+        {
+            if (val <= 0)
+                throw std::logic_error("Delay must be > 0.");
+            m_delay = val;
+        }
+
+        virtual void MoveMatricesToDevice(const DEVICEID_TYPE deviceId)
+        {
+            ComputationNode<ElemType>::MoveMatricesToDevice(deviceId);
+
+            if (deviceId != AUTOPLACEMATRIX)
+            {
+                if (m_functionValues.GetDeviceId() != deviceId)
+                    m_functionValues.TransferFromDeviceToDevice(m_functionValues.GetDeviceId(), deviceId);
+                if (m_pastActivity.GetDeviceId() != deviceId)
+                    m_pastActivity.TransferFromDeviceToDevice(m_pastActivity.GetDeviceId(), deviceId, true);
+            }
+        }
+
+        static const std::wstring TypeName() {return L"Delay";} 
+
+        virtual void CopyTo(const ComputationNodePtr nodeP, const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            ComputationNode<ElemType>::CopyTo(nodeP, newName, flags);
+            DelayNode<ElemType>* node = (DelayNode<ElemType>*) nodeP;
+
+            if (flags & CopyNodeFlags::copyNodeValue)
+            {
+                node->m_delay = m_delay;
+                node->m_Reset = m_Reset;
+                node->m_default_activity = m_default_activity;
+                node->m_pastActivity = m_pastActivity;
+            }
+        }
+
+        // copy constructor
+        DelayNode(const DelayNode<ElemType>* node, const std::wstring& newName, const CopyNodeFlags flags)
+            : ComputationNode<ElemType>(node->m_deviceId), m_pastActivity(node->m_deviceId)
+        {
+            node->CopyTo(this, newName, flags);
+        }
+
+        virtual ComputationNodePtr Duplicate(const std::wstring& newName, const CopyNodeFlags flags) const
+        {
+            const std::wstring& name = (newName == L"")?NodeName():newName;
+                
+            ComputationNodePtr node = new DelayNode<ElemType>(this, name, flags);
+            return node;
+        }
+
+    private:
+        Matrix<ElemType> m_pastActivity;  /// saves the past activity this delay node points to
+        int      m_delay;    /// steps for delay 
+        bool     m_Reset; 
+
+    };
+
+    template class DelayNode<float>; 
+    template class DelayNode<double>;
+
+}}}
diff --git a/MachineLearning/CNTK/SimpleEvaluator.h b/MachineLearning/CNTK/SimpleEvaluator.h
index 10efd000d..3d8308a5b 100644
--- a/MachineLearning/CNTK/SimpleEvaluator.h
+++ b/MachineLearning/CNTK/SimpleEvaluator.h
@@ -5,16 +5,16 @@
 //
 #pragma once
 
-#include "ComputationNetwork.h"
-#include "ComputationNetworkHelper.h"
-#include "DataReader.h"
 #include <vector>
 #include <string>
 #include <stdexcept>
+#include <fstream>
+
 #include "Basics.h"
 #include "fileutil.h"
-#include "commandArgUtil.h"
-#include <fstream>
+
+#include "ComputationNetwork.h"
+#include "ComputationNetworkHelper.h"
 
 using namespace std;
 
diff --git a/MachineLearning/CNTK/SimpleNetworkBuilder.cpp b/MachineLearning/CNTK/SimpleNetworkBuilder.cpp
index 85a68b3b2..2c800cf84 100644
--- a/MachineLearning/CNTK/SimpleNetworkBuilder.cpp
+++ b/MachineLearning/CNTK/SimpleNetworkBuilder.cpp
@@ -7,6 +7,12 @@
 #define _CRT_SECURE_NO_WARNINGS // "secure" CRT not available on all platforms  --add this at the top of all CPP files that give "function or variable may be unsafe" warnings
 
 #include "ComputationNode.h"
+#include "InputAndParamNodes.h"
+#include "LinearAlgebraNodes.h"
+#include "NonlinearityNodes.h"
+#include "ConvolutionalNodes.h"
+#include "RecurrentNodes.h"
+
 #include "SimpleEvaluator.h"
 #include "IComputationNetBuilder.h"
 #include "SGD.h"
diff --git a/MachineLearning/CNTK/SimpleNetworkBuilder.h b/MachineLearning/CNTK/SimpleNetworkBuilder.h
index c808fe8c5..64cb7f45d 100644
--- a/MachineLearning/CNTK/SimpleNetworkBuilder.h
+++ b/MachineLearning/CNTK/SimpleNetworkBuilder.h
@@ -5,16 +5,18 @@
 //
 #pragma once
 
-#include "Basics.h"
-#include "ComputationNetwork.h"
-#include "IComputationNetBuilder.h"
-#include <string>
-#include "commandArgUtil.h"
-#include "Matrix.h"
 #include <stdexcept>
 #include <regex>
+#include <string>
+
+#include "Basics.h"
+#include "Matrix.h"
 #include "BestGpu.h"
 
+#include "ComputationNetwork.h"
+#include "IComputationNetBuilder.h"
+#include "commandArgUtil.h"
+
 #pragma warning (disable: 4661)
 
 using namespace std;
diff --git a/MachineLearning/CNTK/tests.cpp b/MachineLearning/CNTK/tests.cpp
index d1e61b2a4..4fc017681 100644
--- a/MachineLearning/CNTK/tests.cpp
+++ b/MachineLearning/CNTK/tests.cpp
@@ -6,19 +6,20 @@
 // cn.cpp : Defines the entry point for the console application.
 //
 
+#define _CRT_SECURE_NO_WARNINGS // "secure" CRT not available on all platforms  --add this at the top of all CPP files that give "function or variable may be unsafe" warnings
+
 #include "stdafx.h"
+#include <string>
+#include <chrono>
+
 #include "Basics.h"
 #include "ComputationNetwork.h"
-#include "ComputationNode.h"
 #include "DataReader.h"
 #include "SimpleNetworkBuilder.h"
 #include "SGD.h"
-#include <string>
-#include "commandArgUtil.h"
 #include "SimpleEvaluator.h"
 #include "NetworkDescriptionLanguage.h"
 #include "SynchronousExecutionEngine.h"
-#include <chrono>
 
 using namespace std;
 using namespace Microsoft::MSR::CNTK;
@@ -558,4 +559,3 @@ void GenerateTemplates()
     TestCn<float>(config);
     TestCn<double>(config);
 }
-
diff --git a/MachineLearning/CNTKEval/CNTKEval.cpp b/MachineLearning/CNTKEval/CNTKEval.cpp
index 0e8d1925c..1e11c8a13 100644
--- a/MachineLearning/CNTKEval/CNTKEval.cpp
+++ b/MachineLearning/CNTKEval/CNTKEval.cpp
@@ -10,7 +10,6 @@
 #define EVAL_EXPORTS  // creating the exports here
 #include "Eval.h"
 #include "CNTKEval.h"
-#include "commandArgUtil.h"
 #include "SimpleOutputWriter.h"
 #ifdef LEAKDETECT
 #include <vld.h> // leak detection
@@ -171,4 +170,4 @@ void CNTKEval<ElemType>::ResetState()
 // instantiate all the combinations we expect to be used
 template class CNTKEval<double>; 
 template class CNTKEval<float>;
-}}}
\ No newline at end of file
+}}}
diff --git a/MachineLearning/CNTKEval/CNTKEval.h b/MachineLearning/CNTKEval/CNTKEval.h
index 86f4e6aaf..bbb759855 100644
--- a/MachineLearning/CNTKEval/CNTKEval.h
+++ b/MachineLearning/CNTKEval/CNTKEval.h
@@ -5,12 +5,15 @@
 //
 // CNTKEval.h - Include file for the CNTK Evaluation DLL 
 #pragma once
-#include "Eval.h"
+
 #include <string>
 #include <map>
 #include <vector>
+
+#include "Eval.h"
 #include "EvalReader.h"
 #include "EvalWriter.h"
+
 #include "ComputationNetwork.h"
 
 namespace Microsoft { namespace MSR { namespace CNTK {
diff --git a/Math/Math/GPUMatrix.cu b/Math/Math/GPUMatrix.cu
index 7a318ede2..fd01aa342 100644
--- a/Math/Math/GPUMatrix.cu
+++ b/Math/Math/GPUMatrix.cu
@@ -1837,7 +1837,7 @@ namespace Microsoft { namespace MSR { namespace CNTK {
         assert(GetNumRows() == a.GetNumRows());
         assert(GetNumCols() == b.GetNumRows());
         assert(a.GetNumCols() == b.GetNumRows());
-        c;  // TODO: this function seems like a stub
+        a; b; c;  // TODO: this function seems like a stub
         /*
         EnsureAuxMemory();
         int p = 512;

From e0695841682a00b8bdacd4b8bf29129409a942da Mon Sep 17 00:00:00 2001
From: Frank Seide <fseide@microsoft.com>
Date: Mon, 18 May 2015 23:51:46 -0700
Subject: [PATCH 39/49] removed the Setups Solution folder for now, since it
 cannot be easily populated with VS

---
 CNTK.sln | 4 +---
 1 file changed, 1 insertion(+), 3 deletions(-)

diff --git a/CNTK.sln b/CNTK.sln
index 8fbbf9482..5f28bd300 100644
--- a/CNTK.sln
+++ b/CNTK.sln
@@ -151,8 +151,6 @@ Project("{2150E333-8FDC-42A3-9474-1A3956D46DE8}") = "figures", "figures", "{889C
 		Documentation\CNTK-TechReport\figures\SpeechErrorRate.png = Documentation\CNTK-TechReport\figures\SpeechErrorRate.png
 	EndProjectSection
 EndProject
-Project("{2150E333-8FDC-42A3-9474-1A3956D46DE8}") = "Setups", "Setups", "{0D19A753-D8FE-4F23-8C6F-E111AF396D7B}"
-EndProject
 Project("{2150E333-8FDC-42A3-9474-1A3956D46DE8}") = "Other", "Other", "{39E42C4B-A078-4CA4-9D92-B883D8129601}"
 EndProject
 Global
@@ -233,12 +231,12 @@ Global
 		{9A2F2441-5972-4EA8-9215-4119FCE0FB68} = {33EBFE78-A1A8-4961-8938-92A271941F94}
 		{014DA766-B37B-4581-BC26-963EA5507931} = {33EBFE78-A1A8-4961-8938-92A271941F94}
 		{D667AF32-028A-4A5D-BE19-F46776F0F6B2} = {33EBFE78-A1A8-4961-8938-92A271941F94}
+		{3ED0465D-23E7-4855-9694-F788717B6533} = {39E42C4B-A078-4CA4-9D92-B883D8129601}
 		{98D2C32B-0C1F-4E19-A626-65F7BA4600CF} = {065AF55D-AF02-448B-BFCD-52619FDA4BD0}
 		{EA67F51F-1FE8-462D-9F3E-01161685AD59} = {065AF55D-AF02-448B-BFCD-52619FDA4BD0}
 		{DE1A06BA-EC5C-4E0D-BCA8-3EA555310C58} = {065AF55D-AF02-448B-BFCD-52619FDA4BD0}
 		{63024704-A2D7-497E-AD4B-5C10C6AA1374} = {065AF55D-AF02-448B-BFCD-52619FDA4BD0}
 		{F9BEB27E-8AF5-464E-8D45-0000D5AFA2D3} = {EA67F51F-1FE8-462D-9F3E-01161685AD59}
 		{889C1CCF-92B3-450B-B00D-FC9A9D5BE464} = {EA67F51F-1FE8-462D-9F3E-01161685AD59}
-		{3ED0465D-23E7-4855-9694-F788717B6533} = {39E42C4B-A078-4CA4-9D92-B883D8129601}
 	EndGlobalSection
 EndGlobal

From 59dfc28a364ade50e2d78ac683de978e048fd0b1 Mon Sep 17 00:00:00 2001
From: Frank Seide <fseide@microsoft.com>
Date: Tue, 19 May 2015 00:04:33 -0700
Subject: [PATCH 40/49] fixed an incorrect ERRORLEVEL check in prebuild.bat

---
 MachineLearning/CNTK/prebuild.bat | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/MachineLearning/CNTK/prebuild.bat b/MachineLearning/CNTK/prebuild.bat
index acbb6ec36..392e4f062 100644
--- a/MachineLearning/CNTK/prebuild.bat
+++ b/MachineLearning/CNTK/prebuild.bat
@@ -33,5 +33,5 @@ echo #define _CUDA_PATH_    %cuda_path%     >> buildinfo.h$$
 echo #endif >> buildinfo.h$$
 
 ::: update file only if it changed (otherwise CNTK.cpp will get rebuilt each time)
-fc buildinfo.h$$ buildinfo.h > NUL
-if not ERRORLEVEL 0 move /Y buildinfo.h$$ buildinfo.h
+fc buildinfo.h$$ buildinfo.h > NUL 2>1
+if ERRORLEVEL 1 move /Y buildinfo.h$$ buildinfo.h

From 94a262cf4238aeb2799ed036f88fef746e7a5673 Mon Sep 17 00:00:00 2001
From: Dong Yu <dongyu@microsoft.com>
Date: Tue, 19 May 2015 00:10:37 -0700
Subject: [PATCH 41/49] resolve merge conflict.

---
 Math/Math/Matrix.h | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/Math/Math/Matrix.h b/Math/Math/Matrix.h
index 36b1c4ae4..31605f465 100644
--- a/Math/Math/Matrix.h
+++ b/Math/Math/Matrix.h
@@ -150,7 +150,7 @@ namespace Microsoft { namespace MSR { namespace CNTK {
 
         Matrix<ElemType>& AssignNceUnnormalizedEval(const Matrix<ElemType>& a, const Matrix<ElemType>& b, const Matrix<ElemType>& c);
 
-        Matrix<ElemType> Transpose();
+        Matrix<ElemType> Transpose(); // This method doesn't change state of Matrix. It should be a const function
         Matrix<ElemType>& AssignTransposeOf (const Matrix<ElemType>& a);
 
         Matrix<ElemType>& operator+= (const ElemType alpha);

From ade0a60c11131d9c851a5104b19064d0c4c260da Mon Sep 17 00:00:00 2001
From: Frank Seide <fseide@microsoft.com>
Date: Tue, 19 May 2015 00:10:45 -0700
Subject: [PATCH 42/49] (added a missing & in a redirect in prebuild.bat)

---
 MachineLearning/CNTK/prebuild.bat | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/MachineLearning/CNTK/prebuild.bat b/MachineLearning/CNTK/prebuild.bat
index 392e4f062..39daf7b85 100644
--- a/MachineLearning/CNTK/prebuild.bat
+++ b/MachineLearning/CNTK/prebuild.bat
@@ -33,5 +33,5 @@ echo #define _CUDA_PATH_    %cuda_path%     >> buildinfo.h$$
 echo #endif >> buildinfo.h$$
 
 ::: update file only if it changed (otherwise CNTK.cpp will get rebuilt each time)
-fc buildinfo.h$$ buildinfo.h > NUL 2>1
+fc buildinfo.h$$ buildinfo.h > NUL 2>&1
 if ERRORLEVEL 1 move /Y buildinfo.h$$ buildinfo.h

From 89ea3f344855c9a730452141b71af41adc3fcfef Mon Sep 17 00:00:00 2001
From: Frank Seide <fseide@microsoft.com>
Date: Tue, 19 May 2015 00:24:08 -0700
Subject: [PATCH 43/49] replaced printf format %ws by %ls which is portable
 between Visual Studio and gcc

---
 DataReader/DSSMReader/DSSMReader.cpp             |  4 ++--
 DataReader/HTKMLFReader/HTKMLFReader.cpp         |  6 +++---
 DataReader/LMSequenceReader/SequenceReader.cpp   |  4 ++--
 DataReader/LUSequenceReader/LUSequenceReader.cpp |  6 +++---
 .../LibSVMBinaryReader/LibSVMBinaryReader.cpp    |  4 ++--
 DataReader/UCIFastReader/UCIFastReader.cpp       | 10 +++++-----
 MachineLearning/CNTK/CompositeComputationNodes.h |  2 +-
 MachineLearning/CNTK/SGD.h                       |  4 ++--
 .../CNTK/SynchronousExecutionEngine.h            | 16 ++++++++--------
 9 files changed, 28 insertions(+), 28 deletions(-)

diff --git a/DataReader/DSSMReader/DSSMReader.cpp b/DataReader/DSSMReader/DSSMReader.cpp
index a1de611d3..dee6c8ee8 100644
--- a/DataReader/DSSMReader/DSSMReader.cpp
+++ b/DataReader/DSSMReader/DSSMReader.cpp
@@ -94,12 +94,12 @@ void DSSMReader<ElemType>::WriteLabelFile()
             {
                 labelFile << m_mapIdToLabel[i] << '\n';
             }
-            fprintf(stderr, "label file %ws written to disk\n", m_labelFileToWrite.c_str());
+            fprintf(stderr, "label file %ls written to disk\n", m_labelFileToWrite.c_str());
             m_labelFileToWrite.clear();
         }
         else if (!m_cachingWriter)
         {
-            fprintf(stderr, "WARNING: file %ws NOT written to disk yet, will be written the first time the end of the entire dataset is found.\n", m_labelFileToWrite.c_str());
+            fprintf(stderr, "WARNING: file %ls NOT written to disk yet, will be written the first time the end of the entire dataset is found.\n", m_labelFileToWrite.c_str());
         }
     }
 }
diff --git a/DataReader/HTKMLFReader/HTKMLFReader.cpp b/DataReader/HTKMLFReader/HTKMLFReader.cpp
index 52d4bb873..372cc6013 100644
--- a/DataReader/HTKMLFReader/HTKMLFReader.cpp
+++ b/DataReader/HTKMLFReader/HTKMLFReader.cpp
@@ -745,7 +745,7 @@ namespace Microsoft { namespace MSR { namespace CNTK {
             for (auto iter=matrices.begin();iter!=matrices.end();iter++)
             {
                 if (m_nameToTypeMap.find(iter->first)==m_nameToTypeMap.end())
-                    throw std::runtime_error(msra::strfun::strprintf("minibatch requested for input node %ws not found in reader - cannot generate input\n",iter->first.c_str()));
+                    throw std::runtime_error(msra::strfun::strprintf("minibatch requested for input node %ls not found in reader - cannot generate input\n",iter->first.c_str()));
 
             }
             m_checkDictionaryKeys=false;
@@ -1168,7 +1168,7 @@ namespace Microsoft { namespace MSR { namespace CNTK {
             {
                 if (matrices.find(iter->first)==matrices.end())
                 {
-                    fprintf(stderr,"GetMinibatchToWrite: feature node %ws specified in reader not found in the network\n",iter->first.c_str());
+                    fprintf(stderr,"GetMinibatchToWrite: feature node %ls specified in reader not found in the network\n",iter->first.c_str());
                     throw std::runtime_error("GetMinibatchToWrite: feature node specified in reader not found in the network.");
                 }
             }
@@ -1176,7 +1176,7 @@ namespace Microsoft { namespace MSR { namespace CNTK {
             for (auto iter=matrices.begin();iter!=matrices.end();iter++)
             {
                 if (m_featureNameToIdMap.find(iter->first)==m_featureNameToIdMap.end())
-                    throw std::runtime_error(msra::strfun::strprintf("minibatch requested for input node %ws not found in reader - cannot generate input\n",iter->first.c_str()));
+                    throw std::runtime_error(msra::strfun::strprintf("minibatch requested for input node %ls not found in reader - cannot generate input\n",iter->first.c_str()));
             }
             */
             m_checkDictionaryKeys=false;
diff --git a/DataReader/LMSequenceReader/SequenceReader.cpp b/DataReader/LMSequenceReader/SequenceReader.cpp
index 7fdda1cd5..75a862143 100644
--- a/DataReader/LMSequenceReader/SequenceReader.cpp
+++ b/DataReader/LMSequenceReader/SequenceReader.cpp
@@ -340,7 +340,7 @@ void SequenceReader<ElemType>::WriteLabelFile()
             }
             else if (!m_cachingWriter)
             {
-                //fprintf(stderr, "WARNING: file %ws NOT written to disk, label files only written when starting at epoch zero!", labelInfo.fileToWrite.c_str());
+                //fprintf(stderr, "WARNING: file %ls NOT written to disk, label files only written when starting at epoch zero!", labelInfo.fileToWrite.c_str());
                 std::wcerr << "WARNING: file " << labelInfo.fileToWrite.c_str() << " NOT written to disk, label files only written when starting at epoch zero!" << endl;
             }
         }
@@ -565,7 +565,7 @@ void SequenceReader<ElemType>::Init(const ConfigParameters& readerConfig)
     std::wstring m_file = readerConfig("file");
     if (m_traceLevel > 0)
     {
-        //fprintf(stderr, "reading sequence file %ws\n", m_file.c_str());
+        //fprintf(stderr, "reading sequence file %ls\n", m_file.c_str());
         std::wcerr << "reading sequence file" << m_file.c_str() << endl;
     }
 
diff --git a/DataReader/LUSequenceReader/LUSequenceReader.cpp b/DataReader/LUSequenceReader/LUSequenceReader.cpp
index 90fab0f28..e4ed27b08 100644
--- a/DataReader/LUSequenceReader/LUSequenceReader.cpp
+++ b/DataReader/LUSequenceReader/LUSequenceReader.cpp
@@ -163,7 +163,7 @@ void LUSequenceReader<ElemType>::WriteLabelFile()
             }
             else if (!m_cachingWriter)
             {
-                fprintf(stderr, "WARNING: file %ws NOT written to disk, label files only written when starting at epoch zero!", labelInfo.fileToWrite.c_str());
+                fprintf(stderr, "WARNING: file %ls NOT written to disk, label files only written when starting at epoch zero!", labelInfo.fileToWrite.c_str());
             }
         }
     }
@@ -385,7 +385,7 @@ void LUSequenceReader<ElemType>::Init(const ConfigParameters& readerConfig)
 
     std::wstring m_file = readerConfig("file");
     if (m_traceLevel > 0)
-        fprintf(stderr, "reading sequence file %ws\n", m_file.c_str());
+        fprintf(stderr, "reading sequence file %ls\n", m_file.c_str());
 
     const LabelInfo& labelIn = m_labelInfo[labelInfoIn];
     const LabelInfo& labelOut = m_labelInfo[labelInfoOut];
@@ -955,7 +955,7 @@ void BatchLUSequenceReader<ElemType>::Init(const ConfigParameters& readerConfig)
 
     std::wstring m_file = readerConfig("file");
     if (m_traceLevel > 0)
-        fprintf(stderr, "reading sequence file %ws\n", m_file.c_str());
+        fprintf(stderr, "reading sequence file %ls\n", m_file.c_str());
 
     const LabelInfo& labelIn = m_labelInfo[labelInfoIn];
     const LabelInfo& labelOut = m_labelInfo[labelInfoOut];
diff --git a/DataReader/LibSVMBinaryReader/LibSVMBinaryReader.cpp b/DataReader/LibSVMBinaryReader/LibSVMBinaryReader.cpp
index 3b0686ab1..041df80c8 100644
--- a/DataReader/LibSVMBinaryReader/LibSVMBinaryReader.cpp
+++ b/DataReader/LibSVMBinaryReader/LibSVMBinaryReader.cpp
@@ -94,12 +94,12 @@ void LibSVMBinaryReader<ElemType>::WriteLabelFile()
             {
                 labelFile << m_mapIdToLabel[i] << '\n';
             }
-            fprintf(stderr, "label file %ws written to disk\n", m_labelFileToWrite.c_str());
+            fprintf(stderr, "label file %ls written to disk\n", m_labelFileToWrite.c_str());
             m_labelFileToWrite.clear();
         }
         else if (!m_cachingWriter)
         {
-            fprintf(stderr, "WARNING: file %ws NOT written to disk yet, will be written the first time the end of the entire dataset is found.\n", m_labelFileToWrite.c_str());
+            fprintf(stderr, "WARNING: file %ls NOT written to disk yet, will be written the first time the end of the entire dataset is found.\n", m_labelFileToWrite.c_str());
         }
     }
 }
diff --git a/DataReader/UCIFastReader/UCIFastReader.cpp b/DataReader/UCIFastReader/UCIFastReader.cpp
index 461ba8de5..c9b8201ff 100644
--- a/DataReader/UCIFastReader/UCIFastReader.cpp
+++ b/DataReader/UCIFastReader/UCIFastReader.cpp
@@ -231,12 +231,12 @@ void UCIFastReader<ElemType>::WriteLabelFile()
             {
                 labelFile << m_mapIdToLabel[i] << '\n';
             }
-            fprintf(stderr, "label file %ws written to disk\n", m_labelFileToWrite.c_str());
+            fprintf(stderr, "label file %ls written to disk\n", m_labelFileToWrite.c_str());
             m_labelFileToWrite.clear();
         }
         else if (!m_cachingWriter)
         {
-            fprintf(stderr, "WARNING: file %ws NOT written to disk yet, will be written the first time the end of the entire dataset is found.\n", m_labelFileToWrite.c_str());
+            fprintf(stderr, "WARNING: file %ls NOT written to disk yet, will be written the first time the end of the entire dataset is found.\n", m_labelFileToWrite.c_str());
         }
     }
 }
@@ -381,7 +381,7 @@ void UCIFastReader<ElemType>::Init(const ConfigParameters& readerConfig)
 
     std::wstring file = configFeatures("file");
     if (m_traceLevel > 0)
-        fprintf(stderr, "reading uci file %ws\n", file.c_str());
+        fprintf(stderr, "reading uci file %ls\n", file.c_str());
 
     m_parser.ParseInit(file.c_str(), startFeatures, dimFeatures, startLabels, dimLabels);
 
@@ -409,7 +409,7 @@ void UCIFastReader<ElemType>::Init(const ConfigParameters& readerConfig)
             if (allowLabelCreation)
                 m_labelFileToWrite = labelPath;
             else
-                RuntimeError("label mapping file %ws not found, can be created with a 'createLabelMap' command/action\n", labelPath.c_str());
+                RuntimeError("label mapping file %ls not found, can be created with a 'createLabelMap' command/action\n", labelPath.c_str());
         }
     }
 
@@ -610,7 +610,7 @@ void UCIFastReader<ElemType>::SetupEpoch()
             m_parser.SetParseMode(ParseNormal);
             if (!m_labelFileToWrite.empty())
             {
-                fprintf(stderr, "WARNING: file %ws NOT written to disk, label file will only be written when starting epochs at the beginning of the dataset\n", m_labelFileToWrite.c_str());
+                fprintf(stderr, "WARNING: file %ls NOT written to disk, label file will only be written when starting epochs at the beginning of the dataset\n", m_labelFileToWrite.c_str());
                 m_labelFileToWrite.clear();
                 RuntimeError("LabelMappingFile not provided in config, must be provided if not starting from epoch Zero (0)");
             }
diff --git a/MachineLearning/CNTK/CompositeComputationNodes.h b/MachineLearning/CNTK/CompositeComputationNodes.h
index 53d27c606..237fd02fb 100644
--- a/MachineLearning/CNTK/CompositeComputationNodes.h
+++ b/MachineLearning/CNTK/CompositeComputationNodes.h
@@ -753,7 +753,7 @@ namespace Microsoft { namespace MSR { namespace CNTK {
             WCHAR str[BUFLEN];
             swprintf(str, BUFLEN, L"[%lu,%lu]  ", FunctionValues().GetNumRows(), FunctionValues().GetNumCols());
             fstream << wstring(str);
-            swprintf(str, BUFLEN, L"HasComputed=%ws", HasComputed() ? L"true" : L"false");
+            swprintf(str, BUFLEN, L"HasComputed=%ls", HasComputed() ? L"true" : L"false");
             fstream << wstring(str);
 
             PrintNodeValuesToFile(printValues, fstream);
diff --git a/MachineLearning/CNTK/SGD.h b/MachineLearning/CNTK/SGD.h
index e48f83212..8d6ebe0df 100644
--- a/MachineLearning/CNTK/SGD.h
+++ b/MachineLearning/CNTK/SGD.h
@@ -1416,8 +1416,8 @@ protected:
                     bool wrong = (std::isnan(diff) || diff > threshold);
                     if (wrong)
                     {
-                        fprintf(stderr, "\nd%ws Numeric gradient = %e, Error BP gradient = %e\n", node->NodeName().c_str(), eGradNum, eGradErr);
-                        sprintf(wstrtmp, "\nd%ws Numeric gradient = %e, Error BP gradient = %e\n", node->NodeName().c_str(), eGradNum, eGradErr);
+                        fprintf(stderr, "\nd%ls Numeric gradient = %e, Error BP gradient = %e\n", node->NodeName().c_str(), eGradNum, eGradErr);
+                        sprintf(wstrtmp, "\nd%ls Numeric gradient = %e, Error BP gradient = %e\n", node->NodeName().c_str(), eGradNum, eGradErr);
                         errMsgs.push_back(wstrtmp);
                     }
                 }
diff --git a/MachineLearning/CNTK/SynchronousExecutionEngine.h b/MachineLearning/CNTK/SynchronousExecutionEngine.h
index dc7d416ae..10eeaeecd 100644
--- a/MachineLearning/CNTK/SynchronousExecutionEngine.h
+++ b/MachineLearning/CNTK/SynchronousExecutionEngine.h
@@ -67,7 +67,7 @@ public:
         if (InputValue<ElemType>::TypeName() == cnNodeType)
         {
             if (parameter.size() < 1 || parameter.size() > 2)
-                RuntimeError("%ws should have 1 or 2 parameters[rows, [cols=1]].", cnNodeType.c_str());
+                RuntimeError("%ls should have 1 or 2 parameters[rows, [cols=1]].", cnNodeType.c_str());
 
             if (pass == ndlPassInitial)
             {
@@ -86,7 +86,7 @@ public:
         else if (SparseInputValue<ElemType>::TypeName() == cnNodeType)
         {
             if (parameter.size() < 1 || parameter.size() > 2)
-                RuntimeError("%ws should have 1 or 2 parameters[rows, [cols=1]].", cnNodeType.c_str());
+                RuntimeError("%ls should have 1 or 2 parameters[rows, [cols=1]].", cnNodeType.c_str());
 
             if (pass == ndlPassInitial)
             {
@@ -105,7 +105,7 @@ public:
         else if (cnNodeType == L"ImageInput")
         {
             if (parameter.size() < 3 || parameter.size() > 4)
-                RuntimeError("%ws should have 3 or 4 parameters[imageWidth, imageHeight, imageChannels, [numImages=1]].", cnNodeType.c_str());
+                RuntimeError("%ls should have 3 or 4 parameters[imageWidth, imageHeight, imageChannels, [numImages=1]].", cnNodeType.c_str());
 
             if (pass == ndlPassInitial)
             {
@@ -122,7 +122,7 @@ public:
         else if (LearnableParameter<ElemType>::TypeName() == cnNodeType)
         {
             if (parameter.size() < 1 || parameter.size() > 2)
-                RuntimeError("%ws should have 1 or 2 parameters[rows, [cols=1]] plus other optional parameters (needGradient=[true|false], init=[uniform|gaussian|fixedvalue], initValueScale=[1|float], value=[0|float]).", cnNodeType.c_str());
+                RuntimeError("%ls should have 1 or 2 parameters[rows, [cols=1]] plus other optional parameters (needGradient=[true|false], init=[uniform|gaussian|fixedvalue], initValueScale=[1|float], value=[0|float]).", cnNodeType.c_str());
 
             if (pass == ndlPassInitial)
             {
@@ -170,7 +170,7 @@ public:
         else if (SparseLearnableParameter<ElemType>::TypeName() == cnNodeType)
         {
             if (parameter.size() < 1 || parameter.size() > 2)
-                RuntimeError("%ws should have 1 or 2 parameters[rows, [cols=1]] plus other optional parameters (needGradient=[true|false], init=[uniform|gaussian|fixedvalue], initValueScale=[1|float], value=[0|float]).", cnNodeType.c_str());
+                RuntimeError("%ls should have 1 or 2 parameters[rows, [cols=1]] plus other optional parameters (needGradient=[true|false], init=[uniform|gaussian|fixedvalue], initValueScale=[1|float], value=[0|float]).", cnNodeType.c_str());
 
             if (pass == ndlPassInitial)
             {
@@ -283,7 +283,7 @@ public:
         else if (cnNodeType == ConvolutionNode<ElemType>::TypeName())
         {
             if (parameter.size() != 7)
-                RuntimeError("%ws should have 7 fixed parameters[weightNodeName, inputValueNodeName, kernelWidth, kernelHeight, outputChannels,horizontalSubsample, verticalSubsample] and two optional parameters [zeroPadding = [false|yourvalue], maxTempMemSizeInSamples = [0|yourvalue]].", cnNodeType.c_str());
+                RuntimeError("%ls should have 7 fixed parameters[weightNodeName, inputValueNodeName, kernelWidth, kernelHeight, outputChannels,horizontalSubsample, verticalSubsample] and two optional parameters [zeroPadding = [false|yourvalue], maxTempMemSizeInSamples = [0|yourvalue]].", cnNodeType.c_str());
 
             // setup the parameter position of children so we can hook them up later
             nodeParamCount = 2;
@@ -316,7 +316,7 @@ public:
         else if (cnNodeType == MaxPoolingNode<ElemType>::TypeName())
         {
             if (parameter.size() != 5)
-                RuntimeError("%ws should have 5 parameters[inputValueNodeName, windowWidth, windowHeight, horizontalSubsample, verticalSubsample].", cnNodeType.c_str());
+                RuntimeError("%ls should have 5 parameters[inputValueNodeName, windowWidth, windowHeight, horizontalSubsample, verticalSubsample].", cnNodeType.c_str());
 
             // setup the parameter position of children so we can hook them up later
             nodeParamCount = 1;
@@ -343,7 +343,7 @@ public:
         else if (cnNodeType == AveragePoolingNode<ElemType>::TypeName())
         {
             if (parameter.size() != 5)
-                RuntimeError("%ws should have 5 parameters[inputValueNodeName, windowWidth, windowHeight, horizontalSubsample, verticalSubsample].", cnNodeType.c_str());
+                RuntimeError("%ls should have 5 parameters[inputValueNodeName, windowWidth, windowHeight, horizontalSubsample, verticalSubsample].", cnNodeType.c_str());
 
             // setup the parameter position of children so we can hook them up later
             nodeParamCount = 1;

From 61c6d59e04185670737142fbda2573cb87ef850d Mon Sep 17 00:00:00 2001
From: erw <erw@microsoft.com>
Date: Tue, 7 Apr 2015 14:45:23 -0700
Subject: [PATCH 44/49] add a unit test for CNTKEval

This unit test is used privately by erw.

Conflicts:
	CNTKSolution/EvalUnitTest/CNTKEValTest.cpp
	CNTKSolution/EvalUnitTest/EvalUnitTest.vcxproj
	CNTKSolution/EvalUnitTest/EvalUnitTest.vcxproj.filters
---
 .gitignore                                    |   5 +-
 CNTKSolution/EvalUnitTest/CNTKEValTest.cpp    | 243 ++++++++++++++++++
 .../EvalUnitTest/EvalUnitTest.vcxproj         | 162 ++++++++++++
 .../EvalUnitTest/EvalUnitTest.vcxproj.filters |   7 +
 DataReader/HTKMLFReader/htkfeatio.h           |  11 +
 5 files changed, 427 insertions(+), 1 deletion(-)
 create mode 100644 CNTKSolution/EvalUnitTest/CNTKEValTest.cpp
 create mode 100644 CNTKSolution/EvalUnitTest/EvalUnitTest.vcxproj
 create mode 100644 CNTKSolution/EvalUnitTest/EvalUnitTest.vcxproj.filters

diff --git a/.gitignore b/.gitignore
index 33b05dbe7..72a41c51f 100644
--- a/.gitignore
+++ b/.gitignore
@@ -173,4 +173,7 @@ core
 # =========================
 MachineLearning/cn/buildinfo.h
 
-
+# =========================
+# AutoTest resource 
+# =========================
+AutoTest/
diff --git a/CNTKSolution/EvalUnitTest/CNTKEValTest.cpp b/CNTKSolution/EvalUnitTest/CNTKEValTest.cpp
new file mode 100644
index 000000000..720bf09bd
--- /dev/null
+++ b/CNTKSolution/EvalUnitTest/CNTKEValTest.cpp
@@ -0,0 +1,243 @@
+
+
+#include "CppUnitTest.h"
+#include "Eval.h"
+#include "../../DataReader/HTKMLFReader/htkfeatio.h"
+#include <memory>
+#include <string>
+#include <vector>
+
+
+using namespace Microsoft::VisualStudio::CppUnitTestFramework;
+using namespace std;
+using namespace Microsoft::MSR::CNTK;
+using msra::asr::htkfeatreader;
+
+typedef void(*GetEvalProc)(IEvaluateModel<float>** peval);
+
+namespace EvalUnitTest
+{
+    class HTKUtteranceReader    // designed for read one utterance 
+    {
+    public:
+        HTKUtteranceReader() : m_verbosity(0), m_contextWindow(5), m_frameshift(0){
+
+        }
+        void SetContextWindow(size_t windowSize) { m_contextWindow = windowSize; }
+        void SetFrameShift(int shift){ m_frameshift = shift;    }
+        size_t  GetUtteranceData(wstring filename, vector<float>& utterance)
+            // for a D (dim) X N (frame) utterance (specified by filename) and a window size H 
+            // utterance returns a D*(2*H+1) * N vector 
+            // caller don't need to resize utterance 
+        {
+
+            //========================================
+            // Sec. 1 get basic info 
+            //========================================
+            htkfeatreader reader; 
+            htkfeatreader::parsedpath path(filename);
+            
+            string featKind; 
+            size_t featDim; 
+            size_t nframes;
+            unsigned int featPeriod = 0; 
+            reader.getinfo(path, featKind, featDim, featPeriod, nframes);
+
+            //========================================
+            // Sec. 2 resize output vector 
+            //========================================
+            size_t expandedDim = (2 * m_contextWindow + 1) * featDim;       // dimension after contex expanding 
+            size_t totalDim = expandedDim * nframes;                        // dimension of the vector we want to feed to CNTK eval
+            utterance.resize(totalDim, 0.0f);
+            //========================================
+            // Sec. 3 get the feature matrix 
+            //========================================
+            vector<vector<float> > featMatrix;
+            featMatrix.resize(nframes);
+            for (size_t n = 0; n < nframes; n++)
+            {
+                reader.read(featMatrix[n]);
+            }
+            //========================================
+            // Sec. 4 context expansion
+            //========================================
+            if (m_contextWindow > 0)
+            {
+                vector<float>  expandedfeat;
+                expandedfeat.resize(expandedDim);
+
+                for (size_t n = 0; n < nframes; n++)
+                {
+                    
+                    size_t despos = 0; 
+                    for (size_t ileft = m_contextWindow-1; ileft >=0; ileft--, despos ++ )
+                    {
+                        size_t srcpos = max(n - ileft, 0);                         
+                        copy(featMatrix[srcpos].begin(), featMatrix[srcpos].end(), expandedfeat.begin() + featDim *despos);
+                    }
+                    for (size_t iRight = 1; iRight < m_contextWindow; iRight++, despos++)
+                    {
+                        size_t srcpos = min(n + iRight, nframes);
+                        copy(featMatrix[srcpos].begin(), featMatrix[srcpos].end(), expandedfeat.begin() + featDim *despos); 
+                    }
+                    copy(expandedfeat.begin(), expandedfeat.end(), utterance.begin() + expandedDim*n);
+                }
+            }
+            else
+            {
+                size_t idx = 0;
+                for (auto v : featMatrix)
+                {
+                    copy(v.begin(), v.end(), utterance.begin() + expandedDim*idx);
+                    idx++;
+                }
+            }
+
+
+
+            //========================================
+            // Sec. 5 frame shift 
+            //========================================
+            if (m_frameshift > 0)
+            {
+                assert(m_frameshift < nframes);  // TODO: throw an exception
+                /*
+                for (size_t f = m_frameshift; f < nframes; f++)
+                {
+                    copy(featMatrix[f].begin(), featMatrix[f].end(), utterance.begin() + (f-m_frameshift)*expandedDim);
+                }
+                for (size_t r = 0; r < m_frameshift; r++)
+                {
+                    copy(featMatrix[nframes - 1].begin(), featMatrix[nframes - 1].end(), utterance.begin()+(nframes-m_frameshift+r)*expandedDim );
+                }*/
+                for (size_t ipos = nframes - m_frameshift -1; ipos >= 0; ipos++)
+                {
+                    auto src = utterance.begin() + ipos * expandedDim;
+                    auto des = src + (m_frameshift)*expandedDim;
+                    copy(src, src + expandedDim, des);
+                }
+
+                auto src = utterance.begin() + m_frameshift*expandedDim;
+                for (size_t ipos = 0; ipos < m_frameshift; ipos++)
+                {
+                    auto des = utterance.begin() + ipos * expandedDim;
+                    copy(src, src + expandedDim, des);
+                }
+            }
+            return nframes;
+
+        }
+
+    private: 
+        size_t m_contextWindow;         // =5 means 5:1:5 TODO support asymmetric context window
+        size_t m_verbosity; 
+        short  m_frameshift;            // f>0  means x[0..n-1] -> [ x[f..n-1], x[n-1], ... ] 
+                                        // f<0  means x[0..n-1] -> [ x[0], x[0],... x[f..n-1] ] 
+                                        // frameshift is applied after context windows expansion 
+    };
+
+
+
+    TEST_CLASS(CNTKEvalUnitTest)
+    {
+    private:
+        bool LoadEvalutor()
+        {
+            try
+            {
+                Plugin plug;
+                GetEvalProc p_Processor = (GetEvalProc)plug.Load(m_strEvalModule, m_strGetEvalProcessor);
+                IEvaluateModel<float>* pEval = nullptr;
+                p_Processor(&pEval);
+                m_pEval.reset(pEval);
+            }
+            catch (std::exception& e)
+            {
+                printf("ERROR: %s\n", e.what());
+                Assert::Fail(L"Load Module failed");
+            }
+            return true;
+        }
+
+    public:
+        TEST_CLASS_INITIALIZE(ConfigEvalUnitTest)
+        {
+
+        }
+
+        TEST_METHOD(LoadModule)
+        {
+            Assert::IsTrue(LoadEvalutor());
+        }
+
+        TEST_METHOD(RNNModelTest)
+        {
+            Assert::IsTrue(LoadEvalutor());
+            m_pEval->Init("deviceID=-1");
+            m_pEval->LoadModel(m_strRNNModel);
+
+            //========================================
+            // Sec. 1 query node dimension
+            //========================================
+            map<wstring, size_t> inputDimensions;
+            m_pEval->GetNodeDimensions(inputDimensions, nodeInput);
+            map<wstring, size_t> outputDimensions; 
+            m_pEval->GetNodeDimensions(outputDimensions, nodeOutput);
+
+            //========================================
+            // Sec. 2 load in feature files and expected output files 
+            //========================================            
+            HTKUtteranceReader reader; 
+            reader.SetFrameShift(0);
+            reader.SetContextWindow(0);
+            vector<float> utterData; 
+            size_t nframe=reader.GetUtteranceData(m_strRNNModelInputOutputPairs.first, utterData);
+            vector<float> expectedRes;
+            size_t nframeLLR = reader.GetUtteranceData(m_strRNNModelInputOutputPairs.second, expectedRes);
+            Assert::AreEqual(nframe, nframeLLR, L"ERROR: number of input feature vectors mismatched with the number of output vectors");
+
+            //========================================
+            // Sec. 3 setup inputs and outputs 
+            //========================================
+            Assert::IsTrue(inputDimensions.find(L"features") != inputDimensions.end());
+            Assert::IsTrue(outputDimensions.find(L"ScaledLogLikelihood") != outputDimensions.end());
+
+            map<wstring, vector<float>* > inputs; 
+            inputs[L"features"] = &utterData;
+            map<wstring, vector<float>* > outputs; 
+            size_t outputDim = nframe * outputDimensions[L"ScaledLogLikelihood"];
+            vector<float> outputData(outputDim,0.0f);
+            outputs[L"ScaledLogLikelihood"] = &outputData;
+            m_pEval->Evaluate(inputs, outputs);
+
+            //========================================
+            // Sec. 4 CompareResults 
+            //========================================
+            wstring msg = msra::strfun::wstrprintf(L"Output dimensions (%d vs %d) do not match", outputs.size(), expectedRes.size());
+            Assert::AreEqual(expectedRes.size(), outputs[L"ScaledLogLikelihood"]->size(), L"Output dimension does not match");
+            
+            for (size_t i = 0; i < expectedRes.size(); i++)
+            {
+                Assert::AreEqual(expectedRes[i], (*outputs[L"ScaledLogLikelihood"])[i], 0.01f);
+            }
+
+        }
+
+
+    private:
+        shared_ptr<IEvaluateModel<float>>   m_pEval;
+        static const wstring    m_strEvalModule;
+        static const  string    m_strGetEvalProcessor;
+        static const wstring    m_strRNNModel; 
+        static const pair<wstring, wstring>   m_strRNNModelInputOutputPairs;
+
+
+    };
+
+    const wstring  CNTKEvalUnitTest::m_strEvalModule = L"CNTKEval";           // the module (.dll) name 
+    const  string  CNTKEvalUnitTest::m_strGetEvalProcessor = "GetEvalF";     // which function to get eval 
+    const wstring  CNTKEvalUnitTest::m_strRNNModel = L"..\\..\\..\\AutoTest\\resources\\rnn.model.40";
+    const pair<wstring, wstring>  CNTKEvalUnitTest::m_strRNNModelInputOutputPairs = make_pair(L"..\\..\\..\\AutoTest\\resources\\LFB87dim.mfc", L"..\\..\\..\\AutoTest\\resources\\LFB87dim.pos");
+    
+
+}
\ No newline at end of file
diff --git a/CNTKSolution/EvalUnitTest/EvalUnitTest.vcxproj b/CNTKSolution/EvalUnitTest/EvalUnitTest.vcxproj
new file mode 100644
index 000000000..83da932f1
--- /dev/null
+++ b/CNTKSolution/EvalUnitTest/EvalUnitTest.vcxproj
@@ -0,0 +1,162 @@
+<?xml version="1.0" encoding="utf-8"?>
+<Project DefaultTargets="Build" ToolsVersion="12.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
+  <ItemGroup Label="ProjectConfigurations">
+    <ProjectConfiguration Include="Debug|Win32">
+      <Configuration>Debug</Configuration>
+      <Platform>Win32</Platform>
+    </ProjectConfiguration>
+    <ProjectConfiguration Include="Debug|x64">
+      <Configuration>Debug</Configuration>
+      <Platform>x64</Platform>
+    </ProjectConfiguration>
+    <ProjectConfiguration Include="Release|Win32">
+      <Configuration>Release</Configuration>
+      <Platform>Win32</Platform>
+    </ProjectConfiguration>
+    <ProjectConfiguration Include="Release|x64">
+      <Configuration>Release</Configuration>
+      <Platform>x64</Platform>
+    </ProjectConfiguration>
+  </ItemGroup>
+  <PropertyGroup Label="Globals">
+    <ProjectGuid>{4CBCD242-B40B-4A32-9648-DF9CD8CFFC8E}</ProjectGuid>
+    <Keyword>Win32Proj</Keyword>
+    <RootNamespace>EvalUnitTest</RootNamespace>
+  </PropertyGroup>
+  <Import Project="$(VCTargetsPath)\Microsoft.Cpp.Default.props" />
+  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'" Label="Configuration">
+    <ConfigurationType>DynamicLibrary</ConfigurationType>
+    <UseDebugLibraries>true</UseDebugLibraries>
+    <PlatformToolset>v120</PlatformToolset>
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+    <WholeProgramOptimization>true</WholeProgramOptimization>
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+  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'" Label="Configuration">
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+    <PlatformToolset>v120</PlatformToolset>
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+  <ImportGroup Label="ExtensionSettings">
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+    <Import Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" />
+  </ImportGroup>
+  <PropertyGroup Label="UserMacros" />
+  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">
+    <LinkIncremental>true</LinkIncremental>
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+  <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'">
+    <LinkIncremental>true</LinkIncremental>
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+    <LinkIncremental>true</LinkIncremental>
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+    <LinkIncremental>false</LinkIncremental>
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+  <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">
+    <ClCompile>
+      <PrecompiledHeader>Use</PrecompiledHeader>
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+      <Optimization>Disabled</Optimization>
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+      <PreprocessorDefinitions>WIN32;_DEBUG;%(PreprocessorDefinitions)</PreprocessorDefinitions>
+      <UseFullPaths>true</UseFullPaths>
+    </ClCompile>
+    <Link>
+      <SubSystem>Windows</SubSystem>
+      <GenerateDebugInformation>true</GenerateDebugInformation>
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+    </Link>
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+    <ClCompile>
+      <PrecompiledHeader>NotUsing</PrecompiledHeader>
+      <WarningLevel>Level3</WarningLevel>
+      <Optimization>Disabled</Optimization>
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+      <PreprocessorDefinitions>WIN32;_DEBUG;%(PreprocessorDefinitions)</PreprocessorDefinitions>
+      <UseFullPaths>true</UseFullPaths>
+      <AdditionalOptions>/D  _CRT_SECURE_NO_WARNINGS %(AdditionalOptions)</AdditionalOptions>
+    </ClCompile>
+    <Link>
+      <SubSystem>Windows</SubSystem>
+      <GenerateDebugInformation>true</GenerateDebugInformation>
+      <AdditionalLibraryDirectories>$(VCInstallDir)UnitTest\lib;%(AdditionalLibraryDirectories)</AdditionalLibraryDirectories>
+    </Link>
+  </ItemDefinitionGroup>
+  <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">
+    <ClCompile>
+      <WarningLevel>Level3</WarningLevel>
+      <PrecompiledHeader>Use</PrecompiledHeader>
+      <Optimization>MaxSpeed</Optimization>
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+      <IntrinsicFunctions>true</IntrinsicFunctions>
+      <AdditionalIncludeDirectories>$(VCInstallDir)UnitTest\include;%(AdditionalIncludeDirectories)</AdditionalIncludeDirectories>
+      <PreprocessorDefinitions>WIN32;NDEBUG;%(PreprocessorDefinitions)</PreprocessorDefinitions>
+      <UseFullPaths>true</UseFullPaths>
+    </ClCompile>
+    <Link>
+      <SubSystem>Windows</SubSystem>
+      <GenerateDebugInformation>true</GenerateDebugInformation>
+      <EnableCOMDATFolding>true</EnableCOMDATFolding>
+      <OptimizeReferences>true</OptimizeReferences>
+      <AdditionalLibraryDirectories>$(VCInstallDir)UnitTest\lib;%(AdditionalLibraryDirectories)</AdditionalLibraryDirectories>
+    </Link>
+  </ItemDefinitionGroup>
+  <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'">
+    <ClCompile>
+      <WarningLevel>Level3</WarningLevel>
+      <PrecompiledHeader>NotUsing</PrecompiledHeader>
+      <Optimization>MaxSpeed</Optimization>
+      <FunctionLevelLinking>true</FunctionLevelLinking>
+      <IntrinsicFunctions>true</IntrinsicFunctions>
+      <AdditionalIncludeDirectories>..\..\common\include;..\..\math\math;$(VCInstallDir)UnitTest\include;%(AdditionalIncludeDirectories)</AdditionalIncludeDirectories>
+      <PreprocessorDefinitions>WIN32;NDEBUG;%(PreprocessorDefinitions)</PreprocessorDefinitions>
+      <UseFullPaths>true</UseFullPaths>
+      <AdditionalOptions>/D  _CRT_SECURE_NO_WARNINGS %(AdditionalOptions)</AdditionalOptions>
+    </ClCompile>
+    <Link>
+      <SubSystem>Windows</SubSystem>
+      <GenerateDebugInformation>true</GenerateDebugInformation>
+      <EnableCOMDATFolding>true</EnableCOMDATFolding>
+      <OptimizeReferences>true</OptimizeReferences>
+      <AdditionalLibraryDirectories>$(VCInstallDir)UnitTest\lib;%(AdditionalLibraryDirectories)</AdditionalLibraryDirectories>
+    </Link>
+  </ItemDefinitionGroup>
+  <ItemGroup>
+    <ClCompile Include="..\..\Common\fileutil.cpp" />
+    <ClCompile Include="CNTKEValTest.cpp" />
+  </ItemGroup>
+  <Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
+  <ImportGroup Label="ExtensionTargets">
+  </ImportGroup>
+</Project>
\ No newline at end of file
diff --git a/CNTKSolution/EvalUnitTest/EvalUnitTest.vcxproj.filters b/CNTKSolution/EvalUnitTest/EvalUnitTest.vcxproj.filters
new file mode 100644
index 000000000..ab38f4ab4
--- /dev/null
+++ b/CNTKSolution/EvalUnitTest/EvalUnitTest.vcxproj.filters
@@ -0,0 +1,7 @@
+<?xml version="1.0" encoding="utf-8"?>
+<Project ToolsVersion="4.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
+  <ItemGroup>
+    <ClCompile Include="..\..\Common\fileutil.cpp" />
+    <ClCompile Include="CNTKEValTest.cpp" />
+  </ItemGroup>
+</Project>
\ No newline at end of file
diff --git a/DataReader/HTKMLFReader/htkfeatio.h b/DataReader/HTKMLFReader/htkfeatio.h
index 4d03525a3..917451e6e 100644
--- a/DataReader/HTKMLFReader/htkfeatio.h
+++ b/DataReader/HTKMLFReader/htkfeatio.h
@@ -516,6 +516,17 @@ public:
         featdim = this->featdim;
         featperiod = this->featperiod;
     }
+    
+    void getinfo (const parsedpath & ppath, string & featkind, size_t & featdim, unsigned int & featperiod, size_t& nframe)
+    {
+        open (ppath);
+        featkind = this->featkind;
+        featdim = this->featdim;
+        featperiod = this->featperiod;
+        nframe = this->numframes;
+    }
+
+
 
     // called to add energy as we read
     void AddEnergy(size_t energyElements)

From 64a37301f9ed513bad260a1cba9932796ed2d584 Mon Sep 17 00:00:00 2001
From: erw <erw@microsoft.com>
Date: Fri, 15 May 2015 11:21:20 -0700
Subject: [PATCH 45/49] Enable MPI_SUPPORT

---
 MachineLearning/CNTK/CNTK.vcxproj |   16 +-
 MachineLearning/CNTK/mpi/mpi.h    | 5937 +++++++++++++++++++++++++++++
 MachineLearning/cn/mpi/mpi.h      | 5937 +++++++++++++++++++++++++++++
 3 files changed, 11882 insertions(+), 8 deletions(-)
 create mode 100644 MachineLearning/CNTK/mpi/mpi.h
 create mode 100644 MachineLearning/cn/mpi/mpi.h

diff --git a/MachineLearning/CNTK/CNTK.vcxproj b/MachineLearning/CNTK/CNTK.vcxproj
index bb76f801c..b35b19492 100644
--- a/MachineLearning/CNTK/CNTK.vcxproj
+++ b/MachineLearning/CNTK/CNTK.vcxproj
@@ -72,15 +72,15 @@
       <SDLCheck>true</SDLCheck>
       <OpenMPSupport>true</OpenMPSupport>
       <TreatWarningAsError>true</TreatWarningAsError>
-      <AdditionalOptions>/bigobj %(AdditionalOptions)</AdditionalOptions>
-      <AdditionalIncludeDirectories>"c:\Program Files\NVIDIA Corporation\GDK\gdk_win7_amd64_release\nvml\include"</AdditionalIncludeDirectories>
+      <AdditionalOptions>/bigobj /D MPI_SUPPORT %(AdditionalOptions)</AdditionalOptions>
+      <AdditionalIncludeDirectories>"c:\Program Files\NVIDIA Corporation\GDK\gdk_win7_amd64_release\nvml\include";$(ProjectDir)\mpi</AdditionalIncludeDirectories>
     </ClCompile>
     <Link>
       <SubSystem>Console</SubSystem>
       <GenerateDebugInformation>true</GenerateDebugInformation>
       <AdditionalDependencies>CNTKMath.lib; nvml.lib; kernel32.lib; user32.lib; shell32.lib; %(AdditionalDependencies)</AdditionalDependencies>
-      <AdditionalLibraryDirectories>"c:\Program Files\NVIDIA Corporation\GDK\gdk_win7_amd64_release\nvml\lib"</AdditionalLibraryDirectories>
-      <DelayLoadDLLs>CNTKMath.dll; nvml.dll; cudart64_70.dll</DelayLoadDLLs>
+      <AdditionalLibraryDirectories>$(ProjectDir)/mpi/$(Platform); "c:\Program Files\NVIDIA Corporation\GDK\gdk_win7_amd64_release\nvml\lib" </AdditionalLibraryDirectories>
+      <DelayLoadDLLs>CNTKMath.dll;nvml.dll;nvcuda.dll; cudart64_70.dll</DelayLoadDLLs>
     </Link>
     <PostBuildEvent>
       <Command>xcopy /I /D /Y "%ProgramW6432%\NVIDIA Corporation\NVSMI\nvml*.dll" $(TargetDir)</Command>
@@ -110,9 +110,9 @@
       <PreprocessorDefinitions>WIN32;NDEBUG;_CONSOLE;%(PreprocessorDefinitions)</PreprocessorDefinitions>
       <SDLCheck>true</SDLCheck>
       <FavorSizeOrSpeed>Speed</FavorSizeOrSpeed>
-      <AdditionalOptions>/d2Zi+ %(AdditionalOptions)</AdditionalOptions>
+      <AdditionalOptions>/d2Zi+ /D MPI_SUPPORT %(AdditionalOptions)</AdditionalOptions>
       <TreatWarningAsError>true</TreatWarningAsError>
-      <AdditionalIncludeDirectories>"c:\Program Files\NVIDIA Corporation\GDK\gdk_win7_amd64_release\nvml\include"</AdditionalIncludeDirectories>
+      <AdditionalIncludeDirectories>"c:\Program Files\NVIDIA Corporation\GDK\gdk_win7_amd64_release\nvml\include"; $(ProjectDir)\mpi</AdditionalIncludeDirectories>
     </ClCompile>
     <Link>
       <SubSystem>Console</SubSystem>
@@ -122,7 +122,7 @@
       <AdditionalDependencies>CNTKMath.lib; nvml.lib; kernel32.lib; user32.lib; shell32.lib; %(AdditionalDependencies)</AdditionalDependencies>
       <Profile>true</Profile>
       <DelayLoadDLLs>CNTKMath.dll; nvml.dll; cudart64_70.dll</DelayLoadDLLs>
-      <AdditionalLibraryDirectories>"c:\Program Files\NVIDIA Corporation\GDK\gdk_win7_amd64_release\nvml\lib"</AdditionalLibraryDirectories>
+      <AdditionalLibraryDirectories>"c:\Program Files\NVIDIA Corporation\GDK\gdk_win7_amd64_release\nvml\lib"; $(ProjectDir)/mpi/$(Platform)</AdditionalLibraryDirectories>
     </Link>
     <PostBuildEvent>
       <Command>xcopy /I /D /Y "%ProgramW6432%\NVIDIA Corporation\NVSMI\nvml*.dll" $(TargetDir)</Command>
@@ -213,4 +213,4 @@
   </ItemGroup>
   <Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
   <ImportGroup Label="ExtensionTargets" />
-</Project>
\ No newline at end of file
+</Project>
diff --git a/MachineLearning/CNTK/mpi/mpi.h b/MachineLearning/CNTK/mpi/mpi.h
new file mode 100644
index 000000000..bd61200e7
--- /dev/null
+++ b/MachineLearning/CNTK/mpi/mpi.h
@@ -0,0 +1,5937 @@
+/*
+ *  (C) 2001 by Argonne National Laboratory.
+ *  (C) 2009 by Microsoft Corporation.
+ *      See COPYRIGHT in the SDK directory.
+ */
+
+#ifndef MPI_INCLUDED
+#define MPI_INCLUDED
+
+#if defined(__cplusplus)
+extern "C" {
+#endif
+
+
+#ifndef MSMPI_VER
+#define MSMPI_VER 0x100
+#endif
+
+
+/*---------------------------------------------------------------------------*/
+/* SAL ANNOTATIONS                                                           */
+/*---------------------------------------------------------------------------*/
+/*
+ * Define SAL annotations if they aren't defined yet.  Note that if we define
+ * them, we undefine them at the end of this file so that future inclusion of
+ * sal.h doesn't cause errors.
+ */
+#ifndef _In_
+#define MSMPI_DEFINED_SAL
+#define _In_
+#define _In_z_
+#define _In_opt_
+#define _In_count_( x )
+#define _In_bytecount_( x )
+#define _In_opt_count_( x )
+#define _Out_
+#define _Out_cap_( x )
+#define _Out_cap_post_count_( x, y )
+#define _Out_bytecap_( x )
+#define _Out_z_cap_( x )
+#define _Out_z_cap_post_count_( x, y )
+#define _Out_cap_post_part_( x, y )
+#define _Out_opt_
+#define _Out_opt_cap_( x )
+#define _Post_z_
+#define _Inout_
+#define _Inout_count_( x )
+#endif
+
+/*---------------------------------------------------------------------------*/
+/* MSMPI Calling convention                                                  */
+/*---------------------------------------------------------------------------*/
+
+#define MPIAPI __stdcall
+
+
+/*---------------------------------------------------------------------------*/
+/* MPI ERROR CLASS                                                           */
+/*---------------------------------------------------------------------------*/
+
+#define MPI_SUCCESS          0      /* Successful return code */
+
+#define MPI_ERR_BUFFER       1      /* Invalid buffer pointer */
+#define MPI_ERR_COUNT        2      /* Invalid count argument */
+#define MPI_ERR_TYPE         3      /* Invalid datatype argument */
+#define MPI_ERR_TAG          4      /* Invalid tag argument */
+#define MPI_ERR_COMM         5      /* Invalid communicator */
+#define MPI_ERR_RANK         6      /* Invalid rank */
+#define MPI_ERR_ROOT         7      /* Invalid root */
+#define MPI_ERR_GROUP        8      /* Invalid group */
+#define MPI_ERR_OP           9      /* Invalid operation */
+#define MPI_ERR_TOPOLOGY    10      /* Invalid topology */
+#define MPI_ERR_DIMS        11      /* Invalid dimension argument */
+#define MPI_ERR_ARG         12      /* Invalid argument */
+#define MPI_ERR_UNKNOWN     13      /* Unknown error */
+#define MPI_ERR_TRUNCATE    14      /* Message truncated on receive */
+#define MPI_ERR_OTHER       15      /* Other error; use Error_string */
+#define MPI_ERR_INTERN      16      /* Internal error code */
+#define MPI_ERR_IN_STATUS   17      /* Error code is in status */
+#define MPI_ERR_PENDING     18      /* Pending request */
+#define MPI_ERR_REQUEST     19      /* Invalid request (handle) */
+#define MPI_ERR_ACCESS      20      /* Premission denied */
+#define MPI_ERR_AMODE       21      /* Error related to amode passed to MPI_File_open */
+#define MPI_ERR_BAD_FILE    22      /* Invalid file name (e.g., path name too long) */
+#define MPI_ERR_CONVERSION  23      /* Error in user data conversion function */
+#define MPI_ERR_DUP_DATAREP 24      /* Data representation identifier already registered */
+#define MPI_ERR_FILE_EXISTS 25      /* File exists */
+#define MPI_ERR_FILE_IN_USE 26      /* File operation could not be completed, file in use */
+#define MPI_ERR_FILE        27      /* Invalid file handle */
+#define MPI_ERR_INFO        28      /* Invalid info argument */
+#define MPI_ERR_INFO_KEY    29      /* Key longer than MPI_MAX_INFO_KEY */
+#define MPI_ERR_INFO_VALUE  30      /* Value longer than MPI_MAX_INFO_VAL */
+#define MPI_ERR_INFO_NOKEY  31      /* Invalid key passed to MPI_Info_delete */
+#define MPI_ERR_IO          32      /* Other I/O error */
+#define MPI_ERR_NAME        33      /* Invalid service name in MPI_Lookup_name */
+#define MPI_ERR_NO_MEM      34      /* Alloc_mem could not allocate memory */
+#define MPI_ERR_NOT_SAME    35      /* Collective argument/sequence not the same on all processes */
+#define MPI_ERR_NO_SPACE    36      /* Not enough space */
+#define MPI_ERR_NO_SUCH_FILE 37     /* File does not exist */
+#define MPI_ERR_PORT        38      /* Invalid port name in MPI_comm_connect*/
+#define MPI_ERR_QUOTA       39      /* Quota exceeded */
+#define MPI_ERR_READ_ONLY   40      /* Read-only file or file system */
+#define MPI_ERR_SERVICE     41      /* Invalid service name in MPI_Unpublish_name */
+#define MPI_ERR_SPAWN       42      /* Error in spawning processes */
+#define MPI_ERR_UNSUPPORTED_DATAREP   43  /* Unsupported dararep in MPI_File_set_view */
+#define MPI_ERR_UNSUPPORTED_OPERATION 44  /* Unsupported operation on file */
+#define MPI_ERR_WIN         45      /* Invalid win argument */
+#define MPI_ERR_BASE        46      /* Invalid base passed to MPI_Free_mem */
+#define MPI_ERR_LOCKTYPE    47      /* Invalid locktype argument */
+#define MPI_ERR_KEYVAL      48      /* Invalid keyval  */
+#define MPI_ERR_RMA_CONFLICT 49     /* Conflicting accesses to window */
+#define MPI_ERR_RMA_SYNC    50      /* Wrong synchronization of RMA calls */
+#define MPI_ERR_SIZE        51      /* Invalid size argument */
+#define MPI_ERR_DISP        52      /* Invalid disp argument */
+#define MPI_ERR_ASSERT      53      /* Invalid assert argument */
+
+#define MPI_ERR_LASTCODE    0x3fffffff    /* Last valid error code for a predefined error class */
+
+#define MPICH_ERR_LAST_CLASS 53
+
+
+/*---------------------------------------------------------------------------*/
+/* MPI Basic integer types                                                   */
+/*---------------------------------------------------------------------------*/
+
+/* Address size integer */
+#ifdef _WIN64
+typedef __int64 MPI_Aint;
+#else
+typedef int MPI_Aint;
+#endif
+
+/* Fortran INTEGER */
+typedef int MPI_Fint;
+
+/* File offset */
+typedef __int64 MPI_Offset;
+
+
+/*---------------------------------------------------------------------------*/
+/* MPI_Datatype                                                              */
+/*---------------------------------------------------------------------------*/
+
+typedef int MPI_Datatype;
+#define MPI_DATATYPE_NULL           ((MPI_Datatype)0x0c000000)
+
+#define MPI_CHAR                    ((MPI_Datatype)0x4c000101)
+#define MPI_UNSIGNED_CHAR           ((MPI_Datatype)0x4c000102)
+#define MPI_SHORT                   ((MPI_Datatype)0x4c000203)
+#define MPI_UNSIGNED_SHORT          ((MPI_Datatype)0x4c000204)
+#define MPI_INT                     ((MPI_Datatype)0x4c000405)
+#define MPI_UNSIGNED                ((MPI_Datatype)0x4c000406)
+#define MPI_LONG                    ((MPI_Datatype)0x4c000407)
+#define MPI_UNSIGNED_LONG           ((MPI_Datatype)0x4c000408)
+#define MPI_LONG_LONG_INT           ((MPI_Datatype)0x4c000809)
+#define MPI_LONG_LONG               MPI_LONG_LONG_INT
+#define MPI_FLOAT                   ((MPI_Datatype)0x4c00040a)
+#define MPI_DOUBLE                  ((MPI_Datatype)0x4c00080b)
+#define MPI_LONG_DOUBLE             ((MPI_Datatype)0x4c00080c)
+#define MPI_BYTE                    ((MPI_Datatype)0x4c00010d)
+#define MPI_WCHAR                   ((MPI_Datatype)0x4c00020e)
+
+#define MPI_PACKED                  ((MPI_Datatype)0x4c00010f)
+#define MPI_LB                      ((MPI_Datatype)0x4c000010)
+#define MPI_UB                      ((MPI_Datatype)0x4c000011)
+
+#define MPI_C_COMPLEX               ((MPI_Datatype)0x4c000812)
+#define MPI_C_FLOAT_COMPLEX         ((MPI_Datatype)0x4c000813)
+#define MPI_C_DOUBLE_COMPLEX        ((MPI_Datatype)0x4c001614)
+#define MPI_C_LONG_DOUBLE_COMPLEX   ((MPI_Datatype)0x4c001615)
+
+#define MPI_2INT                    ((MPI_Datatype)0x4c000816)
+#define MPI_C_BOOL                  ((MPI_Datatype)0x4c000117)
+#define MPI_SIGNED_CHAR             ((MPI_Datatype)0x4c000118)
+#define MPI_UNSIGNED_LONG_LONG      ((MPI_Datatype)0x4c000819)
+
+/* Fortran types */
+#define MPI_CHARACTER               ((MPI_Datatype)0x4c00011a)
+#define MPI_INTEGER                 ((MPI_Datatype)0x4c00041b)
+#define MPI_REAL                    ((MPI_Datatype)0x4c00041c)
+#define MPI_LOGICAL                 ((MPI_Datatype)0x4c00041d)
+#define MPI_COMPLEX                 ((MPI_Datatype)0x4c00081e)
+#define MPI_DOUBLE_PRECISION        ((MPI_Datatype)0x4c00081f)
+#define MPI_2INTEGER                ((MPI_Datatype)0x4c000820)
+#define MPI_2REAL                   ((MPI_Datatype)0x4c000821)
+#define MPI_DOUBLE_COMPLEX          ((MPI_Datatype)0x4c001022)
+#define MPI_2DOUBLE_PRECISION       ((MPI_Datatype)0x4c001023)
+#define MPI_2COMPLEX                ((MPI_Datatype)0x4c001024)
+#define MPI_2DOUBLE_COMPLEX         ((MPI_Datatype)0x4c002025)
+
+/* Size-specific types (see MPI 2.2, 16.2.5) */
+#define MPI_REAL2                   MPI_DATATYPE_NULL
+#define MPI_REAL4                   ((MPI_Datatype)0x4c000427)
+#define MPI_COMPLEX8                ((MPI_Datatype)0x4c000828)
+#define MPI_REAL8                   ((MPI_Datatype)0x4c000829)
+#define MPI_COMPLEX16               ((MPI_Datatype)0x4c00102a)
+#define MPI_REAL16                  MPI_DATATYPE_NULL
+#define MPI_COMPLEX32               MPI_DATATYPE_NULL
+#define MPI_INTEGER1                ((MPI_Datatype)0x4c00012d)
+#define MPI_COMPLEX4                MPI_DATATYPE_NULL
+#define MPI_INTEGER2                ((MPI_Datatype)0x4c00022f)
+#define MPI_INTEGER4                ((MPI_Datatype)0x4c000430)
+#define MPI_INTEGER8                ((MPI_Datatype)0x4c000831)
+#define MPI_INTEGER16               MPI_DATATYPE_NULL
+#define MPI_INT8_T                  ((MPI_Datatype)0x4c000133)
+#define MPI_INT16_T                 ((MPI_Datatype)0x4c000234)
+#define MPI_INT32_T                 ((MPI_Datatype)0x4c000435)
+#define MPI_INT64_T                 ((MPI_Datatype)0x4c000836)
+#define MPI_UINT8_T                 ((MPI_Datatype)0x4c000137)
+#define MPI_UINT16_T                ((MPI_Datatype)0x4c000238)
+#define MPI_UINT32_T                ((MPI_Datatype)0x4c000439)
+#define MPI_UINT64_T                ((MPI_Datatype)0x4c00083a)
+
+#ifdef _WIN64
+#define MPI_AINT                    ((MPI_Datatype)0x4c00083b)
+#else
+#define MPI_AINT                    ((MPI_Datatype)0x4c00043b)
+#endif
+#define MPI_OFFSET                  ((MPI_Datatype)0x4c00083c)
+
+/*
+ * The layouts for the types MPI_DOUBLE_INT etc. are
+ *
+ *      struct { double a; int b; }
+ */
+#define MPI_FLOAT_INT               ((MPI_Datatype)0x8c000000)
+#define MPI_DOUBLE_INT              ((MPI_Datatype)0x8c000001)
+#define MPI_LONG_INT                ((MPI_Datatype)0x8c000002)
+#define MPI_SHORT_INT               ((MPI_Datatype)0x8c000003)
+#define MPI_LONG_DOUBLE_INT         ((MPI_Datatype)0x8c000004)
+
+
+/*---------------------------------------------------------------------------*/
+/* MPI_Comm                                                                  */
+/*---------------------------------------------------------------------------*/
+
+typedef int MPI_Comm;
+#define MPI_COMM_NULL  ((MPI_Comm)0x04000000)
+
+#define MPI_COMM_WORLD ((MPI_Comm)0x44000000)
+#define MPI_COMM_SELF  ((MPI_Comm)0x44000001)
+
+
+/*---------------------------------------------------------------------------*/
+/* MPI_Win                                                                   */
+/*---------------------------------------------------------------------------*/
+
+typedef int MPI_Win;
+#define MPI_WIN_NULL ((MPI_Win)0x20000000)
+
+
+/*---------------------------------------------------------------------------*/
+/* MPI_File                                                                  */
+/*---------------------------------------------------------------------------*/
+
+typedef struct ADIOI_FileD* MPI_File;
+#define MPI_FILE_NULL ((MPI_File)0)
+
+
+/*---------------------------------------------------------------------------*/
+/* MPI_Op                                                                    */
+/*---------------------------------------------------------------------------*/
+
+typedef int MPI_Op;
+#define MPI_OP_NULL ((MPI_Op)0x18000000)
+
+#define MPI_MAX     ((MPI_Op)0x58000001)
+#define MPI_MIN     ((MPI_Op)0x58000002)
+#define MPI_SUM     ((MPI_Op)0x58000003)
+#define MPI_PROD    ((MPI_Op)0x58000004)
+#define MPI_LAND    ((MPI_Op)0x58000005)
+#define MPI_BAND    ((MPI_Op)0x58000006)
+#define MPI_LOR     ((MPI_Op)0x58000007)
+#define MPI_BOR     ((MPI_Op)0x58000008)
+#define MPI_LXOR    ((MPI_Op)0x58000009)
+#define MPI_BXOR    ((MPI_Op)0x5800000a)
+#define MPI_MINLOC  ((MPI_Op)0x5800000b)
+#define MPI_MAXLOC  ((MPI_Op)0x5800000c)
+#define MPI_REPLACE ((MPI_Op)0x5800000d)
+
+
+/*---------------------------------------------------------------------------*/
+/* MPI_Info                                                                  */
+/*---------------------------------------------------------------------------*/
+
+typedef int MPI_Info;
+#define MPI_INFO_NULL         ((MPI_Info)0x1c000000)
+
+
+/*---------------------------------------------------------------------------*/
+/* MPI_Request                                                               */
+/*---------------------------------------------------------------------------*/
+
+typedef int MPI_Request;
+#define MPI_REQUEST_NULL ((MPI_Request)0x2c000000)
+
+
+/*---------------------------------------------------------------------------*/
+/* MPI_Group                                                                 */
+/*---------------------------------------------------------------------------*/
+
+typedef int MPI_Group;
+#define MPI_GROUP_NULL  ((MPI_Group)0x08000000)
+
+#define MPI_GROUP_EMPTY ((MPI_Group)0x48000000)
+
+
+/*---------------------------------------------------------------------------*/
+/* MPI_Errhandler                                                            */
+/*---------------------------------------------------------------------------*/
+
+typedef int MPI_Errhandler;
+#define MPI_ERRHANDLER_NULL  ((MPI_Errhandler)0x14000000)
+
+#define MPI_ERRORS_ARE_FATAL ((MPI_Errhandler)0x54000000)
+#define MPI_ERRORS_RETURN    ((MPI_Errhandler)0x54000001)
+
+/*---------------------------------------------------------------------------*/
+/* MPI_Status                                                                */
+/*---------------------------------------------------------------------------*/
+
+typedef struct MPI_Status
+{
+    int count;
+    int cancelled;
+    int MPI_SOURCE;
+    int MPI_TAG;
+    int MPI_ERROR;
+
+} MPI_Status;
+
+#define MPI_STATUS_IGNORE ((MPI_Status*)(MPI_Aint)1)
+#define MPI_STATUSES_IGNORE ((MPI_Status*)(MPI_Aint)1)
+
+
+/*---------------------------------------------------------------------------*/
+/* MISC CONSTANTS                                                            */
+/*---------------------------------------------------------------------------*/
+
+/* Used in: Count, Index, Rank, Color, Toplogy, Precision, Exponent range  */
+#define MPI_UNDEFINED   (-32766)
+
+/* Used in: Rank */
+#define MPI_PROC_NULL   (-1)
+#define MPI_ANY_SOURCE  (-2)
+#define MPI_ROOT        (-3)
+
+/* Used in: Tag */
+#define MPI_ANY_TAG     (-1)
+
+/* Used for: Buffer address */
+#define MPI_BOTTOM      ((void*)0)
+
+
+/*---------------------------------------------------------------------------*/
+/* Chapter 3: Point-to-Point Communication                                   */
+/*---------------------------------------------------------------------------*/
+
+/*---------------------------------------------*/
+/* Section 3.2: Blocking Communication         */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Send(
+    _In_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Send(
+    _In_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm
+    );
+
+int
+MPIAPI
+MPI_Recv(
+    _Out_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int source,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_Recv(
+    _Out_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int source,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_Get_count(
+    _In_ MPI_Status* status,
+    MPI_Datatype datatype,
+    _Out_ int* count
+    );
+int
+MPIAPI
+PMPI_Get_count(
+    _In_ MPI_Status* status,
+    MPI_Datatype datatype,
+    _Out_ int* count
+    );
+
+
+/*---------------------------------------------*/
+/* Section 3.4: Communication Modes            */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Bsend(
+    _In_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Bsend(
+    _In_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm
+    );
+
+int
+MPIAPI
+MPI_Ssend(
+    _In_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Ssend(
+    _In_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm
+    );
+
+int
+MPIAPI
+MPI_Rsend(
+    _In_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Rsend(
+    _In_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm
+    );
+
+
+/*---------------------------------------------*/
+/* Section 3.6: Buffer Allocation              */
+/*---------------------------------------------*/
+
+/* Upper bound on bsend overhead for each message */
+#define MSMPI_BSEND_OVERHEAD_V1   95
+#define MSMPI_BSEND_OVERHEAD_V2   MSMPI_BSEND_OVERHEAD_V1
+
+#if MSMPI_VER > 0x300
+#  define MPI_BSEND_OVERHEAD  MSMPI_Get_bsend_overhead()
+#else
+#  define MPI_BSEND_OVERHEAD  MSMPI_BSEND_OVERHEAD_V1
+#endif
+
+int
+MPIAPI
+MPI_Buffer_attach(
+    _In_ void* buffer,
+    int size
+    );
+int
+MPIAPI
+PMPI_Buffer_attach(
+    _In_ void* buffer,
+    int size
+    );
+
+int
+MPIAPI
+MPI_Buffer_detach(
+    _Out_ void* buffer_addr,
+    _Out_ int* size
+    );
+int
+MPIAPI
+PMPI_Buffer_detach(
+    _Out_ void* buffer_addr,
+    _Out_ int* size
+    );
+
+
+/*---------------------------------------------*/
+/* Section 3.7: Nonblocking Communication      */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Isend(
+    _In_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_Isend(
+    _In_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+
+int
+MPIAPI
+MPI_Ibsend(
+    _In_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_Ibsend(
+    _In_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+
+int
+MPIAPI
+MPI_Issend(
+    _In_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_Issend(
+    _In_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+
+int
+MPIAPI
+MPI_Irsend(
+    _In_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_Irsend(
+    _In_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+
+int
+MPIAPI
+MPI_Irecv(
+    _Out_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int source,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_Irecv(
+    _Out_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int source,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+
+
+/*---------------------------------------------*/
+/* Section 3.7.3: Communication Completion     */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Wait(
+    _Inout_ MPI_Request* request,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_Wait(
+    _Inout_ MPI_Request* request,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_Test(
+    _Inout_ MPI_Request* request,
+    _Out_ int* flag,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_Test(
+    _Inout_ MPI_Request* request,
+    _Out_ int* flag,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_Request_free(
+    _Inout_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_Request_free(
+    _Inout_ MPI_Request* request
+    );
+
+
+/*---------------------------------------------*/
+/* Section 3.7.5: Multiple Completions         */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Waitany(
+    int count,
+    _Inout_count_(count) MPI_Request* array_of_requests,
+    _Out_ int* index,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_Waitany(
+    int count,
+    _Inout_count_(count) MPI_Request* array_of_requests,
+    _Out_ int* index,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_Testany(
+    int count,
+    _Inout_count_(count) MPI_Request* array_of_requests,
+    _Out_ int* index,
+    _Out_ int* flag,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_Testany(
+    int count,
+    _Inout_count_(count) MPI_Request* array_of_requests,
+    _Out_ int* index,
+    _Out_ int* flag,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_Waitall(
+    int count,
+    _Inout_count_(count) MPI_Request* array_of_requests,
+    _Out_cap_(count) MPI_Status* array_of_statuses
+    );
+int
+MPIAPI
+PMPI_Waitall(
+    int count,
+    _Inout_count_(count) MPI_Request* array_of_requests,
+    _Out_cap_(count) MPI_Status* array_of_statuses
+    );
+
+int
+MPIAPI
+MPI_Testall(
+    int count,
+    _Inout_count_(count) MPI_Request* array_of_requests,
+    _Out_ int* flag,
+    _Out_cap_(count) MPI_Status* array_of_statuses
+    );
+int
+MPIAPI
+PMPI_Testall(
+    int count,
+    _Inout_count_(count) MPI_Request* array_of_requests,
+    _Out_ int* flag,
+    _Out_cap_(count) MPI_Status* array_of_statuses
+    );
+
+int
+MPIAPI
+MPI_Waitsome(
+    int incount,
+    _Inout_count_(incount) MPI_Request* array_of_requests,
+    _Out_ int* outcount,
+    _Out_cap_post_count_(incount,*outcount) int* array_of_indices,
+    _Out_cap_post_count_(incount,*outcount) MPI_Status* array_of_statuses
+    );
+int
+MPIAPI
+PMPI_Waitsome(
+    int incount,
+    _Inout_count_(incount) MPI_Request* array_of_requests,
+    _Out_ int* outcount,
+    _Out_cap_post_count_(incount,*outcount) int* array_of_indices,
+    _Out_cap_post_count_(incount,*outcount) MPI_Status* array_of_statuses
+    );
+
+int
+MPIAPI
+MPI_Testsome(
+    int incount,
+    _Inout_count_(incount) MPI_Request* array_of_requests,
+    _Out_ int* outcount,
+    _Out_cap_post_count_(incount,*outcount) int* array_of_indices,
+    _Out_cap_post_count_(incount,*outcount) MPI_Status* array_of_statuses
+    );
+int
+MPIAPI
+PMPI_Testsome(
+    int incount,
+    _Inout_count_(incount) MPI_Request* array_of_requests,
+    _Out_ int* outcount,
+    _Out_cap_post_count_(incount,*outcount) int* array_of_indices,
+    _Out_cap_post_count_(incount,*outcount) MPI_Status* array_of_statuses
+    );
+
+
+/*---------------------------------------------*/
+/* Section 3.7.6: Test of status               */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Request_get_status(
+    MPI_Request request,
+    _Out_ int* flag,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_Request_get_status(
+    MPI_Request request,
+    _Out_ int* flag,
+    _Out_ MPI_Status* status
+    );
+
+
+/*---------------------------------------------*/
+/* Section 3.8: Probe and Cancel               */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Iprobe(
+    int source,
+    int tag,
+    MPI_Comm comm,
+    _Out_ int* flag,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_Iprobe(
+    int source,
+    int tag,
+    MPI_Comm comm,
+    _Out_ int* flag,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_Probe(
+    int source,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_Probe(
+    int source,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_Cancel(
+    _In_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_Cancel(
+    _In_ MPI_Request* request
+    );
+
+int
+MPIAPI
+MPI_Test_cancelled(
+    _In_ MPI_Status* status,
+    _Out_ int* flag
+    );
+int
+MPIAPI
+PMPI_Test_cancelled(
+    _In_ MPI_Status* request,
+    _Out_ int* flag
+    );
+
+
+/*---------------------------------------------*/
+/* Section 3.9: Persistent Communication       */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Send_init(
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_Send_init(
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+
+int
+MPIAPI
+MPI_Bsend_init(
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_Bsend_init(
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+
+int
+MPIAPI
+MPI_Ssend_init(
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_Ssend_init(
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+
+int
+MPIAPI
+MPI_Rsend_init(
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_Rsend_init(
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+
+int
+MPIAPI
+MPI_Recv_init(
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int source,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_Recv_init(
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int source,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+
+int
+MPIAPI
+MPI_Start(
+    _Inout_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_Start(
+    _Inout_ MPI_Request* request
+    );
+
+int
+MPIAPI
+MPI_Startall(
+    int count,
+    _Inout_count_(count) MPI_Request* array_of_requests
+    );
+int
+MPIAPI
+PMPI_Startall(
+    int count,
+    _Inout_count_(count) MPI_Request* array_of_requests
+    );
+
+
+/*---------------------------------------------*/
+/* Section 3.10: Send-Recv                     */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Sendrecv(
+    _In_ void* sendbuf,
+    int sendcount,
+    MPI_Datatype sendtype,
+    int dest,
+    int sendtag,
+    _Out_ void* recvbuf,
+    int recvcount,
+    MPI_Datatype recvtype,
+    int source,
+    int recvtag,
+    MPI_Comm comm,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_Sendrecv(
+    _In_ void* sendbuf,
+    int sendcount,
+    MPI_Datatype sendtype,
+    int dest,
+    int sendtag,
+    _Out_ void* recvbuf,
+    int recvcount,
+    MPI_Datatype recvtype,
+    int source,
+    int recvtag,
+    MPI_Comm comm,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_Sendrecv_replace(
+    _Inout_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int sendtag,
+    int source,
+    int recvtag,
+    MPI_Comm comm,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_Sendrecv_replace(
+    _Inout_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int sendtag,
+    int source,
+    int recvtag,
+    MPI_Comm comm,
+    _Out_ MPI_Status* status
+    );
+
+
+/*---------------------------------------------------------------------------*/
+/* Chapter 4: Datatypes                                                      */
+/*---------------------------------------------------------------------------*/
+
+/*---------------------------------------------*/
+/* Section 4.1: Derived Datatypes              */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Type_contiguous(
+    int count,
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+int
+MPIAPI
+PMPI_Type_contiguous(
+    int count,
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+
+int
+MPIAPI
+MPI_Type_vector(
+    int count,
+    int blocklength,
+    int stride,
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+int
+MPIAPI
+PMPI_Type_vector(
+    int count,
+    int blocklength,
+    int stride,
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+
+int
+MPIAPI
+MPI_Type_create_hvector(
+    int count,
+    int blocklength,
+    MPI_Aint stride,
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+int
+MPIAPI
+PMPI_Type_create_hvector(
+    int count,
+    int blocklength,
+    MPI_Aint stride,
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+
+int
+MPIAPI
+MPI_Type_indexed(
+    int count,
+    _In_count_(count) int* array_of_blocklengths,
+    _In_count_(count) int* array_of_displacements,
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+int
+MPIAPI
+PMPI_Type_indexed(
+    int count,
+    _In_count_(count) int* array_of_blocklengths,
+    _In_count_(count) int* array_of_displacements,
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+
+int
+MPIAPI
+MPI_Type_create_hindexed(
+    int count,
+    _In_count_(count) int array_of_blocklengths[],
+    _In_count_(count) MPI_Aint array_of_displacements[],
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+int
+MPIAPI
+PMPI_Type_create_hindexed(
+    int count,
+    _In_count_(count) int array_of_blocklengths[],
+    _In_opt_count_(count) MPI_Aint array_of_displacements[],
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+
+int
+MPIAPI
+MPI_Type_create_indexed_block(
+    int count,
+    int blocklength,
+    _In_count_(count) int array_of_displacements[],
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+int
+MPIAPI
+PMPI_Type_create_indexed_block(
+    int count,
+    int blocklength,
+    _In_count_(count) int array_of_displacements[],
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+
+int
+MPIAPI
+MPI_Type_create_struct(
+    int count,
+    _In_count_(count) int array_of_blocklengths[],
+    _In_count_(count) MPI_Aint array_of_displacements[],
+    _In_count_(count) MPI_Datatype array_of_types[],
+    _Out_ MPI_Datatype* newtype
+    );
+int
+MPIAPI
+PMPI_Type_create_struct(
+    int count,
+    _In_count_(count) int array_of_blocklengths[],
+    _In_opt_count_(count) MPI_Aint array_of_displacements[],
+    _In_count_(count) MPI_Datatype array_of_types[],
+    _Out_ MPI_Datatype* newtype
+    );
+
+
+#define MPI_ORDER_C         56
+#define MPI_ORDER_FORTRAN   57
+
+int
+MPIAPI
+MPI_Type_create_subarray(
+    int ndims,
+    _In_count_(ndims) int array_of_sizes[],
+    _In_count_(ndims) int array_of_subsizes[],
+    _In_count_(ndims) int array_of_starts[],
+    int order,
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+int
+MPIAPI
+PMPI_Type_create_subarray(
+    int ndims,
+    _In_count_(ndims) int array_of_sizes[],
+    _In_count_(ndims) int array_of_subsizes[],
+    _In_count_(ndims) int array_of_starts[],
+    int order,
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+
+
+#define MPI_DISTRIBUTE_BLOCK         121
+#define MPI_DISTRIBUTE_CYCLIC        122
+#define MPI_DISTRIBUTE_NONE          123
+#define MPI_DISTRIBUTE_DFLT_DARG (-49767)
+
+int
+MPIAPI
+MPI_Type_create_darray(
+    int size,
+    int rank,
+    int ndims,
+    _In_count_(ndims) int array_of_gszies[],
+    _In_count_(ndims) int array_of_distribs[],
+    _In_count_(ndims) int array_of_dargs[],
+    _In_count_(ndims) int array_of_psizes[],
+    int order,
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+int
+MPIAPI
+PMPI_Type_create_darray(
+    int size,
+    int rank,
+    int ndims,
+    _In_count_(ndims) int array_of_gszies[],
+    _In_count_(ndims) int array_of_distribs[],
+    _In_count_(ndims) int array_of_dargs[],
+    _In_count_(ndims) int array_of_psizes[],
+    int order,
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+
+
+/*---------------------------------------------*/
+/* Section 4.1.5: Datatype Address and Size    */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Get_address(
+    _In_ void* location,
+    _Out_ MPI_Aint* address
+    );
+int
+MPIAPI
+PMPI_Get_address(
+    _In_ void* location,
+    _Out_ MPI_Aint* address
+    );
+
+int
+MPIAPI
+MPI_Type_size(
+    MPI_Datatype datatype,
+    _Out_ int* size
+    );
+int
+MPIAPI
+PMPI_Type_size(
+    MPI_Datatype datatype,
+    _Out_ int* size
+    );
+
+
+/*---------------------------------------------*/
+/* Section 4.1.7: Datatype Extent and Bounds   */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Type_get_extent(
+    MPI_Datatype datatype,
+    _Out_ MPI_Aint* lb,
+    _Out_ MPI_Aint* extent
+    );
+int
+MPIAPI
+PMPI_Type_get_extent(
+    MPI_Datatype datatype,
+    _Out_ MPI_Aint* lb,
+    _Out_ MPI_Aint* extent
+    );
+
+int
+MPIAPI
+MPI_Type_create_resized(
+    MPI_Datatype oldtype,
+    MPI_Aint lb,
+    MPI_Aint extent,
+    _Out_ MPI_Datatype* newtype
+    );
+int
+MPIAPI
+PMPI_Type_create_resized(
+    MPI_Datatype oldtype,
+    MPI_Aint lb,
+    MPI_Aint extent,
+    _Out_ MPI_Datatype* newtype
+    );
+
+
+/*---------------------------------------------*/
+/* Section 4.1.8: Datatype True Extent         */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Type_get_true_extent(
+    MPI_Datatype datatype,
+    _Out_ MPI_Aint* true_lb,
+    _Out_ MPI_Aint* true_extent
+    );
+int
+MPIAPI
+PMPI_Type_get_true_extent(
+    MPI_Datatype datatype,
+    _Out_ MPI_Aint* true_lb,
+    _Out_ MPI_Aint* true_extent
+    );
+
+
+/*---------------------------------------------*/
+/* Section 4.1.9: Datatype Commit and Free     */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Type_commit(
+    _In_ MPI_Datatype* datatype
+    );
+int
+MPIAPI
+PMPI_Type_commit(
+    _In_ MPI_Datatype* datatype
+    );
+
+int
+MPIAPI
+MPI_Type_free(
+    _Inout_ MPI_Datatype* datatype
+    );
+int
+MPIAPI
+PMPI_Type_free(
+    _Inout_ MPI_Datatype* datatype
+    );
+
+
+/*---------------------------------------------*/
+/* Section 4.1.10: Datatype Duplication        */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Type_dup(
+    MPI_Datatype type,
+    _Out_ MPI_Datatype* newtype
+    );
+int
+MPIAPI
+PMPI_Type_dup(
+    MPI_Datatype type,
+    _Out_ MPI_Datatype* newtype
+    );
+
+
+/*---------------------------------------------*/
+/* Section 4.1.11: Datatype and Communication  */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Get_elements(
+    _In_ MPI_Status* status,
+    MPI_Datatype datatype,
+    _Out_ int* count
+    );
+int
+MPIAPI
+PMPI_Get_elements(
+    _In_ MPI_Status* status,
+    MPI_Datatype datatype,
+    _Out_ int* count
+    );
+
+
+/*---------------------------------------------*/
+/* Section 4.1.13: Decoding a Datatype         */
+/*---------------------------------------------*/
+
+/* Datatype combiners result */
+enum
+{
+    MPI_COMBINER_NAMED            = 1,
+    MPI_COMBINER_DUP              = 2,
+    MPI_COMBINER_CONTIGUOUS       = 3,
+    MPI_COMBINER_VECTOR           = 4,
+    MPI_COMBINER_HVECTOR_INTEGER  = 5,
+    MPI_COMBINER_HVECTOR          = 6,
+    MPI_COMBINER_INDEXED          = 7,
+    MPI_COMBINER_HINDEXED_INTEGER = 8,
+    MPI_COMBINER_HINDEXED         = 9,
+    MPI_COMBINER_INDEXED_BLOCK    = 10,
+    MPI_COMBINER_STRUCT_INTEGER   = 11,
+    MPI_COMBINER_STRUCT           = 12,
+    MPI_COMBINER_SUBARRAY         = 13,
+    MPI_COMBINER_DARRAY           = 14,
+    MPI_COMBINER_F90_REAL         = 15,
+    MPI_COMBINER_F90_COMPLEX      = 16,
+    MPI_COMBINER_F90_INTEGER      = 17,
+    MPI_COMBINER_RESIZED          = 18
+};
+
+int
+MPIAPI
+MPI_Type_get_envelope(
+    MPI_Datatype datatype,
+    _Out_ int* num_integers,
+    _Out_ int* num_addresses,
+    _Out_ int* num_datatypes,
+    _Out_ int* combiner
+    );
+int
+MPIAPI
+PMPI_Type_get_envelope(
+    MPI_Datatype datatype,
+    _Out_ int* num_integers,
+    _Out_ int* num_addresses,
+    _Out_ int* num_datatypes,
+    _Out_ int* combiner
+    );
+
+int
+MPIAPI
+MPI_Type_get_contents(
+    MPI_Datatype datatype,
+    int max_integers,
+    int max_addresses,
+    int max_datatypes,
+    _Out_cap_(max_integers) int array_of_integers[],
+    _Out_cap_(max_addresses) MPI_Aint array_of_addresses[],
+    _Out_cap_(max_datatypes) MPI_Datatype array_of_datatypes[]
+    );
+int
+MPIAPI
+PMPI_Type_get_contents(
+    MPI_Datatype datatype,
+    int max_integers,
+    int max_addresses,
+    int max_datatypes,
+    _Out_cap_(max_integers) int array_of_integers[],
+    _Out_cap_(max_addresses) MPI_Aint array_of_addresses[],
+    _Out_cap_(max_datatypes) MPI_Datatype array_of_datatypes[]
+    );
+
+
+/*---------------------------------------------*/
+/* Section 4.2: Datatype Pack and Unpack       */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Pack(
+    _In_ void* inbuf,
+    int incount,
+    MPI_Datatype datatype,
+    _Out_bytecap_(outsize) void* outbuf,
+    int outsize,
+    _Inout_ int* position,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Pack(
+    _In_ void* inbuf,
+    int incount,
+    MPI_Datatype datatype,
+    _Out_bytecap_(outsize) void* outbuf,
+    int outsize,
+    _Inout_ int* position,
+    MPI_Comm comm
+    );
+
+int
+MPIAPI
+MPI_Unpack(
+    _In_bytecount_(insize) void* inbuf,
+    int insize,
+    _Inout_ int* position,
+    _Out_ void* outbuf,
+    int outcount,
+    MPI_Datatype datatype,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Unpack(
+    _In_bytecount_(insize) void* inbuf,
+    int insize,
+    _Inout_ int* position,
+    _Out_ void* outbuf,
+    int outcount,
+    MPI_Datatype datatype,
+    MPI_Comm comm
+    );
+
+int
+MPIAPI
+MPI_Pack_size(
+    int incount,
+    MPI_Datatype datatype,
+    MPI_Comm comm,
+    _Out_ int* size
+    );
+int
+MPIAPI
+PMPI_Pack_size(
+    int incount,
+    MPI_Datatype datatype,
+    MPI_Comm comm,
+    _Out_ int* size
+    );
+
+
+/*---------------------------------------------*/
+/* Section 4.3: Canonical Pack and Unpack      */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Pack_external(
+    _In_z_ char* datarep,
+    _In_ void* inbuf,
+    int incount,
+    MPI_Datatype datatype,
+    _Out_bytecap_(outsize) void* outbuf,
+    MPI_Aint outsize,
+    _Inout_ MPI_Aint* position
+    );
+int
+MPIAPI
+PMPI_Pack_external(
+    _In_z_ char* datarep,
+    _In_ void* inbuf,
+    int incount,
+    MPI_Datatype datatype,
+    _Out_bytecap_(outsize) void* outbuf,
+    MPI_Aint outsize,
+    _Inout_ MPI_Aint* position
+    );
+
+int
+MPIAPI
+MPI_Unpack_external(
+    _In_z_ char* datarep,
+    _In_bytecount_(insize) void* inbuf,
+    MPI_Aint insize,
+    _Inout_ MPI_Aint* position,
+    _Out_ void* outbuf,
+    int outcount,
+    MPI_Datatype datatype
+    );
+int
+MPIAPI
+PMPI_Unpack_external(
+    _In_z_ char* datarep,
+    _In_bytecount_(insize) void* inbuf,
+    MPI_Aint insize,
+    _Inout_ MPI_Aint* position,
+    _Out_ void* outbuf,
+    int outcount,
+    MPI_Datatype datatype
+    );
+
+int
+MPIAPI
+MPI_Pack_external_size(
+    _In_z_ char* datarep,
+    int incount,
+    MPI_Datatype datatype,
+    _Out_ MPI_Aint* size
+    );
+int
+MPIAPI
+PMPI_Pack_external_size(
+    _In_z_ char* datarep,
+    int incount,
+    MPI_Datatype datatype,
+    _Out_ MPI_Aint* size
+    );
+
+
+/*---------------------------------------------------------------------------*/
+/* Chapter 5: Collective Communication                                       */
+/*---------------------------------------------------------------------------*/
+
+#define MPI_IN_PLACE ((void*)(MPI_Aint)-1)
+
+/*---------------------------------------------*/
+/* Section 5.3: Barrier Synchronization        */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Barrier(
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Barrier(
+    MPI_Comm comm
+    );
+
+
+/*---------------------------------------------*/
+/* Section 5.4: Broadcast                      */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Bcast(
+    _Inout_ void* buffer,
+    int count,
+    MPI_Datatype datatype,
+    int root,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Bcast(
+    _Inout_ void* buffer,
+    int count,
+    MPI_Datatype datatype,
+    int root,
+    MPI_Comm comm
+    );
+
+
+/*---------------------------------------------*/
+/* Section 5.5: Gather                         */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Gather(
+    _In_ void* sendbuf,
+    int sendcount,
+    MPI_Datatype sendtype,
+    _Out_opt_ void* recvbuf,
+    int recvcount,
+    MPI_Datatype recvtype,
+    int root,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Gather(
+    _In_ void* sendbuf,
+    int sendcount,
+    MPI_Datatype sendtype,
+    _Out_opt_ void* recvbuf,
+    int recvcount,
+    MPI_Datatype recvtype,
+    int root,
+    MPI_Comm comm
+    );
+
+int
+MPIAPI
+MPI_Gatherv(
+    _In_ void* sendbuf,
+    int sendcount,
+    MPI_Datatype sendtype,
+    _Out_opt_ void* recvbuf,
+    _In_opt_ int* recvcounts,
+    _In_opt_ int* displs,
+    MPI_Datatype recvtype,
+    int root,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Gatherv(
+    _In_ void* sendbuf,
+    int sendcount,
+    MPI_Datatype sendtype,
+    _Out_opt_ void* recvbuf,
+    _In_opt_ int* recvcounts,
+    _In_opt_ int* displs,
+    MPI_Datatype recvtype,
+    int root,
+    MPI_Comm comm
+    );
+
+
+/*---------------------------------------------*/
+/* Section 5.6: Scatter                        */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Scatter(
+    _In_ void* sendbuf,
+    int sendcount,
+    MPI_Datatype sendtype,
+    _Out_ void* recvbuf,
+    int recvcount,
+    MPI_Datatype recvtype,
+    int root,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Scatter(
+    _In_ void* sendbuf,
+    int sendcount,
+    MPI_Datatype sendtype,
+    _Out_ void* recvbuf,
+    int recvcount,
+    MPI_Datatype recvtype,
+    int root,
+    MPI_Comm comm
+    );
+
+int
+MPIAPI
+MPI_Scatterv(
+    _In_ void* sendbuf,
+    _In_ int* sendcounts,
+    _In_ int* displs,
+    MPI_Datatype sendtype,
+    _Out_ void* recvbuf,
+    int recvcount,
+    MPI_Datatype recvtype,
+    int root,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Scatterv(
+    _In_ void* sendbuf,
+    _In_ int* sendcounts,
+    _In_ int* displs,
+    MPI_Datatype sendtype,
+    _Out_ void* recvbuf,
+    int recvcount,
+    MPI_Datatype recvtype,
+    int root,
+    MPI_Comm comm
+    );
+
+
+/*---------------------------------------------*/
+/* Section 5.6: Gather-to-all                  */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Allgather(
+    _In_ void* sendbuf,
+    int sendcount,
+    MPI_Datatype sendtype,
+    _Out_ void* recvbuf,
+    int recvcount,
+    MPI_Datatype recvtype,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Allgather(
+    _In_ void* sendbuf,
+    int sendcount,
+    MPI_Datatype sendtype,
+    _Out_ void* recvbuf,
+    int recvcount,
+    MPI_Datatype recvtype,
+    MPI_Comm comm
+    );
+
+int
+MPIAPI
+MPI_Allgatherv(
+    _In_ void* sendbuf,
+    int sendcount,
+    MPI_Datatype sendtype,
+    _Out_ void* recvbuf,
+    _In_ int* recvcounts,
+    _In_ int* displs,
+    MPI_Datatype recvtype,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Allgatherv(
+    _In_ void* sendbuf,
+    int sendcount,
+    MPI_Datatype sendtype,
+    _Out_ void* recvbuf,
+    _In_ int* recvcounts,
+    _In_ int* displs,
+    MPI_Datatype recvtype,
+    MPI_Comm comm
+    );
+
+
+/*---------------------------------------------*/
+/* Section 5.6: All-to-All Scatter/Gather      */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Alltoall(
+    _In_ void* sendbuf,
+    int sendcount,
+    MPI_Datatype sendtype,
+    _Out_ void* recvbuf,
+    int recvcount,
+    MPI_Datatype recvtype,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Alltoall(
+    _In_ void* sendbuf,
+    int sendcount,
+    MPI_Datatype sendtype,
+    _Out_ void* recvbuf,
+    int recvcount,
+    MPI_Datatype recvtype,
+    MPI_Comm comm
+    );
+
+int
+MPIAPI
+MPI_Alltoallv(
+    _In_ void* sendbuf,
+    _In_ int* sendcounts,
+    _In_ int* sdispls,
+    MPI_Datatype sendtype,
+    _Out_ void* recvbuf,
+    _In_ int* recvcounts,
+    _In_ int* rdispls,
+    MPI_Datatype recvtype,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Alltoallv(
+    _In_ void* sendbuf,
+    _In_ int* sendcounts,
+    _In_ int* sdispls,
+    MPI_Datatype sendtype,
+    _Out_ void* recvbuf,
+    _In_ int* recvcounts,
+    _In_ int* rdispls,
+    MPI_Datatype recvtype,
+    MPI_Comm comm
+    );
+
+int
+MPIAPI
+MPI_Alltoallw(
+    _In_ void* sendbuf,
+    _In_ int sendcounts[],
+    _In_ int sdispls[],
+    _In_ MPI_Datatype sendtypes[],
+    _Out_ void* recvbuf,
+    _In_ int recvcounts[],
+    _In_ int rdispls[],
+    _In_ MPI_Datatype recvtypes[],
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Alltoallw(
+    _In_ void* sendbuf,
+    _In_ int sendcounts[],
+    _In_ int sdispls[],
+    _In_ MPI_Datatype sendtypes[],
+    _Out_ void* recvbuf,
+    _In_ int recvcounts[],
+    _In_ int rdispls[],
+    _In_ MPI_Datatype recvtypes[],
+    MPI_Comm comm
+    );
+
+
+/*---------------------------------------------*/
+/* Section 5.9: Global Reduction Operations    */
+/*---------------------------------------------*/
+
+typedef
+void
+(MPIAPI MPI_User_function)(
+    _In_count_(*len) void* invec,
+    _Inout_ void* inoutvec,
+    _In_ int* len,
+    _In_ MPI_Datatype* datatype
+    );
+
+int
+MPIAPI
+MPI_Op_create(
+    _In_ MPI_User_function* function,
+    int commute,
+    _Out_ MPI_Op* op
+    );
+int
+MPIAPI
+PMPI_Op_create(
+    _In_ MPI_User_function* function,
+    int commute,
+    _Out_ MPI_Op* op
+    );
+
+int
+MPIAPI
+MPI_Op_free(
+    _Inout_ MPI_Op* op
+    );
+int
+MPIAPI
+PMPI_Op_free(
+    _Inout_ MPI_Op* op
+    );
+
+int
+MPIAPI
+MPI_Reduce(
+    _In_ void* sendbuf,
+    _Out_opt_ void* recvbuf,
+    int count,
+    MPI_Datatype datatype,
+    MPI_Op op,
+    int root,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Reduce(
+    _In_ void* sendbuf,
+    _Out_opt_ void* recvbuf,
+    int count,
+    MPI_Datatype datatype,
+    MPI_Op op,
+    int root,
+    MPI_Comm comm
+    );
+
+int
+MPIAPI
+MPI_Allreduce(
+    _In_ void* sendbuf,
+    _Out_ void* recvbuf,
+    int count,
+    MPI_Datatype datatype,
+    MPI_Op op,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Allreduce(
+    _In_ void* sendbuf,
+    _Out_ void* recvbuf,
+    int count,
+    MPI_Datatype datatype,
+    MPI_Op op,
+    MPI_Comm comm
+    );
+
+int
+MPIAPI
+MPI_Reduce_local(
+    _In_ void *inbuf,
+    _Inout_ void *inoutbuf,
+    int count,
+    MPI_Datatype datatype,
+    MPI_Op op
+    );
+int
+MPIAPI
+PMPI_Reduce_local(
+    _In_ void *inbuf,
+    _Inout_ void *inoutbuf,
+    int count,
+    MPI_Datatype datatype,
+    MPI_Op op
+    );
+
+/*---------------------------------------------*/
+/* Section 5.10: Reduce-Scatter                */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Reduce_scatter(
+    _In_ void* sendbuf,
+    _Out_ void* recvbuf,
+    _In_ int* recvcounts,
+    MPI_Datatype datatype,
+    MPI_Op op,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Reduce_scatter(
+    _In_ void* sendbuf,
+    _Out_ void* recvbuf,
+    _In_ int* recvcounts,
+    MPI_Datatype datatype,
+    MPI_Op op,
+    MPI_Comm comm
+    );
+
+
+/*---------------------------------------------*/
+/* Section 5.11: Scan                          */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Scan(
+    _In_ void* sendbuf,
+    _Out_ void* recvbuf,
+    int count,
+    MPI_Datatype datatype,
+    MPI_Op op,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Scan(
+    _In_ void* sendbuf,
+    _Out_ void* recvbuf,
+    int count,
+    MPI_Datatype datatype,
+    MPI_Op op,
+    MPI_Comm comm
+    );
+
+int
+MPIAPI
+MPI_Exscan(
+    _In_ void* sendbuf,
+    _Out_ void* recvbuf,
+    int count,
+    MPI_Datatype datatype,
+    MPI_Op op,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Exscan(
+    _In_ void* sendbuf,
+    _Out_ void* recvbuf,
+    int count,
+    MPI_Datatype datatype,
+    MPI_Op op,
+    MPI_Comm comm
+    );
+
+
+/*---------------------------------------------------------------------------*/
+/* Chapter 6: Groups, Contexts, Communicators, and Caching                   */
+/*---------------------------------------------------------------------------*/
+
+/*---------------------------------------------*/
+/* Section 6.3: Group Management               */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Group_size(
+    MPI_Group group,
+    _Out_ int* size
+    );
+int
+MPIAPI
+PMPI_Group_size(
+    MPI_Group group,
+    _Out_ int* size
+    );
+
+int
+MPIAPI
+MPI_Group_rank(
+    MPI_Group group,
+    _Out_ int* rank
+    );
+int
+MPIAPI
+PMPI_Group_rank(
+    MPI_Group group,
+    _Out_ int* rank
+    );
+
+int
+MPIAPI
+MPI_Group_translate_ranks(
+    MPI_Group group1,
+    int n,
+    _In_count_(n) int* ranks1,
+    MPI_Group group2,
+    _Out_ int* ranks2
+    );
+
+int
+MPIAPI
+PMPI_Group_translate_ranks(
+    MPI_Group group1,
+    int n,
+    _In_count_(n) int* ranks1,
+    MPI_Group group2,
+    _Out_ int* ranks2
+    );
+
+/* Results of the compare operations */
+#define MPI_IDENT       0
+#define MPI_CONGRUENT   1
+#define MPI_SIMILAR     2
+#define MPI_UNEQUAL     3
+
+int
+MPIAPI
+MPI_Group_compare(
+    MPI_Group group1,
+    MPI_Group group2,
+    _Out_ int* result
+    );
+int
+MPIAPI
+PMPI_Group_compare(
+    MPI_Group group1,
+    MPI_Group group2,
+    _Out_ int* result
+    );
+
+int
+MPIAPI
+MPI_Comm_group(
+    MPI_Comm comm,
+    _Out_ MPI_Group* group
+    );
+int
+MPIAPI
+PMPI_Comm_group(
+    MPI_Comm comm,
+    _Out_ MPI_Group* group
+    );
+
+int
+MPIAPI
+MPI_Group_union(
+    MPI_Group group1,
+    MPI_Group group2,
+    _Out_ MPI_Group* newgroup
+    );
+int
+MPIAPI
+PMPI_Group_union(
+    MPI_Group group1,
+    MPI_Group group2,
+    _Out_ MPI_Group* newgroup
+    );
+
+int
+MPIAPI
+MPI_Group_intersection(
+    MPI_Group group1,
+    MPI_Group group2,
+    _Out_ MPI_Group* newgroup
+    );
+int
+MPIAPI
+PMPI_Group_intersection(
+    MPI_Group group1,
+    MPI_Group group2,
+    _Out_ MPI_Group* newgroup
+    );
+
+int
+MPIAPI
+MPI_Group_difference(
+    MPI_Group group1,
+    MPI_Group group2,
+    _Out_ MPI_Group* newgroup
+    );
+int
+MPIAPI
+PMPI_Group_difference(
+    MPI_Group group1,
+    MPI_Group group2,
+    _Out_ MPI_Group* newgroup
+    );
+
+int
+MPIAPI
+MPI_Group_incl(
+    MPI_Group group,
+    int n,
+    _In_count_(n) int* ranks,
+    _Out_ MPI_Group* newgroup
+    );
+int
+MPIAPI
+PMPI_Group_incl(
+    MPI_Group group,
+    int n,
+    _In_count_(n) int* ranks,
+    _Out_ MPI_Group* newgroup
+    );
+
+int
+MPIAPI
+MPI_Group_excl(
+    MPI_Group group,
+    int n,
+    _In_count_(n) int* ranks,
+    _Out_ MPI_Group* newgroup
+    );
+int
+MPIAPI
+PMPI_Group_excl(
+    MPI_Group group,
+    int n,
+    _In_count_(n) int* ranks,
+    _Out_ MPI_Group* newgroup
+    );
+
+int
+MPIAPI
+MPI_Group_range_incl(
+    MPI_Group group,
+    int n,
+    _In_count_(n) int ranges[][3],
+    _Out_ MPI_Group* newgroup
+    );
+int
+MPIAPI
+PMPI_Group_range_incl(
+    MPI_Group group,
+    int n,
+    _In_count_(n) int ranges[][3],
+    _Out_ MPI_Group* newgroup
+    );
+
+int
+MPIAPI
+MPI_Group_range_excl(
+    MPI_Group group,
+    int n,
+    _In_count_(n) int ranges[][3],
+    _Out_ MPI_Group* newgroup
+    );
+int
+MPIAPI
+PMPI_Group_range_excl(
+    MPI_Group group,
+    int n,
+    _In_count_(n) int ranges[][3],
+    _Out_ MPI_Group* newgroup
+    );
+
+int
+MPIAPI
+MPI_Group_free(
+    _Inout_ MPI_Group* group
+    );
+int
+MPIAPI
+PMPI_Group_free(
+    _Inout_ MPI_Group* group
+    );
+
+
+/*---------------------------------------------*/
+/* Section 6.4: Communicator Management        */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Comm_size(
+    MPI_Comm comm,
+    _Out_ int* size
+    );
+int
+MPIAPI
+PMPI_Comm_size(
+    MPI_Comm comm,
+    _Out_ int* size
+    );
+
+int
+MPIAPI
+MPI_Comm_rank(
+    MPI_Comm comm,
+    _Out_ int* rank
+    );
+int
+MPIAPI
+PMPI_Comm_rank(
+    MPI_Comm comm,
+    _Out_ int* rank
+    );
+
+int
+MPIAPI
+MPI_Comm_compare(
+    MPI_Comm comm1,
+    MPI_Comm comm2,
+    _Out_ int* result
+    );
+int
+MPIAPI
+PMPI_Comm_compare(
+    MPI_Comm comm1,
+    MPI_Comm comm2,
+    _Out_ int* result
+    );
+
+int
+MPIAPI
+MPI_Comm_dup(
+    MPI_Comm comm,
+    _Out_ MPI_Comm* newcomm
+    );
+int
+MPIAPI
+PMPI_Comm_dup(
+    MPI_Comm comm,
+    _Out_ MPI_Comm* newcomm
+    );
+
+int
+MPIAPI
+MPI_Comm_create(
+    MPI_Comm comm,
+    MPI_Group group,
+    _Out_ MPI_Comm* newcomm
+    );
+int
+MPIAPI
+PMPI_Comm_create(
+    MPI_Comm comm,
+    MPI_Group group,
+    _Out_ MPI_Comm* newcomm
+    );
+
+int
+MPIAPI
+MPI_Comm_split(
+    MPI_Comm comm,
+    int color,
+    int key,
+    _Out_ MPI_Comm* newcomm
+    );
+int
+MPIAPI
+PMPI_Comm_split(
+    MPI_Comm comm,
+    int color,
+    int key,
+    _Out_ MPI_Comm* newcomm
+    );
+
+int
+MPIAPI
+MPI_Comm_free(
+    _Inout_ MPI_Comm* comm
+    );
+int
+MPIAPI
+PMPI_Comm_free(
+    _Inout_ MPI_Comm* comm
+    );
+
+
+/*---------------------------------------------*/
+/* Section 6.6: Inter-Communication            */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Comm_test_inter(
+    MPI_Comm comm,
+    _Out_ int* flag
+    );
+int
+MPIAPI
+PMPI_Comm_test_inter(
+    MPI_Comm comm,
+    _Out_ int* flag
+    );
+
+int
+MPIAPI
+MPI_Comm_remote_size(
+    MPI_Comm comm,
+    _Out_ int* size
+    );
+int
+MPIAPI
+PMPI_Comm_remote_size(
+    MPI_Comm comm,
+    _Out_ int* size
+    );
+
+int
+MPIAPI
+MPI_Comm_remote_group(
+    MPI_Comm comm,
+    _Out_ MPI_Group* group
+    );
+int
+MPIAPI
+PMPI_Comm_remote_group(
+    MPI_Comm comm,
+    _Out_ MPI_Group* group
+    );
+
+int
+MPIAPI
+MPI_Intercomm_create(
+    MPI_Comm local_comm,
+    int local_leader,
+    MPI_Comm peer_comm,
+    int remote_leader,
+    int tag,
+    _Out_ MPI_Comm* newintercomm
+    );
+int
+MPIAPI
+PMPI_Intercomm_create(
+    MPI_Comm local_comm,
+    int local_leader,
+    MPI_Comm peer_comm,
+    int remote_leader,
+    int tag,
+    _Out_ MPI_Comm* newintercomm
+    );
+
+int
+MPIAPI
+MPI_Intercomm_merge(
+    MPI_Comm intercomm,
+    int high,
+    _Out_ MPI_Comm* newintracomm
+    );
+int
+MPIAPI
+PMPI_Intercomm_merge(
+    MPI_Comm intercomm,
+    int high,
+    _Out_ MPI_Comm* newintracomm
+    );
+
+
+/*---------------------------------------------*/
+/* Section 6.7: Caching                        */
+/*---------------------------------------------*/
+
+#define MPI_KEYVAL_INVALID  0x24000000
+
+typedef
+int
+(MPIAPI MPI_Comm_copy_attr_function)(
+    MPI_Comm oldcomm,
+    int comm_keyval,
+    _In_opt_ void* extra_state,
+    _In_ void* attribute_val_in,
+    _Out_ void* attribute_val_out,
+    _Out_ int* flag
+    );
+
+typedef
+int
+(MPIAPI MPI_Comm_delete_attr_function)(
+    MPI_Comm comm,
+    int comm_keyval,
+    _In_ void* attribute_val,
+    _In_opt_ void* extra_state
+    );
+
+#define MPI_COMM_NULL_COPY_FN ((MPI_Comm_copy_attr_function*)0)
+#define MPI_COMM_NULL_DELETE_FN ((MPI_Comm_delete_attr_function*)0)
+#define MPI_COMM_DUP_FN ((MPI_Comm_copy_attr_function*)MPIR_Dup_fn)
+
+int
+MPIAPI
+MPI_Comm_create_keyval(
+    _In_opt_ MPI_Comm_copy_attr_function* comm_copy_attr_fn,
+    _In_opt_ MPI_Comm_delete_attr_function* comm_delete_attr_fn,
+    _Out_ int* comm_keyval,
+    _In_opt_ void* extra_state
+    );
+int
+MPIAPI
+PMPI_Comm_create_keyval(
+    _In_opt_ MPI_Comm_copy_attr_function* comm_copy_attr_fn,
+    _In_opt_ MPI_Comm_delete_attr_function* comm_delete_attr_fn,
+    _Out_ int* comm_keyval,
+    _In_opt_ void* extra_state
+    );
+
+int
+MPIAPI
+MPI_Comm_free_keyval(
+    _Inout_ int* comm_keyval
+    );
+int
+MPIAPI
+PMPI_Comm_free_keyval(
+    _Inout_ int* comm_keyval
+    );
+
+int
+MPIAPI
+MPI_Comm_set_attr(
+    MPI_Comm comm,
+    int comm_keyval,
+    _In_ void* attribute_val
+    );
+int
+MPIAPI
+PMPI_Comm_set_attr(
+    MPI_Comm comm,
+    int comm_keyval,
+    _In_ void* attribute_val
+    );
+
+
+/* Predefined comm attribute key values */
+/* C Versions (return pointer to value),
+   Fortran Versions (return integer value).
+
+   DO NOT CHANGE THESE.  The values encode:
+   builtin kind (0x1 in bit 30-31)
+   Keyval object (0x9 in bits 26-29)
+   for communicator (0x1 in bits 22-25)
+
+   Fortran versions of the attributes are formed by adding one to
+   the C version.
+ */
+#define MPI_TAG_UB          0x64400001
+#define MPI_HOST            0x64400003
+#define MPI_IO              0x64400005
+#define MPI_WTIME_IS_GLOBAL 0x64400007
+#define MPI_UNIVERSE_SIZE   0x64400009
+#define MPI_LASTUSEDCODE    0x6440000b
+#define MPI_APPNUM          0x6440000d
+
+int
+MPIAPI
+MPI_Comm_get_attr(
+    MPI_Comm comm,
+    int comm_keyval,
+    _Out_ void* attribute_val,
+    _Out_ int* flag
+    );
+int
+MPIAPI
+PMPI_Comm_get_attr(
+    MPI_Comm comm,
+    int comm_keyval,
+    _Out_ void* attribute_val,
+    _Out_ int* flag
+    );
+
+int
+MPIAPI
+MPI_Comm_delete_attr(
+    MPI_Comm comm,
+    int comm_keyval
+    );
+int
+MPIAPI
+PMPI_Comm_delete_attr(
+    MPI_Comm comm,
+    int comm_keyval
+    );
+
+
+typedef
+int
+(MPIAPI MPI_Win_copy_attr_function)(
+    MPI_Win oldwin,
+    int win_keyval,
+    _In_opt_ void* extra_state,
+    _In_ void* attribute_val_in,
+    _Out_ void* attribute_val_out,
+    _Out_ int* flag
+    );
+
+typedef
+int
+(MPIAPI MPI_Win_delete_attr_function)(
+    MPI_Win win,
+    int win_keyval,
+    _In_ void* attribute_val,
+    _In_opt_ void* extra_state
+    );
+
+#define MPI_WIN_NULL_COPY_FN ((MPI_Win_copy_attr_function*)0)
+#define MPI_WIN_NULL_DELETE_FN ((MPI_Win_delete_attr_function*)0)
+#define MPI_WIN_DUP_FN ((MPI_Win_copy_attr_function*)MPIR_Dup_fn)
+
+int
+MPIAPI
+MPI_Win_create_keyval(
+    _In_ MPI_Win_copy_attr_function* win_copy_attr_fn,
+    _In_ MPI_Win_delete_attr_function* win_delete_attr_fn,
+    _Out_ int* win_keyval,
+    _In_opt_ void* extra_state
+    );
+int
+MPIAPI
+PMPI_Win_create_keyval(
+    _In_ MPI_Win_copy_attr_function* win_copy_attr_fn,
+    _In_ MPI_Win_delete_attr_function* win_delete_attr_fn,
+    _Out_ int* win_keyval,
+    _In_opt_ void* extra_state
+    );
+
+int
+MPIAPI
+MPI_Win_free_keyval(
+    _Inout_ int* win_keyval
+    );
+int
+MPIAPI
+PMPI_Win_free_keyval(
+    _Inout_ int* win_keyval
+    );
+
+int
+MPIAPI
+MPI_Win_set_attr(
+    MPI_Win win,
+    int win_keyval,
+    _In_ void* attribute_val
+    );
+int
+MPIAPI
+PMPI_Win_set_attr(
+    MPI_Win win,
+    int win_keyval,
+    _In_ void* attribute_val
+    );
+
+
+/* Predefined window key value attributes */
+#define MPI_WIN_BASE        0x66000001
+#define MPI_WIN_SIZE        0x66000003
+#define MPI_WIN_DISP_UNIT   0x66000005
+
+int
+MPIAPI
+MPI_Win_get_attr(
+    MPI_Win win,
+    int win_keyval,
+    _Out_ void* attribute_val,
+    _Out_ int* flag
+    );
+int
+MPIAPI
+PMPI_Win_get_attr(
+    MPI_Win win,
+    int win_keyval,
+    _Out_ void* attribute_val,
+    _Out_ int* flag
+    );
+
+int
+MPIAPI
+MPI_Win_delete_attr(
+    MPI_Win win,
+    int win_keyval
+    );
+int
+MPIAPI
+PMPI_Win_delete_attr(
+    MPI_Win win,
+    int win_keyval
+    );
+
+
+typedef
+int
+(MPIAPI MPI_Type_copy_attr_function)(
+    MPI_Datatype olddatatype,
+    int datatype_keyval,
+    _In_opt_ void* extra_state,
+    _In_ void* attribute_val_in,
+    _Out_ void* attribute_val_out,
+    _Out_ int* flag
+    );
+
+typedef
+int
+(MPIAPI MPI_Type_delete_attr_function)(
+    MPI_Datatype datatype,
+    int datatype_keyval,
+    _In_ void* attribute_val,
+    _In_opt_ void* extra_state
+    );
+
+#define MPI_TYPE_NULL_COPY_FN ((MPI_Type_copy_attr_function*)0)
+#define MPI_TYPE_NULL_DELETE_FN ((MPI_Type_delete_attr_function*)0)
+#define MPI_TYPE_DUP_FN ((MPI_Type_copy_attr_function*)MPIR_Dup_fn)
+
+int
+MPIAPI
+MPI_Type_create_keyval(
+    _In_ MPI_Type_copy_attr_function* type_copy_attr_fn,
+    _In_ MPI_Type_delete_attr_function* type_delete_attr_fn,
+    _Out_ int* type_keyval,
+    _In_opt_ void* extra_state
+    );
+int
+MPIAPI
+PMPI_Type_create_keyval(
+    _In_ MPI_Type_copy_attr_function* type_copy_attr_fn,
+    _In_ MPI_Type_delete_attr_function* type_delete_attr_fn,
+    _Out_ int* type_keyval,
+    _In_opt_ void* extra_state
+    );
+
+int
+MPIAPI
+MPI_Type_free_keyval(
+    _Inout_ int* type_keyval
+    );
+int
+MPIAPI
+PMPI_Type_free_keyval(
+    _Inout_ int* type_keyval
+    );
+
+int
+MPIAPI
+MPI_Type_set_attr(
+    MPI_Datatype type,
+    int type_keyval,
+    _In_ void* attribute_val
+    );
+int
+MPIAPI
+PMPI_Type_set_attr(
+    MPI_Datatype type,
+    int type_keyval,
+    _In_ void* attribute_val
+    );
+
+int
+MPIAPI
+MPI_Type_get_attr(
+    MPI_Datatype type,
+    int type_keyval,
+    _Out_ void* attribute_val,
+    _Out_ int* flag
+    );
+int
+MPIAPI
+PMPI_Type_get_attr(
+    MPI_Datatype type,
+    int type_keyval,
+    _Out_ void* attribute_val,
+    _Out_ int* flag
+    );
+
+int
+MPIAPI
+MPI_Type_delete_attr(
+    MPI_Datatype datatype,
+    int type_keyval
+    );
+int
+MPIAPI
+PMPI_Type_delete_attr(
+    MPI_Datatype datatype,
+    int type_keyval
+    );
+
+
+/*---------------------------------------------*/
+/* Section 6.8: Naming Objects                 */
+/*---------------------------------------------*/
+
+#define MPI_MAX_OBJECT_NAME 128
+
+int
+MPIAPI
+MPI_Comm_set_name(
+    MPI_Comm comm,
+    _In_z_ char* comm_name
+    );
+int
+MPIAPI
+PMPI_Comm_set_name(
+    MPI_Comm comm,
+    _In_z_ char* comm_name
+    );
+
+int
+MPIAPI
+MPI_Comm_get_name(
+    MPI_Comm comm,
+    _Out_z_cap_post_count_(MPI_MAX_OBJECT_NAME,*resultlen) char* comm_name,
+    _Out_ int* resultlen
+    );
+int
+MPIAPI
+PMPI_Comm_get_name(
+    MPI_Comm comm,
+    _Out_z_cap_post_count_(MPI_MAX_OBJECT_NAME,*resultlen) char* comm_name,
+    _Out_ int* resultlen
+    );
+
+int
+MPIAPI
+MPI_Type_set_name(
+    MPI_Datatype type,
+    _In_z_ char* type_name
+    );
+int
+MPIAPI
+PMPI_Type_set_name(
+    MPI_Datatype type,
+    _In_z_ char* type_name
+    );
+
+int
+MPIAPI
+MPI_Type_get_name(
+    MPI_Datatype type,
+    _Out_z_cap_post_count_(MPI_MAX_OBJECT_NAME,*resultlen) char* type_name,
+    _Out_ int* resultlen
+    );
+int
+MPIAPI
+PMPI_Type_get_name(
+    MPI_Datatype type,
+    _Out_z_cap_post_count_(MPI_MAX_OBJECT_NAME,*resultlen) char* type_name,
+    _Out_ int* resultlen
+    );
+
+int
+MPIAPI
+MPI_Win_set_name(
+    MPI_Win win,
+    _In_z_ char* win_name
+    );
+int
+MPIAPI
+PMPI_Win_set_name(
+    MPI_Win win,
+    _In_z_ char* win_name
+    );
+
+int
+MPIAPI
+MPI_Win_get_name(
+    MPI_Win win,
+    _Out_z_cap_post_count_(MPI_MAX_OBJECT_NAME,*resultlen) char* win_name,
+    _Out_ int* resultlen
+    );
+int
+MPIAPI
+PMPI_Win_get_name(
+    MPI_Win win,
+    _Out_z_cap_post_count_(MPI_MAX_OBJECT_NAME,*resultlen) char* win_name,
+    _Out_ int* resultlen
+    );
+
+
+/*---------------------------------------------------------------------------*/
+/* Chapter 7: Process Topologies                                             */
+/*---------------------------------------------------------------------------*/
+
+int
+MPIAPI
+MPI_Cart_create(
+    MPI_Comm comm_old,
+    int ndims,
+    _In_count_(ndims) int* dims,
+    _In_count_(ndims) int* periods,
+    int reorder,
+    _Out_ MPI_Comm* comm_cart
+    );
+int
+MPIAPI
+PMPI_Cart_create(
+    MPI_Comm comm_old,
+    int ndims,
+    _In_count_(ndims) int* dims,
+    _In_count_(ndims) int* periods,
+    int reorder,
+    _Out_ MPI_Comm* comm_cart
+    );
+
+int
+MPIAPI
+MPI_Dims_create(
+    int nnodes,
+    int ndims,
+    _Inout_count_(ndims) int* dims
+    );
+int
+MPIAPI
+PMPI_Dims_create(
+    int nnodes,
+    int ndims,
+    _Inout_count_(ndims) int* dims
+    );
+
+int
+MPIAPI
+MPI_Graph_create(
+    MPI_Comm comm_old,
+    int nnodes,
+    _In_count_(nnodes) int* index,
+    _In_ int* edges,
+    int reorder,
+    _Out_ MPI_Comm* comm_cart
+    );
+int
+MPIAPI
+PMPI_Graph_create(
+    MPI_Comm comm_old,
+    int nnodes,
+    _In_count_(nnodes) int* index,
+    _In_ int* edges,
+    int reorder,
+    _Out_ MPI_Comm* comm_cart
+    );
+
+
+/* Topology types */
+enum
+{
+    MPI_GRAPH   = 1,
+    MPI_CART    = 2
+};
+
+int
+MPIAPI
+MPI_Topo_test(
+    MPI_Comm comm,
+    _Out_ int* status
+    );
+int
+MPIAPI
+PMPI_Topo_test(
+    MPI_Comm comm,
+    _Out_ int* status
+    );
+
+int
+MPIAPI
+MPI_Graphdims_get(
+    MPI_Comm comm,
+    _Out_ int* nnodes,
+    _Out_ int* nedges
+    );
+int
+MPIAPI
+PMPI_Graphdims_get(
+    MPI_Comm comm,
+    _Out_ int* nnodes,
+    _Out_ int* nedges
+    );
+
+int
+MPIAPI
+MPI_Graph_get(
+    MPI_Comm comm,
+    int maxindex,
+    int maxedges,
+    _Out_cap_(maxindex) int* index,
+    _Out_cap_(maxedges) int* edges
+    );
+int
+MPIAPI
+PMPI_Graph_get(
+    MPI_Comm comm,
+    int maxindex,
+    int maxedges,
+    _Out_cap_(maxindex) int* index,
+    _Out_cap_(maxedges) int* edges
+    );
+
+int
+MPIAPI
+MPI_Cartdim_get(
+    MPI_Comm comm,
+    _Out_ int* ndims
+    );
+int
+MPIAPI
+PMPI_Cartdim_get(
+    MPI_Comm comm,
+    _Out_ int* ndims
+    );
+
+int
+MPIAPI
+MPI_Cart_get(
+    MPI_Comm comm,
+    int maxdims,
+    _Out_cap_(maxdims) int* dims,
+    _Out_cap_(maxdims) int* periods,
+    _Out_cap_(maxdims) int* coords
+    );
+int
+MPIAPI
+PMPI_Cart_get(
+    MPI_Comm comm,
+    int maxdims,
+    _Out_cap_(maxdims) int* dims,
+    _Out_cap_(maxdims) int* periods,
+    _Out_cap_(maxdims) int* coords
+    );
+
+int
+MPIAPI
+MPI_Cart_rank(
+    MPI_Comm comm,
+    _In_ int* coords,
+    _Out_ int* rank
+    );
+int
+MPIAPI
+PMPI_Cart_rank(
+    MPI_Comm comm,
+    _In_ int* coords,
+    _Out_ int* rank
+    );
+
+int
+MPIAPI
+MPI_Cart_coords(
+    MPI_Comm comm,
+    int rank,
+    int maxdims,
+    _Out_cap_(maxdims) int* coords
+    );
+int
+MPIAPI
+PMPI_Cart_coords(
+    MPI_Comm comm,
+    int rank,
+    int maxdims,
+    _Out_cap_(maxdims) int* coords
+    );
+
+int
+MPIAPI
+MPI_Graph_neighbors_count(
+    MPI_Comm comm,
+    int rank,
+    _Out_ int* nneighbors
+    );
+int
+MPIAPI
+PMPI_Graph_neighbors_count(
+    MPI_Comm comm,
+    int rank,
+    _Out_ int* nneighbors
+    );
+
+int
+MPIAPI
+MPI_Graph_neighbors(
+    MPI_Comm comm,
+    int rank,
+    int maxneighbors,
+    _Out_cap_(maxneighbors) int* neighbors
+    );
+int
+MPIAPI
+PMPI_Graph_neighbors(
+    MPI_Comm comm,
+    int rank,
+    int maxneighbors,
+    _Out_cap_(maxneighbors) int* neighbors
+    );
+
+int
+MPIAPI
+MPI_Cart_shift(
+    MPI_Comm comm,
+    int direction,
+    int disp,
+    _Out_ int* rank_source,
+    _Out_ int* rank_dest
+    );
+int
+MPIAPI
+PMPI_Cart_shift(
+    MPI_Comm comm,
+    int direction,
+    int disp,
+    _Out_ int* rank_source,
+    _Out_ int* rank_dest
+    );
+
+int
+MPIAPI
+MPI_Cart_sub(
+    MPI_Comm comm,
+    _In_ int* remain_dims,
+    _Out_ MPI_Comm* newcomm
+    );
+int
+MPIAPI
+PMPI_Cart_sub(
+    MPI_Comm comm,
+    _In_ int* remain_dims,
+    _Out_ MPI_Comm* newcomm
+    );
+
+int
+MPIAPI
+MPI_Cart_map(
+    MPI_Comm comm,
+    int ndims,
+    _In_count_(ndims) int* dims,
+    _In_count_(ndims) int* periods,
+    _Out_ int* newrank
+    );
+int
+MPIAPI
+PMPI_Cart_map(
+    MPI_Comm comm,
+    int ndims,
+    _In_count_(ndims) int* dims,
+    _In_count_(ndims) int* periods,
+    _Out_ int* newrank
+    );
+
+int
+MPIAPI
+MPI_Graph_map(
+    MPI_Comm comm,
+    int nnodes,
+    _In_count_(nnodes) int* index,
+    _In_ int* edges,
+    _Out_ int* newrank
+    );
+int
+MPIAPI
+PMPI_Graph_map(
+    MPI_Comm comm,
+    int nnodes,
+    _In_count_(nnodes) int* index,
+    _In_ int* edges,
+    _Out_ int* newrank
+    );
+
+
+/*---------------------------------------------------------------------------*/
+/* Chapter 8: Environmental Management                                       */
+/*---------------------------------------------------------------------------*/
+
+/*---------------------------------------------*/
+/* Section 8.1: Implementation Information     */
+/*---------------------------------------------*/
+
+#define MPI_VERSION     2
+#define MPI_SUBVERSION  0
+
+int
+MPIAPI
+MPI_Get_version(
+    _Out_ int* version,
+    _Out_ int* subversion
+    );
+int
+MPIAPI
+PMPI_Get_version(
+    _Out_ int* version,
+    _Out_ int* subversion
+    );
+
+#define MPI_MAX_PROCESSOR_NAME  128
+
+int
+MPIAPI
+MPI_Get_processor_name(
+    _Out_z_cap_post_count_(MPI_MAX_PROCESSOR_NAME,*resultlen) char* name,
+    _Out_ int* resultlen
+    );
+int
+MPIAPI
+PMPI_Get_processor_name(
+    _Out_z_cap_post_count_(MPI_MAX_PROCESSOR_NAME,*resultlen) char* name,
+    _Out_ int* resultlen
+    );
+
+/*---------------------------------------------*/
+/* Section 8.2: Memory Allocation              */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Alloc_mem(
+    MPI_Aint size,
+    MPI_Info info,
+    _Out_ void* baseptr
+    );
+int
+MPIAPI
+PMPI_Alloc_mem(
+    MPI_Aint size,
+    MPI_Info info,
+    _Out_ void* baseptr
+    );
+
+int
+MPIAPI
+MPI_Free_mem(
+    _In_ void* base
+    );
+int
+MPIAPI
+PMPI_Free_mem(
+    _In_ void* base
+    );
+
+
+/*---------------------------------------------*/
+/* Section 8.3: Error Handling                 */
+/*---------------------------------------------*/
+
+typedef
+void
+(MPIAPI MPI_Comm_errhandler_fn)(
+    _In_ MPI_Comm* comm,
+    _Inout_ int* errcode,
+    ...
+    );
+
+int
+MPIAPI
+MPI_Comm_create_errhandler(
+    _In_ MPI_Comm_errhandler_fn* function,
+    _Out_ MPI_Errhandler* errhandler
+    );
+int
+MPIAPI
+PMPI_Comm_create_errhandler(
+    _In_ MPI_Comm_errhandler_fn* function,
+    _Out_ MPI_Errhandler* errhandler
+    );
+
+int
+MPIAPI
+MPI_Comm_set_errhandler(
+    MPI_Comm comm,
+    MPI_Errhandler errhandler
+    );
+int
+MPIAPI
+PMPI_Comm_set_errhandler(
+    MPI_Comm comm,
+    MPI_Errhandler errhandler
+    );
+
+int
+MPIAPI
+MPI_Comm_get_errhandler(
+    MPI_Comm comm,
+    _Out_ MPI_Errhandler* errhandler
+    );
+int
+MPIAPI
+PMPI_Comm_get_errhandler(
+    MPI_Comm comm,
+    _Out_ MPI_Errhandler* errhandler
+    );
+
+
+typedef
+void
+(MPIAPI MPI_Win_errhandler_fn)(
+    _In_ MPI_Win* win,
+    _Inout_ int* errcode,
+    ...
+    );
+
+int
+MPIAPI
+MPI_Win_create_errhandler(
+    _In_ MPI_Win_errhandler_fn* function,
+    _Out_ MPI_Errhandler* errhandler
+    );
+int
+MPIAPI
+PMPI_Win_create_errhandler(
+    _In_ MPI_Win_errhandler_fn* function,
+    _Out_ MPI_Errhandler* errhandler
+    );
+
+int
+MPIAPI
+MPI_Win_set_errhandler(
+    MPI_Win win,
+    MPI_Errhandler errhandler
+    );
+int
+MPIAPI
+PMPI_Win_set_errhandler(
+    MPI_Win win,
+    MPI_Errhandler errhandler
+    );
+
+int
+MPIAPI
+MPI_Win_get_errhandler(
+    MPI_Win win,
+    _Out_ MPI_Errhandler* errhandler
+    );
+int
+MPIAPI
+PMPI_Win_get_errhandler(
+    MPI_Win win,
+    _Out_ MPI_Errhandler* errhandler
+    );
+
+
+typedef
+void
+(MPIAPI MPI_File_errhandler_fn)(
+    _In_ MPI_File* file,
+    _Inout_ int* errcode,
+    ...
+    );
+
+int
+MPIAPI
+MPI_File_create_errhandler(
+    _In_ MPI_File_errhandler_fn* function,
+    _Out_ MPI_Errhandler* errhandler
+    );
+int
+MPIAPI
+PMPI_File_create_errhandler(
+    _In_ MPI_File_errhandler_fn* function,
+    _Out_ MPI_Errhandler* errhandler
+    );
+
+int
+MPIAPI
+MPI_File_set_errhandler(
+    MPI_File file,
+    MPI_Errhandler errhandler
+    );
+int
+MPIAPI
+PMPI_File_set_errhandler(
+    MPI_File file,
+    MPI_Errhandler errhandler
+    );
+
+int
+MPIAPI
+MPI_File_get_errhandler(
+    MPI_File file,
+    _Out_ MPI_Errhandler* errhandler
+    );
+int
+MPIAPI
+PMPI_File_get_errhandler(
+    MPI_File file,
+    _Out_ MPI_Errhandler* errhandler
+    );
+
+int
+MPIAPI
+MPI_Errhandler_free(
+    _Inout_ MPI_Errhandler* errhandler
+    );
+int
+MPIAPI
+PMPI_Errhandler_free(
+    _Inout_ MPI_Errhandler* errhandler
+    );
+
+#define MPI_MAX_ERROR_STRING    512
+
+int
+MPIAPI
+MPI_Error_string(
+    int errorcode,
+    _Out_z_cap_post_count_(MPI_MAX_ERROR_STRING,*resultlen) char* string,
+    _Out_ int* resultlen
+    );
+int
+MPIAPI
+PMPI_Error_string(
+    int errorcode,
+    _Out_z_cap_post_count_(MPI_MAX_ERROR_STRING,*resultlen) char* string,
+    _Out_ int* resultlen
+    );
+
+
+/*---------------------------------------------*/
+/* Section 8.4: Error Codes and Classes        */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Error_class(
+    int errorcode,
+    _Out_ int* errorclass
+    );
+int
+MPIAPI
+PMPI_Error_class(
+    int errorcode,
+    _Out_ int* errorclass
+    );
+
+int
+MPIAPI
+MPI_Add_error_class(
+    _Out_ int* errorclass
+    );
+int
+MPIAPI
+PMPI_Add_error_class(
+    _Out_ int* errorclass
+    );
+
+int
+MPIAPI
+MPI_Add_error_code(
+    int errorclass,
+    _Out_ int* errorcode
+    );
+int
+MPIAPI
+PMPI_Add_error_code(
+    int errorclass,
+    _Out_ int* errorcode
+    );
+
+int
+MPIAPI
+MPI_Add_error_string(
+    int errorcode,
+    _In_z_ char* string
+    );
+int
+MPIAPI
+PMPI_Add_error_string(
+    int errorcode,
+    _In_z_ char* string
+    );
+
+int
+MPIAPI
+MPI_Comm_call_errhandler(
+    MPI_Comm comm,
+    int errorcode
+    );
+int
+MPIAPI
+PMPI_Comm_call_errhandler(
+    MPI_Comm comm,
+    int errorcode
+    );
+
+int
+MPIAPI
+MPI_Win_call_errhandler(
+    MPI_Win win,
+    int errcode
+    );
+int
+MPIAPI
+PMPI_Win_call_errhandler(
+    MPI_Win win,
+    int errcode
+    );
+
+int
+MPIAPI
+MPI_File_call_errhandler(
+    MPI_File file,
+    int errorcode
+    );
+int
+MPIAPI
+PMPI_File_call_errhandler(
+    MPI_File file,
+    int errorcode
+    );
+
+
+/*---------------------------------------------*/
+/* Section 8.6: Timers and Synchronization     */
+/*---------------------------------------------*/
+
+double
+MPIAPI
+MPI_Wtime(
+    void
+    );
+double
+MPIAPI
+PMPI_Wtime(
+    void
+    );
+
+double
+MPIAPI
+MPI_Wtick(
+    void
+    );
+double
+MPIAPI
+PMPI_Wtick(
+    void
+    );
+
+
+/*---------------------------------------------*/
+/* Section 8.7: Startup                        */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Init(
+    _In_opt_ int* argc,
+    _In_opt_count_(*argc) char*** argv
+    );
+int
+MPIAPI
+PMPI_Init(
+    _In_opt_ int* argc,
+    _In_opt_count_(*argc) char*** argv
+    );
+
+int
+MPIAPI
+MPI_Finalize(
+    void
+    );
+int
+MPIAPI
+PMPI_Finalize(
+    void
+    );
+
+int
+MPIAPI
+MPI_Initialized(
+    _Out_ int* flag
+    );
+int
+MPIAPI
+PMPI_Initialized(
+    _Out_ int* flag
+    );
+
+int
+MPIAPI
+MPI_Abort(
+    MPI_Comm comm,
+    int errorcode
+    );
+int
+MPIAPI
+PMPI_Abort(
+    MPI_Comm comm,
+    int errorcode
+    );
+
+int
+MPIAPI
+MPI_Finalized(
+    _Out_ int* flag
+    );
+int
+MPIAPI
+PMPI_Finalized(
+    _Out_ int* flag
+    );
+
+
+/*---------------------------------------------------------------------------*/
+/* Chapter 9: The Info Object                                                */
+/*---------------------------------------------------------------------------*/
+
+#define MPI_MAX_INFO_KEY    255
+#define MPI_MAX_INFO_VAL   1024
+
+int
+MPIAPI
+MPI_Info_create(
+    _Out_ MPI_Info* info
+    );
+int
+MPIAPI
+PMPI_Info_create(
+    _Out_ MPI_Info* info
+    );
+
+int
+MPIAPI
+MPI_Info_set(
+    MPI_Info info,
+    _In_z_ char* key,
+    _In_z_ char* value
+    );
+int
+MPIAPI
+PMPI_Info_set(
+    MPI_Info info,
+    _In_z_ char* key,
+    _In_z_ char* value
+    );
+
+int
+MPIAPI
+MPI_Info_delete(
+    MPI_Info info,
+    _In_z_ char* key
+    );
+int
+MPIAPI
+PMPI_Info_delete(
+    MPI_Info info,
+    _In_z_ char* key
+    );
+
+int
+MPIAPI
+MPI_Info_get(
+    MPI_Info info,
+    _In_z_ char* key,
+    int valuelen,
+    _Out_z_cap_(valuelen) char* value,
+    _Out_ int* flag
+    );
+int
+MPIAPI
+PMPI_Info_get(
+    MPI_Info info,
+    _In_z_ char* key,
+    int valuelen,
+    _Out_z_cap_(valuelen) char* value,
+    _Out_ int* flag
+    );
+
+int
+MPIAPI
+MPI_Info_get_valuelen(
+    MPI_Info info,
+    _In_z_ char* key,
+    _Out_ int* valuelen,
+    _Out_ int* flag
+    );
+int
+MPIAPI
+PMPI_Info_get_valuelen(
+    MPI_Info info,
+    _In_z_ char* key,
+    _Out_ int* valuelen,
+    _Out_ int* flag
+    );
+
+int
+MPIAPI
+MPI_Info_get_nkeys(
+    MPI_Info info,
+    _Out_ int* nkeys
+    );
+int
+MPIAPI
+PMPI_Info_get_nkeys(
+    MPI_Info info,
+    _Out_ int* nkeys
+    );
+
+int
+MPIAPI
+MPI_Info_get_nthkey(
+    MPI_Info info,
+    int n,
+    _Out_z_cap_(MPI_MAX_INFO_KEY) char* key
+    );
+int
+MPIAPI
+PMPI_Info_get_nthkey(
+    MPI_Info info,
+    int n,
+    _Out_z_cap_(MPI_MAX_INFO_KEY) char* key
+    );
+
+int
+MPIAPI
+MPI_Info_dup(
+    MPI_Info info,
+    _Out_ MPI_Info* newinfo
+    );
+int
+MPIAPI
+PMPI_Info_dup(
+    MPI_Info info,
+    _Out_ MPI_Info* newinfo
+    );
+
+int
+MPIAPI
+MPI_Info_free(
+    _Inout_ MPI_Info* info
+    );
+int
+MPIAPI
+PMPI_Info_free(
+    _Inout_ MPI_Info* info
+    );
+
+
+/*---------------------------------------------------------------------------*/
+/* Chapter 10: Process Creation and Management                               */
+/*---------------------------------------------------------------------------*/
+
+/*---------------------------------------------*/
+/* Section 10.3: Process Manager Interface     */
+/*---------------------------------------------*/
+
+#define MPI_ARGV_NULL ((char**)0)
+#define MPI_ARGVS_NULL ((char***)0)
+
+#define MPI_ERRCODES_IGNORE ((int*)0)
+
+int
+MPIAPI
+MPI_Comm_spawn(
+    _In_z_ char* command,
+    _In_ char* argv[],
+    int maxprocs,
+    MPI_Info info,
+    int root,
+    MPI_Comm comm,
+    _Out_ MPI_Comm* intercomm,
+    _Out_opt_cap_(maxprocs) int array_of_errcodes[]
+    );
+int
+MPIAPI
+PMPI_Comm_spawn(
+    _In_z_ char* command,
+    _In_ char* argv[],
+    int maxprocs,
+    MPI_Info info,
+    int root,
+    MPI_Comm comm,
+    _Out_ MPI_Comm* intercomm,
+    _Out_opt_cap_(maxprocs) int array_of_errcodes[]
+    );
+
+int
+MPIAPI
+MPI_Comm_get_parent(
+    _Out_ MPI_Comm* parent
+    );
+int
+MPIAPI
+PMPI_Comm_get_parent(
+    _Out_ MPI_Comm* parent
+    );
+
+int
+MPIAPI
+MPI_Comm_spawn_multiple(
+    int count,
+    _In_count_(count) char* array_of_commands[],
+    _In_opt_count_(count) char** array_of_argv[],
+    _In_count_(count) int array_of_maxprocs[],
+    _In_count_(count) MPI_Info array_of_info[],
+    int root,
+    MPI_Comm comm,
+    _Out_ MPI_Comm* intercomm,
+    _Out_opt_ int array_of_errcodes[]
+    );
+int
+MPIAPI
+PMPI_Comm_spawn_multiple(
+    int count,
+    _In_count_(count) char* array_of_commands[],
+    _In_opt_count_(count) char** array_of_argv[],
+    _In_count_(count) int array_of_maxprocs[],
+    _In_count_(count) MPI_Info array_of_info[],
+    int root,
+    MPI_Comm comm,
+    _Out_ MPI_Comm* intercomm,
+    _Out_opt_ int array_of_errcodes[]
+    );
+
+
+/*---------------------------------------------*/
+/* Section 10.4: Establishing Communication    */
+/*---------------------------------------------*/
+
+#define MPI_MAX_PORT_NAME   256
+
+int
+MPIAPI
+MPI_Open_port(
+    MPI_Info info,
+    _Out_cap_(MPI_MAX_PORT_NAME) char* port_name
+    );
+int
+MPIAPI
+PMPI_Open_port(
+    MPI_Info info,
+    _Out_cap_(MPI_MAX_PORT_NAME) char* port_name
+    );
+
+int
+MPIAPI
+MPI_Close_port(
+    _In_z_ char* port_name
+    );
+int
+MPIAPI
+PMPI_Close_port(
+    _In_z_ char* port_name
+    );
+
+int
+MPIAPI
+MPI_Comm_accept(
+    _In_z_ char* port_name,
+    MPI_Info info,
+    int root,
+    MPI_Comm comm,
+    _Out_ MPI_Comm* newcomm
+    );
+int
+MPIAPI
+PMPI_Comm_accept(
+    _In_z_ char* port_name,
+    MPI_Info info,
+    int root,
+    MPI_Comm comm,
+    _Out_ MPI_Comm* newcomm
+    );
+
+int
+MPIAPI
+MPI_Comm_connect(
+    _In_z_ char* port_name,
+    MPI_Info info,
+    int root,
+    MPI_Comm comm,
+    _Out_ MPI_Comm* newcomm
+    );
+int
+MPIAPI
+PMPI_Comm_connect(
+    _In_z_ char* port_name,
+    MPI_Info info,
+    int root,
+    MPI_Comm comm,
+    _Out_ MPI_Comm* newcomm
+    );
+
+
+/*---------------------------------------------*/
+/* Section 10.4.4: Name Publishing             */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Publish_name(
+    _In_z_ char* service_name,
+    MPI_Info info,
+    _In_z_ char* port_name
+    );
+int
+MPIAPI
+PMPI_Publish_name(
+    _In_z_ char* service_name,
+    MPI_Info info,
+    _In_z_ char* port_name
+    );
+
+int
+MPIAPI
+MPI_Unpublish_name(
+    _In_z_ char* service_name,
+    MPI_Info info,
+    _In_z_ char* port_name
+    );
+int
+MPIAPI
+PMPI_Unpublish_name(
+    _In_z_ char* service_name,
+    MPI_Info info,
+    _In_z_ char* port_name
+    );
+
+int
+MPIAPI
+MPI_Lookup_name(
+    _In_z_ char* service_name,
+    MPI_Info info,
+    _Out_cap_(MPI_MAX_PORT_NAME) char* port_name
+    );
+int
+MPIAPI
+PMPI_Lookup_name(
+    _In_z_ char* service_name,
+    MPI_Info info,
+    _Out_cap_(MPI_MAX_PORT_NAME) char* port_name
+    );
+
+
+/*---------------------------------------------*/
+/* Section 10.5: Other Functionality           */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Comm_disconnect(
+    _In_ MPI_Comm* comm
+    );
+int
+MPIAPI
+PMPI_Comm_disconnect(
+    _In_ MPI_Comm* comm
+    );
+
+int
+MPIAPI
+MPI_Comm_join(
+    int fd,
+    _Out_ MPI_Comm* intercomm
+    );
+int
+MPIAPI
+PMPI_Comm_join(
+    int fd,
+    _Out_ MPI_Comm* intercomm
+    );
+
+
+/*---------------------------------------------------------------------------*/
+/* Chapter 11: One-Sided Communications                                      */
+/*---------------------------------------------------------------------------*/
+
+int
+MPIAPI
+MPI_Win_create(
+    _In_ void* base,
+    MPI_Aint size,
+    int disp_unit,
+    MPI_Info info,
+    MPI_Comm comm,
+    _Out_ MPI_Win* win
+    );
+int
+MPIAPI
+PMPI_Win_create(
+    _In_ void* base,
+    MPI_Aint size,
+    int disp_unit,
+    MPI_Info info,
+    MPI_Comm comm,
+    _Out_ MPI_Win* win
+    );
+
+int
+MPIAPI
+MPI_Win_free(
+    _Inout_ MPI_Win* win
+    );
+int
+MPIAPI
+PMPI_Win_free(
+    _Inout_ MPI_Win* win
+    );
+
+int
+MPIAPI
+MPI_Win_get_group(
+    MPI_Win win,
+    _Out_ MPI_Group* group
+    );
+int
+MPIAPI
+PMPI_Win_get_group(
+    MPI_Win win,
+    _Out_ MPI_Group* group
+    );
+
+int
+MPIAPI
+MPI_Put(
+    _In_ void* origin_addr,
+    int origin_count,
+    MPI_Datatype origin_datatype,
+    int target_rank,
+    MPI_Aint target_disp,
+    int target_count,
+    MPI_Datatype datatype,
+    MPI_Win win
+    );
+int
+MPIAPI
+PMPI_Put(
+    _In_ void* origin_addr,
+    int origin_count,
+    MPI_Datatype origin_datatype,
+    int target_rank,
+    MPI_Aint target_disp,
+    int target_count,
+    MPI_Datatype datatype,
+    MPI_Win win
+    );
+
+int
+MPIAPI
+MPI_Get(
+    _Out_ void* origin_addr,
+    int origin_count,
+    MPI_Datatype origin_datatype,
+    int target_rank,
+    MPI_Aint target_disp,
+    int target_count,
+    MPI_Datatype datatype,
+    MPI_Win win
+    );
+int
+MPIAPI
+PMPI_Get(
+    _Out_ void* origin_addr,
+    int origin_count,
+    MPI_Datatype origin_datatype,
+    int target_rank,
+    MPI_Aint target_disp,
+    int target_count,
+    MPI_Datatype datatype,
+    MPI_Win win
+    );
+
+int
+MPIAPI
+MPI_Accumulate(
+    _In_ void* origin_addr,
+    int origin_count,
+    MPI_Datatype origin_datatype,
+    int target_rank,
+    MPI_Aint target_disp,
+    int target_count,
+    MPI_Datatype datatype,
+    MPI_Op op,
+    MPI_Win win
+    );
+int
+MPIAPI
+PMPI_Accumulate(
+    _In_ void* origin_addr,
+    int origin_count,
+    MPI_Datatype origin_datatype,
+    int target_rank,
+    MPI_Aint target_disp,
+    int target_count,
+    MPI_Datatype datatype,
+    MPI_Op op,
+    MPI_Win win
+    );
+
+/* Asserts for one-sided communication */
+#define MPI_MODE_NOCHECK    1024
+#define MPI_MODE_NOSTORE    2048
+#define MPI_MODE_NOPUT      4096
+#define MPI_MODE_NOPRECEDE  8192
+#define MPI_MODE_NOSUCCEED 16384
+
+int
+MPIAPI
+MPI_Win_fence(
+    int assert,
+    MPI_Win win
+    );
+int
+MPIAPI
+PMPI_Win_fence(
+    int assert,
+    MPI_Win win
+    );
+
+int
+MPIAPI
+MPI_Win_start(
+    MPI_Group group,
+    int assert,
+    MPI_Win win
+    );
+int
+MPIAPI
+PMPI_Win_start(
+    MPI_Group group,
+    int assert,
+    MPI_Win win
+    );
+
+int
+MPIAPI
+MPI_Win_complete(
+    MPI_Win win
+    );
+int
+MPIAPI
+PMPI_Win_complete(
+    MPI_Win win
+    );
+
+int
+MPIAPI
+MPI_Win_post(
+    MPI_Group group,
+    int assert,
+    MPI_Win win
+    );
+int
+MPIAPI
+PMPI_Win_post(
+    MPI_Group group,
+    int assert,
+    MPI_Win win
+    );
+
+int
+MPIAPI
+MPI_Win_wait(
+    MPI_Win win
+    );
+int
+MPIAPI
+PMPI_Win_wait(
+    MPI_Win win
+    );
+
+int
+MPIAPI
+MPI_Win_test(
+    MPI_Win win,
+    _Out_ int* flag
+    );
+int
+MPIAPI
+PMPI_Win_test(
+    MPI_Win win,
+    _Out_ int* flag
+    );
+
+#define MPI_LOCK_EXCLUSIVE  234
+#define MPI_LOCK_SHARED     235
+
+int
+MPIAPI
+MPI_Win_lock(
+    int lock_type,
+    int rank,
+    int assert,
+    MPI_Win win
+    );
+int
+MPIAPI
+PMPI_Win_lock(
+    int lock_type,
+    int rank,
+    int assert,
+    MPI_Win win
+    );
+
+int
+MPIAPI
+MPI_Win_unlock(
+    int rank,
+    MPI_Win win
+    );
+int
+MPIAPI
+PMPI_Win_unlock(
+    int rank,
+    MPI_Win win
+    );
+
+
+/*---------------------------------------------------------------------------*/
+/* Chapter 12: External Interfaces                                           */
+/*---------------------------------------------------------------------------*/
+
+/*---------------------------------------------*/
+/* Section 12.2: Generalized Requests          */
+/*---------------------------------------------*/
+
+typedef
+int
+(MPIAPI MPI_Grequest_query_function)(
+    _In_opt_ void* extra_state,
+    _Out_ MPI_Status* status
+    );
+
+typedef
+int
+(MPIAPI MPI_Grequest_free_function)(
+    _In_opt_ void* extra_state
+    );
+
+typedef
+int
+(MPIAPI MPI_Grequest_cancel_function)(
+    _In_opt_ void* extra_state,
+    int complete
+    );
+
+int
+MPIAPI
+MPI_Grequest_start(
+    _In_ MPI_Grequest_query_function* query_fn,
+    _In_ MPI_Grequest_free_function* free_fn,
+    _In_ MPI_Grequest_cancel_function* cancel_fn,
+    _In_opt_ void* extra_state,
+    _Out_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_Grequest_start(
+    _In_ MPI_Grequest_query_function* query_fn,
+    _In_ MPI_Grequest_free_function* free_fn,
+    _In_ MPI_Grequest_cancel_function* cancel_fn,
+    _In_opt_ void* extra_state,
+    _Out_ MPI_Request* request
+    );
+
+int
+MPIAPI
+MPI_Grequest_complete(
+    MPI_Request request
+    );
+int
+MPIAPI
+PMPI_Grequest_complete(
+    MPI_Request request
+    );
+
+
+/*---------------------------------------------*/
+/* Section 12.3: Information with Status       */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Status_set_elements(
+    _In_ MPI_Status* status,
+    MPI_Datatype datatype,
+    int count
+    );
+int
+MPIAPI
+PMPI_Status_set_elements(
+    _In_ MPI_Status* status,
+    MPI_Datatype datatype,
+    int count
+    );
+
+int
+MPIAPI
+MPI_Status_set_cancelled(
+    _In_ MPI_Status* status,
+    int flag
+    );
+int
+MPIAPI
+PMPI_Status_set_cancelled(
+    _In_ MPI_Status* status,
+    int flag
+    );
+
+
+/*---------------------------------------------*/
+/* Section 12.4: Threads                       */
+/*---------------------------------------------*/
+
+#define MPI_THREAD_SINGLE       0
+#define MPI_THREAD_FUNNELED     1
+#define MPI_THREAD_SERIALIZED   2
+#define MPI_THREAD_MULTIPLE     3
+
+int
+MPIAPI
+MPI_Init_thread(
+    _In_opt_ int* argc,
+    _In_opt_count_(*argc) char*** argv,
+    int required,
+    _Out_ int* provided
+    );
+int
+MPIAPI
+PMPI_Init_thread(
+    _In_opt_ int* argc,
+    _In_opt_count_(*argc) char*** argv,
+    int required,
+    _Out_ int* provided
+    );
+
+int
+MPIAPI
+MPI_Query_thread(
+    _Out_ int* provided
+    );
+int
+MPIAPI
+PMPI_Query_thread(
+    _Out_ int* provided
+    );
+
+int
+MPIAPI
+MPI_Is_thread_main(
+    _Out_ int* flag
+    );
+int
+MPIAPI
+PMPI_Is_thread_main(
+    _Out_ int* flag
+    );
+
+
+/*---------------------------------------------------------------------------*/
+/* Chapter 13: I/O                                                           */
+/*---------------------------------------------------------------------------*/
+
+/*---------------------------------------------*/
+/* Section 13.2: File Manipulation             */
+/*---------------------------------------------*/
+
+#define MPI_MODE_CREATE             0x00000001
+#define MPI_MODE_RDONLY             0x00000002
+#define MPI_MODE_WRONLY             0x00000004
+#define MPI_MODE_RDWR               0x00000008
+#define MPI_MODE_DELETE_ON_CLOSE    0x00000010
+#define MPI_MODE_UNIQUE_OPEN        0x00000020
+#define MPI_MODE_EXCL               0x00000040
+#define MPI_MODE_APPEND             0x00000080
+#define MPI_MODE_SEQUENTIAL         0x00000100
+#define MSMPI_MODE_HIDDEN           0x00000200
+
+int
+MPIAPI
+MPI_File_open(
+    MPI_Comm comm,
+    _In_z_ char* filename,
+    int amode,
+    MPI_Info info,
+    _Out_ MPI_File* newfile
+    );
+int
+MPIAPI
+PMPI_File_open(
+    MPI_Comm comm,
+    _In_z_ char* filename,
+    int amode,
+    MPI_Info info,
+    _Out_ MPI_File* newfile
+    );
+
+int
+MPIAPI
+MPI_File_close(
+    _In_ MPI_File* file
+    );
+int
+MPIAPI
+PMPI_File_close(
+    _In_ MPI_File* file
+    );
+
+int
+MPIAPI
+MPI_File_delete(
+    _In_z_ char* filename,
+    MPI_Info info
+    );
+int
+MPIAPI
+PMPI_File_delete(
+    _In_z_ char* filename,
+    MPI_Info info
+    );
+
+int
+MPIAPI
+MPI_File_set_size(
+    MPI_File file,
+    MPI_Offset size
+    );
+int
+MPIAPI
+PMPI_File_set_size(
+    MPI_File file,
+    MPI_Offset size
+    );
+
+int
+MPIAPI
+MPI_File_preallocate(
+    MPI_File file,
+    MPI_Offset size
+    );
+int
+MPIAPI
+PMPI_File_preallocate(
+    MPI_File file,
+    MPI_Offset size
+    );
+
+int
+MPIAPI
+MPI_File_get_size(
+    MPI_File file,
+    _Out_ MPI_Offset* size
+    );
+int
+MPIAPI
+PMPI_File_get_size(
+    MPI_File file,
+    _Out_ MPI_Offset* size
+    );
+
+int
+MPIAPI
+MPI_File_get_group(
+    MPI_File file,
+    _Out_ MPI_Group* group
+    );
+int
+MPIAPI
+PMPI_File_get_group(
+    MPI_File file,
+    _Out_ MPI_Group* group
+    );
+
+int
+MPIAPI
+MPI_File_get_amode(
+    MPI_File file,
+    _Out_ int* amode
+    );
+int
+MPIAPI
+PMPI_File_get_amode(
+    MPI_File file,
+    _Out_ int* amode
+    );
+
+int
+MPIAPI
+MPI_File_set_info(
+    MPI_File file,
+    MPI_Info info
+    );
+int
+MPIAPI
+PMPI_File_set_info(
+    MPI_File file,
+    MPI_Info info
+    );
+
+int
+MPIAPI
+MPI_File_get_info(
+    MPI_File file,
+    _Out_ MPI_Info* info
+    );
+int
+MPIAPI
+PMPI_File_get_info(
+    MPI_File file,
+    _Out_ MPI_Info* info
+    );
+
+
+/*---------------------------------------------*/
+/* Section 13.3: File Views                    */
+/*---------------------------------------------*/
+
+#define MPI_DISPLACEMENT_CURRENT (-54278278)
+
+int
+MPIAPI
+MPI_File_set_view(
+    MPI_File file,
+    MPI_Offset disp,
+    MPI_Datatype etype,
+    MPI_Datatype filetype,
+    _In_z_ char* datarep,
+    MPI_Info info
+    );
+int
+MPIAPI
+PMPI_File_set_view(
+    MPI_File file,
+    MPI_Offset disp,
+    MPI_Datatype etype,
+    MPI_Datatype filetype,
+    _In_z_ char* datarep,
+    MPI_Info info
+    );
+
+#define MPI_MAX_DATAREP_STRING  128
+
+int
+MPIAPI
+MPI_File_get_view(
+    MPI_File file,
+    _Out_ MPI_Offset* disp,
+    _Out_ MPI_Datatype* etype,
+    _Out_ MPI_Datatype* filetype,
+    _Out_z_cap_(MPI_MAX_DATAREP_STRING) char* datarep
+    );
+int
+MPIAPI
+PMPI_File_get_view(
+    MPI_File file,
+    _Out_ MPI_Offset* disp,
+    _Out_ MPI_Datatype* etype,
+    _Out_ MPI_Datatype* filetype,
+    _Out_z_cap_(MPI_MAX_DATAREP_STRING) char* datarep
+    );
+
+
+/*---------------------------------------------*/
+/* Section 13.4: Data Access                   */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_File_read_at(
+    MPI_File file,
+    MPI_Offset offset,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_File_read_at(
+    MPI_File file,
+    MPI_Offset offset,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_File_read_at_all(
+    MPI_File file,
+    MPI_Offset offset,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_File_read_at_all(
+    MPI_File file,
+    MPI_Offset offset,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_File_write_at(
+    MPI_File file,
+    MPI_Offset offset,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_File_write_at(
+    MPI_File file,
+    MPI_Offset offset,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_File_write_at_all(
+    MPI_File file,
+    MPI_Offset offset,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_File_write_at_all(
+    MPI_File file,
+    MPI_Offset offset,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_File_iread_at(
+    MPI_File file,
+    MPI_Offset offset,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_File_iread_at(
+    MPI_File file,
+    MPI_Offset offset,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Request* request
+    );
+
+int
+MPIAPI
+MPI_File_iwrite_at(
+    MPI_File file,
+    MPI_Offset offset,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_File_iwrite_at(
+    MPI_File file,
+    MPI_Offset offset,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Request* request
+    );
+
+int
+MPIAPI
+MPI_File_read(
+    MPI_File file,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_File_read(
+    MPI_File file,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_File_read_all(
+    MPI_File file,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_File_read_all(
+    MPI_File file,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_File_write(
+    MPI_File file,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_File_write(
+    MPI_File file,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_File_write_all(
+    MPI_File file,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_File_write_all(
+    MPI_File file,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+
+
+int
+MPIAPI
+MPI_File_iread(
+    MPI_File file,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_File_iread(
+    _In_ MPI_File file,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Request* request
+    );
+
+int
+MPIAPI
+MPI_File_iwrite(
+    MPI_File file,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_File_iwrite(
+    MPI_File file,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Request* request
+    );
+
+
+/* File seek whence */
+#define MPI_SEEK_SET    600
+#define MPI_SEEK_CUR    602
+#define MPI_SEEK_END    604
+
+int
+MPIAPI
+MPI_File_seek(
+    MPI_File file,
+    MPI_Offset offset,
+    int whence
+    );
+int
+MPIAPI
+PMPI_File_seek(
+    MPI_File file,
+    MPI_Offset offset,
+    int whence
+    );
+
+int
+MPIAPI
+MPI_File_get_position(
+    MPI_File file,
+    _Out_ MPI_Offset* offset
+    );
+int
+MPIAPI
+PMPI_File_get_position(
+    MPI_File file,
+    _Out_ MPI_Offset* offset
+    );
+
+int
+MPIAPI
+MPI_File_get_byte_offset(
+    MPI_File file,
+    MPI_Offset offset,
+    _Out_ MPI_Offset* disp
+    );
+int
+MPIAPI
+PMPI_File_get_byte_offset(
+    MPI_File file,
+    MPI_Offset offset,
+    _Out_ MPI_Offset* disp
+    );
+
+int
+MPIAPI
+MPI_File_read_shared(
+    MPI_File file,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+     );
+int
+MPIAPI
+PMPI_File_read_shared(
+    MPI_File file,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+     );
+
+int
+MPIAPI
+MPI_File_write_shared(
+    MPI_File file,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_File_write_shared(
+    MPI_File file,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_File_iread_shared(
+    MPI_File file,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_File_iread_shared(
+    MPI_File file,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Request* request
+    );
+
+int
+MPIAPI
+MPI_File_iwrite_shared(
+    MPI_File file,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_File_iwrite_shared(
+    MPI_File file,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Request* request
+    );
+
+int
+MPIAPI
+MPI_File_read_ordered(
+    MPI_File file,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_File_read_ordered(
+    MPI_File file,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_File_write_ordered(
+    _In_ MPI_File file,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_File_write_ordered(
+    MPI_File file,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_File_seek_shared(
+    MPI_File file,
+    MPI_Offset offset,
+    int whence
+    );
+int
+MPIAPI
+PMPI_File_seek_shared(
+    MPI_File file,
+    MPI_Offset offset,
+    int whence
+    );
+
+int
+MPIAPI
+MPI_File_get_position_shared(
+    MPI_File file,
+    _Out_ MPI_Offset* offset
+    );
+int
+MPIAPI
+PMPI_File_get_position_shared(
+    MPI_File file,
+    _Out_ MPI_Offset* offset
+    );
+
+int
+MPIAPI
+MPI_File_read_at_all_begin(
+    MPI_File file,
+    MPI_Offset offset,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype
+    );
+int
+MPIAPI
+PMPI_File_read_at_all_begin(
+    MPI_File file,
+    MPI_Offset offset,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype
+    );
+
+int
+MPIAPI
+MPI_File_read_at_all_end(
+    MPI_File file,
+    _Out_ void* buf,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_File_read_at_all_end(
+    MPI_File file,
+    _Out_ void* buf,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_File_write_at_all_begin(
+    MPI_File file,
+    MPI_Offset offset,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype
+    );
+int
+MPIAPI
+PMPI_File_write_at_all_begin(
+    MPI_File file,
+    MPI_Offset offset,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype
+    );
+
+int
+MPIAPI
+MPI_File_write_at_all_end(
+    MPI_File file,
+    _In_ void* buf,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_File_write_at_all_end(
+    MPI_File file,
+    _In_ void* buf,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_File_read_all_begin(
+    MPI_File file,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype
+    );
+int
+MPIAPI
+PMPI_File_read_all_begin(
+    MPI_File file,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype
+    );
+
+int
+MPIAPI
+MPI_File_read_all_end(
+    MPI_File file,
+    _Out_ void* buf,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_File_read_all_end(
+    MPI_File file,
+    _Out_ void* buf,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_File_write_all_begin(
+    MPI_File file,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype
+    );
+int
+MPIAPI
+PMPI_File_write_all_begin(
+    MPI_File file,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype
+    );
+
+int
+MPIAPI
+MPI_File_write_all_end(
+    MPI_File file,
+    _In_ void* buf,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_File_write_all_end(
+    MPI_File file,
+    _In_ void* buf,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_File_read_ordered_begin(
+    MPI_File file,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype
+    );
+int
+MPIAPI
+PMPI_File_read_ordered_begin(
+    MPI_File file,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype
+    );
+
+int
+MPIAPI
+MPI_File_read_ordered_end(
+    MPI_File file,
+    _Out_ void* buf,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_File_read_ordered_end(
+    MPI_File file,
+    _Out_ void* buf,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_File_write_ordered_begin(
+    MPI_File file,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype
+    );
+int
+MPIAPI
+PMPI_File_write_ordered_begin(
+    MPI_File file,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype
+    );
+
+int
+MPIAPI
+MPI_File_write_ordered_end(
+    MPI_File file,
+    _In_ void* buf,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_File_write_ordered_end(
+    MPI_File file,
+    _In_ void* buf,
+    _Out_ MPI_Status* status
+    );
+
+
+/*---------------------------------------------*/
+/* Section 13.5: File Interoperability         */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_File_get_type_extent(
+    MPI_File file,
+    MPI_Datatype datatype,
+    _Out_ MPI_Aint* extent
+    );
+int
+MPIAPI
+PMPI_File_get_type_extent(
+    MPI_File file,
+    MPI_Datatype datatype,
+    _Out_ MPI_Aint* extent
+    );
+
+
+typedef
+int
+(MPIAPI MPI_Datarep_conversion_function)(
+    _Inout_ void* userbuf,
+    MPI_Datatype datatype,
+    int count,
+    _Inout_ void* filebuf,
+    MPI_Offset position,
+    _In_ void* extra_state
+    );
+
+typedef
+int
+(MPIAPI MPI_Datarep_extent_function)(
+    MPI_Datatype datatype,
+    _Out_ MPI_Aint* file_extent,
+    _In_ void* extra_state
+    );
+
+#define MPI_CONVERSION_FN_NULL ((MPI_Datarep_conversion_function*)0)
+
+int
+MPIAPI
+MPI_Register_datarep(
+    _In_z_ char* datarep,
+    _In_opt_ MPI_Datarep_conversion_function* read_conversion_fn,
+    _In_opt_ MPI_Datarep_conversion_function* write_conversion_fn,
+    _In_ MPI_Datarep_extent_function* dtype_file_extent_fn,
+    _In_opt_ void* extra_state
+    );
+int
+MPIAPI
+PMPI_Register_datarep(
+    _In_z_ char* datarep,
+    _In_opt_ MPI_Datarep_conversion_function* read_conversion_fn,
+    _In_opt_ MPI_Datarep_conversion_function* write_conversion_fn,
+    _In_ MPI_Datarep_extent_function* dtype_file_extent_fn,
+    _In_opt_ void* extra_state
+    );
+
+
+/*---------------------------------------------*/
+/* Section 13.6: Consistency and Semantics     */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_File_set_atomicity(
+    MPI_File file,
+    int flag
+    );
+int
+MPIAPI
+PMPI_File_set_atomicity(
+    MPI_File file,
+    int flag
+    );
+
+int
+MPIAPI
+MPI_File_get_atomicity(
+    MPI_File file,
+    _Out_ int* flag
+    );
+int
+MPIAPI
+PMPI_File_get_atomicity(
+    MPI_File file,
+    _Out_ int* flag
+    );
+
+int
+MPIAPI
+MPI_File_sync(
+    MPI_File file
+    );
+int
+MPIAPI
+PMPI_File_sync(
+    MPI_File file
+    );
+
+
+/*---------------------------------------------------------------------------*/
+/* Chapter 14: Profiling Interface                                           */
+/*---------------------------------------------------------------------------*/
+
+int
+MPIAPI
+MPI_Pcontrol(
+    const int level,
+    ...);
+int
+MPIAPI
+PMPI_Pcontrol(
+    const int level,
+    ...);
+
+
+/*---------------------------------------------------------------------------*/
+/* Chapter 15: Depricated Functions                                          */
+/*---------------------------------------------------------------------------*/
+
+#ifdef MSMPI_NO_DEPRECATE_20
+#define MSMPI_DEPRECATE_20( x )
+#else
+#define MSMPI_DEPRECATE_20( x ) __declspec(deprecated( \
+    "Deprecated in MPI 2.0, use '" #x "'.  " \
+    "To disable deprecation, define MSMPI_NO_DEPRECATE_20." ))
+#endif
+
+MSMPI_DEPRECATE_20( MPI_Type_create_hvector )
+int
+MPIAPI
+MPI_Type_hvector(
+    int count,
+    int blocklength,
+    MPI_Aint stride,
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+MSMPI_DEPRECATE_20( PMPI_Type_create_hvector )
+int
+MPIAPI
+PMPI_Type_hvector(
+    int count,
+    int blocklength,
+    MPI_Aint stride,
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+
+MSMPI_DEPRECATE_20( MPI_Type_create_hindexed )
+int
+MPIAPI
+MPI_Type_hindexed(
+    int count,
+    _In_count_(count) int array_of_blocklengths[],
+    _In_count_(count) MPI_Aint array_of_displacements[],
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+MSMPI_DEPRECATE_20( PMPI_Type_create_hindexed )
+int
+MPIAPI
+PMPI_Type_hindexed(
+    int count,
+    _In_count_(count) int array_of_blocklengths[],
+    _In_count_(count) MPI_Aint array_of_displacements[],
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+
+MSMPI_DEPRECATE_20( MPI_Type_create_struct )
+int
+MPIAPI
+MPI_Type_struct(
+    int count,
+    _In_count_(count) int array_of_blocklengths[],
+    _In_count_(count) MPI_Aint array_of_displacements[],
+    _In_count_(count) MPI_Datatype array_of_types[],
+    _In_ MPI_Datatype* newtype
+    );
+MSMPI_DEPRECATE_20( PMPI_Type_create_struct )
+int
+MPIAPI
+PMPI_Type_struct(
+    int count,
+    _In_count_(count) int array_of_blocklengths[],
+    _In_count_(count) MPI_Aint array_of_displacements[],
+    _In_count_(count) MPI_Datatype array_of_types[],
+    _In_ MPI_Datatype* newtype
+    );
+
+MSMPI_DEPRECATE_20( MPI_Get_address )
+int
+MPIAPI
+MPI_Address(
+    _In_ void* location,
+    _Out_ MPI_Aint* address
+    );
+MSMPI_DEPRECATE_20( PMPI_Get_address )
+int
+MPIAPI
+PMPI_Address(
+    _In_ void* location,
+    _Out_ MPI_Aint* address
+    );
+
+MSMPI_DEPRECATE_20( MPI_Type_get_extent )
+int
+MPIAPI
+MPI_Type_extent(
+    MPI_Datatype datatype,
+    _Out_ MPI_Aint* extent
+    );
+MSMPI_DEPRECATE_20( PMPI_Type_get_extent )
+int
+MPIAPI
+PMPI_Type_extent(
+    MPI_Datatype datatype,
+    _Out_ MPI_Aint* extent
+    );
+
+MSMPI_DEPRECATE_20( MPI_Type_get_extent )
+int
+MPIAPI
+MPI_Type_lb(
+    MPI_Datatype datatype,
+    _Out_ MPI_Aint* displacement
+    );
+MSMPI_DEPRECATE_20( PMPI_Type_get_extent )
+int
+MPIAPI
+PMPI_Type_lb(
+    MPI_Datatype datatype,
+    _Out_ MPI_Aint* displacement
+    );
+
+MSMPI_DEPRECATE_20( MPI_Type_get_extent )
+int
+MPIAPI
+MPI_Type_ub(
+    MPI_Datatype datatype,
+    _Out_ MPI_Aint* displacement
+    );
+MSMPI_DEPRECATE_20( PMPI_Type_get_extent )
+int
+MPIAPI
+PMPI_Type_ub(
+    MPI_Datatype datatype,
+    _Out_ MPI_Aint* displacement
+    );
+
+
+typedef MPI_Comm_copy_attr_function MPI_Copy_function;
+typedef MPI_Comm_delete_attr_function MPI_Delete_function;
+
+#define MPI_NULL_COPY_FN ((MPI_Copy_function*)0)
+#define MPI_NULL_DELETE_FN ((MPI_Delete_function*)0)
+#define MPI_DUP_FN MPIR_Dup_fn
+
+
+MSMPI_DEPRECATE_20( MPI_Comm_create_keyval )
+int
+MPIAPI
+MPI_Keyval_create(
+    _In_ MPI_Copy_function* copy_fn,
+    _In_ MPI_Delete_function* delete_fn,
+    _Out_ int* keyval,
+    _In_opt_ void* extra_state
+    );
+MSMPI_DEPRECATE_20( PMPI_Comm_create_keyval )
+int
+MPIAPI
+PMPI_Keyval_create(
+    _In_ MPI_Copy_function* copy_fn,
+    _In_ MPI_Delete_function* delete_fn,
+    _Out_ int* keyval,
+    _In_opt_ void* extra_state
+    );
+
+MSMPI_DEPRECATE_20( MPI_Comm_free_keyval )
+int
+MPIAPI
+MPI_Keyval_free(
+    _Inout_ int* keyval
+    );
+MSMPI_DEPRECATE_20( PMPI_Comm_free_keyval )
+int
+MPIAPI
+PMPI_Keyval_free(
+    _Inout_ int* keyval
+    );
+
+MSMPI_DEPRECATE_20( MPI_Comm_set_attr )
+int
+MPIAPI
+MPI_Attr_put(
+    MPI_Comm comm,
+    int keyval,
+    _In_ void* attribute_val
+    );
+MSMPI_DEPRECATE_20( PMPI_Comm_set_attr )
+int
+MPIAPI
+PMPI_Attr_put(
+    MPI_Comm comm,
+    int keyval,
+    _In_ void* attribute_val
+    );
+
+MSMPI_DEPRECATE_20( MPI_Comm_get_attr )
+int
+MPIAPI
+MPI_Attr_get(
+    MPI_Comm comm,
+    int keyval,
+    _Out_ void* attribute_val,
+    _Out_ int* flag
+    );
+MSMPI_DEPRECATE_20( PMPI_Comm_get_attr )
+int
+MPIAPI
+PMPI_Attr_get(
+    MPI_Comm comm,
+    int keyval,
+    _Out_ void* attribute_val,
+    _Out_ int* flag
+    );
+
+MSMPI_DEPRECATE_20( MPI_Comm_delete_attr )
+int
+MPIAPI
+MPI_Attr_delete(
+    MPI_Comm comm,
+    int keyval
+    );
+MSMPI_DEPRECATE_20( PMPI_Comm_delete_attr )
+int
+MPIAPI
+PMPI_Attr_delete(
+    MPI_Comm comm,
+    int keyval
+    );
+
+
+typedef MPI_Comm_errhandler_fn MPI_Handler_function;
+
+MSMPI_DEPRECATE_20( MPI_Comm_create_errhandler )
+int
+MPIAPI
+MPI_Errhandler_create(
+    _In_ MPI_Handler_function* function,
+    _Out_ MPI_Errhandler* errhandler
+    );
+MSMPI_DEPRECATE_20( PMPI_Comm_create_errhandler )
+int
+MPIAPI
+PMPI_Errhandler_create(
+    _In_ MPI_Handler_function* function,
+    _Out_ MPI_Errhandler* errhandler
+    );
+
+MSMPI_DEPRECATE_20( MPI_Comm_set_errhandler )
+int
+MPIAPI
+MPI_Errhandler_set(
+    MPI_Comm comm,
+    MPI_Errhandler errhandler
+    );
+MSMPI_DEPRECATE_20( PMPI_Comm_set_errhandler )
+int
+MPIAPI
+PMPI_Errhandler_set(
+    MPI_Comm comm,
+    MPI_Errhandler errhandler
+    );
+
+MSMPI_DEPRECATE_20( MPI_Comm_get_errhandler )
+int
+MPIAPI
+MPI_Errhandler_get(
+    MPI_Comm comm,
+    _Out_ MPI_Errhandler* errhandler
+    );
+MSMPI_DEPRECATE_20( PMPI_Comm_get_errhandler )
+int
+MPIAPI
+PMPI_Errhandler_get(
+    MPI_Comm comm,
+    _Out_ MPI_Errhandler* errhandler
+    );
+
+
+/*---------------------------------------------------------------------------*/
+/* Chapter 16: Language Bindings                                             */
+/*---------------------------------------------------------------------------*/
+
+/*---------------------------------------------*/
+/* Section 16.2: Fortran Support               */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Type_create_f90_real(
+    int p,
+    int r,
+    _Out_ MPI_Datatype* newtype
+    );
+int
+MPIAPI
+PMPI_Type_create_f90_real(
+    int p,
+    int r,
+    _Out_ MPI_Datatype* newtype
+    );
+
+int
+MPIAPI
+MPI_Type_create_f90_complex(
+    int p,
+    int r,
+    _Out_ MPI_Datatype* newtype
+    );
+int
+MPIAPI
+PMPI_Type_create_f90_complex(
+    int p,
+    int r,
+    _Out_ MPI_Datatype* newtype
+    );
+
+int
+MPIAPI
+MPI_Type_create_f90_integer(
+    int r,
+    _Out_ MPI_Datatype* newtype
+    );
+int
+MPIAPI
+PMPI_Type_create_f90_integer(
+    int r,
+    _Out_ MPI_Datatype* newtype
+    );
+
+/* typeclasses */
+#define MPI_TYPECLASS_REAL      1
+#define MPI_TYPECLASS_INTEGER   2
+#define MPI_TYPECLASS_COMPLEX   3
+
+int
+MPIAPI
+MPI_Type_match_size(
+    int typeclass,
+    int size,
+    _Out_ MPI_Datatype* type
+    );
+int
+MPIAPI
+PMPI_Type_match_size(
+    int typeclass,
+    int size,
+    _Out_ MPI_Datatype* type
+    );
+
+
+/*---------------------------------------------*/
+/* Section 16.3: Language Interoperability     */
+/*---------------------------------------------*/
+
+#define MPI_Comm_c2f(comm)  (MPI_Fint)(comm)
+#define PMPI_Comm_c2f(comm) (MPI_Fint)(comm)
+
+#define MPI_Comm_f2c(comm)  (MPI_Comm)(comm)
+#define PMPI_Comm_f2c(comm) (MPI_Comm)(comm)
+
+
+#define MPI_Type_f2c(datatype)  (MPI_Datatype)(datatype)
+#define PMPI_Type_f2c(datatype) (MPI_Datatype)(datatype)
+
+#define MPI_Type_c2f(datatype)  (MPI_Fint)(datatype)
+#define PMPI_Type_c2f(datatype) (MPI_Fint)(datatype)
+
+
+#define MPI_Group_f2c(group)  (MPI_Group)(group)
+#define PMPI_Group_f2c(group) (MPI_Group)(group)
+
+#define MPI_Group_c2f(group)  (MPI_Fint)(group)
+#define PMPI_Group_c2f(group) (MPI_Fint)(group)
+
+
+#define MPI_Request_f2c(request)  (MPI_Request)(request)
+#define PMPI_Request_f2c(request) (MPI_Request)(request)
+
+#define MPI_Request_c2f(request)  (MPI_Fint)(request)
+#define PMPI_Request_c2f(request) (MPI_Fint)(request)
+
+
+#define MPI_Win_f2c(win)  (MPI_Win)(win)
+#define PMPI_Win_f2c(win) (MPI_Win)(win)
+
+#define MPI_Win_c2f(win)  (MPI_Fint)(win)
+#define PMPI_Win_c2f(win) (MPI_Fint)(win)
+
+
+#define MPI_Op_c2f(op)  (MPI_Fint)(op)
+#define PMPI_Op_c2f(op) (MPI_Fint)(op)
+
+#define MPI_Op_f2c(op)  (MPI_Op)(op)
+#define PMPI_Op_f2c(op) (MPI_Op)(op)
+
+
+#define MPI_Info_c2f(info)  (MPI_Fint)(info)
+#define PMPI_Info_c2f(info) (MPI_Fint)(info)
+
+#define MPI_Info_f2c(info)  (MPI_Info)(info)
+#define PMPI_Info_f2c(info) (MPI_Info)(info)
+
+
+#define MPI_Errhandler_c2f(errhandler)  (MPI_Fint)(errhandler)
+#define PMPI_Errhandler_c2f(errhandler) (MPI_Fint)(errhandler)
+
+#define MPI_Errhandler_f2c(errhandler)  (MPI_Errhandler)(errhandler)
+#define PMPI_Errhandler_f2c(errhandler) (MPI_Errhandler)(errhandler)
+
+
+MPI_File
+MPIAPI
+MPI_File_f2c(
+    MPI_Fint file
+    );
+MPI_File
+MPIAPI
+PMPI_File_f2c(
+    MPI_Fint file
+    );
+
+MPI_Fint
+MPIAPI
+MPI_File_c2f(
+    MPI_File file
+    );
+MPI_Fint
+MPIAPI
+PMPI_File_c2f(
+    MPI_File file
+    );
+
+int
+MPIAPI
+MPI_Status_f2c(
+    _In_ MPI_Fint* f_status,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_Status_f2c(
+    _In_ MPI_Fint* f_status,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_Status_c2f(
+    _In_ MPI_Status* status,
+    _Out_ MPI_Fint* f_status
+    );
+int
+MPIAPI
+PMPI_Status_c2f(
+    _In_ MPI_Status* status,
+    _Out_ MPI_Fint* f_status
+    );
+
+
+#if !defined(_MPICH_DLL_)
+#define MPIU_DLL_SPEC __declspec(dllimport)
+#else
+#define MPIU_DLL_SPEC
+#endif
+
+extern MPIU_DLL_SPEC MPI_Fint* MPI_F_STATUS_IGNORE;
+extern MPIU_DLL_SPEC MPI_Fint* MPI_F_STATUSES_IGNORE;
+
+
+/*---------------------------------------------------------------------------*/
+/* Implementation Specific                                                   */
+/*---------------------------------------------------------------------------*/
+
+int
+MPIAPI
+MPIR_Dup_fn(
+    MPI_Comm oldcomm,
+    int keyval,
+    _In_opt_ void* extra_state,
+    _In_ void* attribute_val_in,
+    _Out_ void* attribute_val_out,
+    _Out_ int* flag
+    );
+
+
+#if MSMPI_VER >= 0x300
+
+int
+MPIAPI
+MSMPI_Get_bsend_overhead();
+
+#endif
+
+
+#if MSMPI_VER >= 0x300
+
+int
+MPIAPI
+MSMPI_Get_version();
+
+#else
+#  define MSMPI_Get_version() (MSMPI_VER)
+#endif
+
+typedef void
+(MPIAPI MSMPI_Request_callback)(
+    _In_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MSMPI_Request_set_apc(
+    MPI_Request request,
+    _In_ MSMPI_Request_callback* callback_fn,
+    _In_ MPI_Status* callback_status
+    );
+
+typedef struct _MSMPI_LOCK_QUEUE
+{
+    struct _MSMPI_LOCK_QUEUE* volatile next;
+    volatile MPI_Aint flags;
+
+} MSMPI_Lock_queue;
+
+void
+MPIAPI
+MSMPI_Queuelock_acquire(
+    _Out_ MSMPI_Lock_queue* queue
+    );
+
+void
+MPIAPI
+MSMPI_Queuelock_release(
+    _In_ MSMPI_Lock_queue* queue
+    );
+
+int
+MPIAPI
+MSMPI_Waitsome_interruptible(
+    int incount,
+    _Inout_count_(incount) MPI_Request array_of_requests[],
+    _Out_ int* outcount,
+    _Out_cap_post_count_(incount,*outcount) int array_of_indices[],
+    _Out_cap_post_count_(incount,*outcount) MPI_Status array_of_statuses[]
+    );
+
+
+/*---------------------------------------------------------------------------*/
+/* SAL ANNOTATIONS                                                           */
+/*---------------------------------------------------------------------------*/
+
+//OACR_WARNING_POP
+
+#ifdef MSMPI_DEFINED_SAL
+#undef MSMPI_DEFINED_SAL
+#undef _In_
+#undef _In_z_
+#undef _In_opt_
+#undef _In_count_
+#undef _In_bytecount_
+#undef _In_opt_count_
+#undef _Out_
+#undef _Out_cap_
+#undef _Out_cap_post_count_
+#undef _Out_bytecap_
+#undef _Out_z_cap_
+#undef _Out_z_cap_post_count_
+#undef _Out_cap_post_part_
+#undef _Out_opt_
+#undef _Out_opt_cap_
+#undef _Post_z_
+#undef _Inout_
+#undef _Inout_count_
+#endif
+
+#if defined(__cplusplus)
+}
+#endif
+
+#endif /* MPI_INCLUDED */
diff --git a/MachineLearning/cn/mpi/mpi.h b/MachineLearning/cn/mpi/mpi.h
new file mode 100644
index 000000000..bd61200e7
--- /dev/null
+++ b/MachineLearning/cn/mpi/mpi.h
@@ -0,0 +1,5937 @@
+/*
+ *  (C) 2001 by Argonne National Laboratory.
+ *  (C) 2009 by Microsoft Corporation.
+ *      See COPYRIGHT in the SDK directory.
+ */
+
+#ifndef MPI_INCLUDED
+#define MPI_INCLUDED
+
+#if defined(__cplusplus)
+extern "C" {
+#endif
+
+
+#ifndef MSMPI_VER
+#define MSMPI_VER 0x100
+#endif
+
+
+/*---------------------------------------------------------------------------*/
+/* SAL ANNOTATIONS                                                           */
+/*---------------------------------------------------------------------------*/
+/*
+ * Define SAL annotations if they aren't defined yet.  Note that if we define
+ * them, we undefine them at the end of this file so that future inclusion of
+ * sal.h doesn't cause errors.
+ */
+#ifndef _In_
+#define MSMPI_DEFINED_SAL
+#define _In_
+#define _In_z_
+#define _In_opt_
+#define _In_count_( x )
+#define _In_bytecount_( x )
+#define _In_opt_count_( x )
+#define _Out_
+#define _Out_cap_( x )
+#define _Out_cap_post_count_( x, y )
+#define _Out_bytecap_( x )
+#define _Out_z_cap_( x )
+#define _Out_z_cap_post_count_( x, y )
+#define _Out_cap_post_part_( x, y )
+#define _Out_opt_
+#define _Out_opt_cap_( x )
+#define _Post_z_
+#define _Inout_
+#define _Inout_count_( x )
+#endif
+
+/*---------------------------------------------------------------------------*/
+/* MSMPI Calling convention                                                  */
+/*---------------------------------------------------------------------------*/
+
+#define MPIAPI __stdcall
+
+
+/*---------------------------------------------------------------------------*/
+/* MPI ERROR CLASS                                                           */
+/*---------------------------------------------------------------------------*/
+
+#define MPI_SUCCESS          0      /* Successful return code */
+
+#define MPI_ERR_BUFFER       1      /* Invalid buffer pointer */
+#define MPI_ERR_COUNT        2      /* Invalid count argument */
+#define MPI_ERR_TYPE         3      /* Invalid datatype argument */
+#define MPI_ERR_TAG          4      /* Invalid tag argument */
+#define MPI_ERR_COMM         5      /* Invalid communicator */
+#define MPI_ERR_RANK         6      /* Invalid rank */
+#define MPI_ERR_ROOT         7      /* Invalid root */
+#define MPI_ERR_GROUP        8      /* Invalid group */
+#define MPI_ERR_OP           9      /* Invalid operation */
+#define MPI_ERR_TOPOLOGY    10      /* Invalid topology */
+#define MPI_ERR_DIMS        11      /* Invalid dimension argument */
+#define MPI_ERR_ARG         12      /* Invalid argument */
+#define MPI_ERR_UNKNOWN     13      /* Unknown error */
+#define MPI_ERR_TRUNCATE    14      /* Message truncated on receive */
+#define MPI_ERR_OTHER       15      /* Other error; use Error_string */
+#define MPI_ERR_INTERN      16      /* Internal error code */
+#define MPI_ERR_IN_STATUS   17      /* Error code is in status */
+#define MPI_ERR_PENDING     18      /* Pending request */
+#define MPI_ERR_REQUEST     19      /* Invalid request (handle) */
+#define MPI_ERR_ACCESS      20      /* Premission denied */
+#define MPI_ERR_AMODE       21      /* Error related to amode passed to MPI_File_open */
+#define MPI_ERR_BAD_FILE    22      /* Invalid file name (e.g., path name too long) */
+#define MPI_ERR_CONVERSION  23      /* Error in user data conversion function */
+#define MPI_ERR_DUP_DATAREP 24      /* Data representation identifier already registered */
+#define MPI_ERR_FILE_EXISTS 25      /* File exists */
+#define MPI_ERR_FILE_IN_USE 26      /* File operation could not be completed, file in use */
+#define MPI_ERR_FILE        27      /* Invalid file handle */
+#define MPI_ERR_INFO        28      /* Invalid info argument */
+#define MPI_ERR_INFO_KEY    29      /* Key longer than MPI_MAX_INFO_KEY */
+#define MPI_ERR_INFO_VALUE  30      /* Value longer than MPI_MAX_INFO_VAL */
+#define MPI_ERR_INFO_NOKEY  31      /* Invalid key passed to MPI_Info_delete */
+#define MPI_ERR_IO          32      /* Other I/O error */
+#define MPI_ERR_NAME        33      /* Invalid service name in MPI_Lookup_name */
+#define MPI_ERR_NO_MEM      34      /* Alloc_mem could not allocate memory */
+#define MPI_ERR_NOT_SAME    35      /* Collective argument/sequence not the same on all processes */
+#define MPI_ERR_NO_SPACE    36      /* Not enough space */
+#define MPI_ERR_NO_SUCH_FILE 37     /* File does not exist */
+#define MPI_ERR_PORT        38      /* Invalid port name in MPI_comm_connect*/
+#define MPI_ERR_QUOTA       39      /* Quota exceeded */
+#define MPI_ERR_READ_ONLY   40      /* Read-only file or file system */
+#define MPI_ERR_SERVICE     41      /* Invalid service name in MPI_Unpublish_name */
+#define MPI_ERR_SPAWN       42      /* Error in spawning processes */
+#define MPI_ERR_UNSUPPORTED_DATAREP   43  /* Unsupported dararep in MPI_File_set_view */
+#define MPI_ERR_UNSUPPORTED_OPERATION 44  /* Unsupported operation on file */
+#define MPI_ERR_WIN         45      /* Invalid win argument */
+#define MPI_ERR_BASE        46      /* Invalid base passed to MPI_Free_mem */
+#define MPI_ERR_LOCKTYPE    47      /* Invalid locktype argument */
+#define MPI_ERR_KEYVAL      48      /* Invalid keyval  */
+#define MPI_ERR_RMA_CONFLICT 49     /* Conflicting accesses to window */
+#define MPI_ERR_RMA_SYNC    50      /* Wrong synchronization of RMA calls */
+#define MPI_ERR_SIZE        51      /* Invalid size argument */
+#define MPI_ERR_DISP        52      /* Invalid disp argument */
+#define MPI_ERR_ASSERT      53      /* Invalid assert argument */
+
+#define MPI_ERR_LASTCODE    0x3fffffff    /* Last valid error code for a predefined error class */
+
+#define MPICH_ERR_LAST_CLASS 53
+
+
+/*---------------------------------------------------------------------------*/
+/* MPI Basic integer types                                                   */
+/*---------------------------------------------------------------------------*/
+
+/* Address size integer */
+#ifdef _WIN64
+typedef __int64 MPI_Aint;
+#else
+typedef int MPI_Aint;
+#endif
+
+/* Fortran INTEGER */
+typedef int MPI_Fint;
+
+/* File offset */
+typedef __int64 MPI_Offset;
+
+
+/*---------------------------------------------------------------------------*/
+/* MPI_Datatype                                                              */
+/*---------------------------------------------------------------------------*/
+
+typedef int MPI_Datatype;
+#define MPI_DATATYPE_NULL           ((MPI_Datatype)0x0c000000)
+
+#define MPI_CHAR                    ((MPI_Datatype)0x4c000101)
+#define MPI_UNSIGNED_CHAR           ((MPI_Datatype)0x4c000102)
+#define MPI_SHORT                   ((MPI_Datatype)0x4c000203)
+#define MPI_UNSIGNED_SHORT          ((MPI_Datatype)0x4c000204)
+#define MPI_INT                     ((MPI_Datatype)0x4c000405)
+#define MPI_UNSIGNED                ((MPI_Datatype)0x4c000406)
+#define MPI_LONG                    ((MPI_Datatype)0x4c000407)
+#define MPI_UNSIGNED_LONG           ((MPI_Datatype)0x4c000408)
+#define MPI_LONG_LONG_INT           ((MPI_Datatype)0x4c000809)
+#define MPI_LONG_LONG               MPI_LONG_LONG_INT
+#define MPI_FLOAT                   ((MPI_Datatype)0x4c00040a)
+#define MPI_DOUBLE                  ((MPI_Datatype)0x4c00080b)
+#define MPI_LONG_DOUBLE             ((MPI_Datatype)0x4c00080c)
+#define MPI_BYTE                    ((MPI_Datatype)0x4c00010d)
+#define MPI_WCHAR                   ((MPI_Datatype)0x4c00020e)
+
+#define MPI_PACKED                  ((MPI_Datatype)0x4c00010f)
+#define MPI_LB                      ((MPI_Datatype)0x4c000010)
+#define MPI_UB                      ((MPI_Datatype)0x4c000011)
+
+#define MPI_C_COMPLEX               ((MPI_Datatype)0x4c000812)
+#define MPI_C_FLOAT_COMPLEX         ((MPI_Datatype)0x4c000813)
+#define MPI_C_DOUBLE_COMPLEX        ((MPI_Datatype)0x4c001614)
+#define MPI_C_LONG_DOUBLE_COMPLEX   ((MPI_Datatype)0x4c001615)
+
+#define MPI_2INT                    ((MPI_Datatype)0x4c000816)
+#define MPI_C_BOOL                  ((MPI_Datatype)0x4c000117)
+#define MPI_SIGNED_CHAR             ((MPI_Datatype)0x4c000118)
+#define MPI_UNSIGNED_LONG_LONG      ((MPI_Datatype)0x4c000819)
+
+/* Fortran types */
+#define MPI_CHARACTER               ((MPI_Datatype)0x4c00011a)
+#define MPI_INTEGER                 ((MPI_Datatype)0x4c00041b)
+#define MPI_REAL                    ((MPI_Datatype)0x4c00041c)
+#define MPI_LOGICAL                 ((MPI_Datatype)0x4c00041d)
+#define MPI_COMPLEX                 ((MPI_Datatype)0x4c00081e)
+#define MPI_DOUBLE_PRECISION        ((MPI_Datatype)0x4c00081f)
+#define MPI_2INTEGER                ((MPI_Datatype)0x4c000820)
+#define MPI_2REAL                   ((MPI_Datatype)0x4c000821)
+#define MPI_DOUBLE_COMPLEX          ((MPI_Datatype)0x4c001022)
+#define MPI_2DOUBLE_PRECISION       ((MPI_Datatype)0x4c001023)
+#define MPI_2COMPLEX                ((MPI_Datatype)0x4c001024)
+#define MPI_2DOUBLE_COMPLEX         ((MPI_Datatype)0x4c002025)
+
+/* Size-specific types (see MPI 2.2, 16.2.5) */
+#define MPI_REAL2                   MPI_DATATYPE_NULL
+#define MPI_REAL4                   ((MPI_Datatype)0x4c000427)
+#define MPI_COMPLEX8                ((MPI_Datatype)0x4c000828)
+#define MPI_REAL8                   ((MPI_Datatype)0x4c000829)
+#define MPI_COMPLEX16               ((MPI_Datatype)0x4c00102a)
+#define MPI_REAL16                  MPI_DATATYPE_NULL
+#define MPI_COMPLEX32               MPI_DATATYPE_NULL
+#define MPI_INTEGER1                ((MPI_Datatype)0x4c00012d)
+#define MPI_COMPLEX4                MPI_DATATYPE_NULL
+#define MPI_INTEGER2                ((MPI_Datatype)0x4c00022f)
+#define MPI_INTEGER4                ((MPI_Datatype)0x4c000430)
+#define MPI_INTEGER8                ((MPI_Datatype)0x4c000831)
+#define MPI_INTEGER16               MPI_DATATYPE_NULL
+#define MPI_INT8_T                  ((MPI_Datatype)0x4c000133)
+#define MPI_INT16_T                 ((MPI_Datatype)0x4c000234)
+#define MPI_INT32_T                 ((MPI_Datatype)0x4c000435)
+#define MPI_INT64_T                 ((MPI_Datatype)0x4c000836)
+#define MPI_UINT8_T                 ((MPI_Datatype)0x4c000137)
+#define MPI_UINT16_T                ((MPI_Datatype)0x4c000238)
+#define MPI_UINT32_T                ((MPI_Datatype)0x4c000439)
+#define MPI_UINT64_T                ((MPI_Datatype)0x4c00083a)
+
+#ifdef _WIN64
+#define MPI_AINT                    ((MPI_Datatype)0x4c00083b)
+#else
+#define MPI_AINT                    ((MPI_Datatype)0x4c00043b)
+#endif
+#define MPI_OFFSET                  ((MPI_Datatype)0x4c00083c)
+
+/*
+ * The layouts for the types MPI_DOUBLE_INT etc. are
+ *
+ *      struct { double a; int b; }
+ */
+#define MPI_FLOAT_INT               ((MPI_Datatype)0x8c000000)
+#define MPI_DOUBLE_INT              ((MPI_Datatype)0x8c000001)
+#define MPI_LONG_INT                ((MPI_Datatype)0x8c000002)
+#define MPI_SHORT_INT               ((MPI_Datatype)0x8c000003)
+#define MPI_LONG_DOUBLE_INT         ((MPI_Datatype)0x8c000004)
+
+
+/*---------------------------------------------------------------------------*/
+/* MPI_Comm                                                                  */
+/*---------------------------------------------------------------------------*/
+
+typedef int MPI_Comm;
+#define MPI_COMM_NULL  ((MPI_Comm)0x04000000)
+
+#define MPI_COMM_WORLD ((MPI_Comm)0x44000000)
+#define MPI_COMM_SELF  ((MPI_Comm)0x44000001)
+
+
+/*---------------------------------------------------------------------------*/
+/* MPI_Win                                                                   */
+/*---------------------------------------------------------------------------*/
+
+typedef int MPI_Win;
+#define MPI_WIN_NULL ((MPI_Win)0x20000000)
+
+
+/*---------------------------------------------------------------------------*/
+/* MPI_File                                                                  */
+/*---------------------------------------------------------------------------*/
+
+typedef struct ADIOI_FileD* MPI_File;
+#define MPI_FILE_NULL ((MPI_File)0)
+
+
+/*---------------------------------------------------------------------------*/
+/* MPI_Op                                                                    */
+/*---------------------------------------------------------------------------*/
+
+typedef int MPI_Op;
+#define MPI_OP_NULL ((MPI_Op)0x18000000)
+
+#define MPI_MAX     ((MPI_Op)0x58000001)
+#define MPI_MIN     ((MPI_Op)0x58000002)
+#define MPI_SUM     ((MPI_Op)0x58000003)
+#define MPI_PROD    ((MPI_Op)0x58000004)
+#define MPI_LAND    ((MPI_Op)0x58000005)
+#define MPI_BAND    ((MPI_Op)0x58000006)
+#define MPI_LOR     ((MPI_Op)0x58000007)
+#define MPI_BOR     ((MPI_Op)0x58000008)
+#define MPI_LXOR    ((MPI_Op)0x58000009)
+#define MPI_BXOR    ((MPI_Op)0x5800000a)
+#define MPI_MINLOC  ((MPI_Op)0x5800000b)
+#define MPI_MAXLOC  ((MPI_Op)0x5800000c)
+#define MPI_REPLACE ((MPI_Op)0x5800000d)
+
+
+/*---------------------------------------------------------------------------*/
+/* MPI_Info                                                                  */
+/*---------------------------------------------------------------------------*/
+
+typedef int MPI_Info;
+#define MPI_INFO_NULL         ((MPI_Info)0x1c000000)
+
+
+/*---------------------------------------------------------------------------*/
+/* MPI_Request                                                               */
+/*---------------------------------------------------------------------------*/
+
+typedef int MPI_Request;
+#define MPI_REQUEST_NULL ((MPI_Request)0x2c000000)
+
+
+/*---------------------------------------------------------------------------*/
+/* MPI_Group                                                                 */
+/*---------------------------------------------------------------------------*/
+
+typedef int MPI_Group;
+#define MPI_GROUP_NULL  ((MPI_Group)0x08000000)
+
+#define MPI_GROUP_EMPTY ((MPI_Group)0x48000000)
+
+
+/*---------------------------------------------------------------------------*/
+/* MPI_Errhandler                                                            */
+/*---------------------------------------------------------------------------*/
+
+typedef int MPI_Errhandler;
+#define MPI_ERRHANDLER_NULL  ((MPI_Errhandler)0x14000000)
+
+#define MPI_ERRORS_ARE_FATAL ((MPI_Errhandler)0x54000000)
+#define MPI_ERRORS_RETURN    ((MPI_Errhandler)0x54000001)
+
+/*---------------------------------------------------------------------------*/
+/* MPI_Status                                                                */
+/*---------------------------------------------------------------------------*/
+
+typedef struct MPI_Status
+{
+    int count;
+    int cancelled;
+    int MPI_SOURCE;
+    int MPI_TAG;
+    int MPI_ERROR;
+
+} MPI_Status;
+
+#define MPI_STATUS_IGNORE ((MPI_Status*)(MPI_Aint)1)
+#define MPI_STATUSES_IGNORE ((MPI_Status*)(MPI_Aint)1)
+
+
+/*---------------------------------------------------------------------------*/
+/* MISC CONSTANTS                                                            */
+/*---------------------------------------------------------------------------*/
+
+/* Used in: Count, Index, Rank, Color, Toplogy, Precision, Exponent range  */
+#define MPI_UNDEFINED   (-32766)
+
+/* Used in: Rank */
+#define MPI_PROC_NULL   (-1)
+#define MPI_ANY_SOURCE  (-2)
+#define MPI_ROOT        (-3)
+
+/* Used in: Tag */
+#define MPI_ANY_TAG     (-1)
+
+/* Used for: Buffer address */
+#define MPI_BOTTOM      ((void*)0)
+
+
+/*---------------------------------------------------------------------------*/
+/* Chapter 3: Point-to-Point Communication                                   */
+/*---------------------------------------------------------------------------*/
+
+/*---------------------------------------------*/
+/* Section 3.2: Blocking Communication         */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Send(
+    _In_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Send(
+    _In_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm
+    );
+
+int
+MPIAPI
+MPI_Recv(
+    _Out_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int source,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_Recv(
+    _Out_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int source,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_Get_count(
+    _In_ MPI_Status* status,
+    MPI_Datatype datatype,
+    _Out_ int* count
+    );
+int
+MPIAPI
+PMPI_Get_count(
+    _In_ MPI_Status* status,
+    MPI_Datatype datatype,
+    _Out_ int* count
+    );
+
+
+/*---------------------------------------------*/
+/* Section 3.4: Communication Modes            */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Bsend(
+    _In_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Bsend(
+    _In_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm
+    );
+
+int
+MPIAPI
+MPI_Ssend(
+    _In_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Ssend(
+    _In_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm
+    );
+
+int
+MPIAPI
+MPI_Rsend(
+    _In_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Rsend(
+    _In_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm
+    );
+
+
+/*---------------------------------------------*/
+/* Section 3.6: Buffer Allocation              */
+/*---------------------------------------------*/
+
+/* Upper bound on bsend overhead for each message */
+#define MSMPI_BSEND_OVERHEAD_V1   95
+#define MSMPI_BSEND_OVERHEAD_V2   MSMPI_BSEND_OVERHEAD_V1
+
+#if MSMPI_VER > 0x300
+#  define MPI_BSEND_OVERHEAD  MSMPI_Get_bsend_overhead()
+#else
+#  define MPI_BSEND_OVERHEAD  MSMPI_BSEND_OVERHEAD_V1
+#endif
+
+int
+MPIAPI
+MPI_Buffer_attach(
+    _In_ void* buffer,
+    int size
+    );
+int
+MPIAPI
+PMPI_Buffer_attach(
+    _In_ void* buffer,
+    int size
+    );
+
+int
+MPIAPI
+MPI_Buffer_detach(
+    _Out_ void* buffer_addr,
+    _Out_ int* size
+    );
+int
+MPIAPI
+PMPI_Buffer_detach(
+    _Out_ void* buffer_addr,
+    _Out_ int* size
+    );
+
+
+/*---------------------------------------------*/
+/* Section 3.7: Nonblocking Communication      */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Isend(
+    _In_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_Isend(
+    _In_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+
+int
+MPIAPI
+MPI_Ibsend(
+    _In_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_Ibsend(
+    _In_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+
+int
+MPIAPI
+MPI_Issend(
+    _In_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_Issend(
+    _In_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+
+int
+MPIAPI
+MPI_Irsend(
+    _In_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_Irsend(
+    _In_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+
+int
+MPIAPI
+MPI_Irecv(
+    _Out_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int source,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_Irecv(
+    _Out_opt_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int source,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+
+
+/*---------------------------------------------*/
+/* Section 3.7.3: Communication Completion     */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Wait(
+    _Inout_ MPI_Request* request,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_Wait(
+    _Inout_ MPI_Request* request,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_Test(
+    _Inout_ MPI_Request* request,
+    _Out_ int* flag,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_Test(
+    _Inout_ MPI_Request* request,
+    _Out_ int* flag,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_Request_free(
+    _Inout_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_Request_free(
+    _Inout_ MPI_Request* request
+    );
+
+
+/*---------------------------------------------*/
+/* Section 3.7.5: Multiple Completions         */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Waitany(
+    int count,
+    _Inout_count_(count) MPI_Request* array_of_requests,
+    _Out_ int* index,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_Waitany(
+    int count,
+    _Inout_count_(count) MPI_Request* array_of_requests,
+    _Out_ int* index,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_Testany(
+    int count,
+    _Inout_count_(count) MPI_Request* array_of_requests,
+    _Out_ int* index,
+    _Out_ int* flag,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_Testany(
+    int count,
+    _Inout_count_(count) MPI_Request* array_of_requests,
+    _Out_ int* index,
+    _Out_ int* flag,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_Waitall(
+    int count,
+    _Inout_count_(count) MPI_Request* array_of_requests,
+    _Out_cap_(count) MPI_Status* array_of_statuses
+    );
+int
+MPIAPI
+PMPI_Waitall(
+    int count,
+    _Inout_count_(count) MPI_Request* array_of_requests,
+    _Out_cap_(count) MPI_Status* array_of_statuses
+    );
+
+int
+MPIAPI
+MPI_Testall(
+    int count,
+    _Inout_count_(count) MPI_Request* array_of_requests,
+    _Out_ int* flag,
+    _Out_cap_(count) MPI_Status* array_of_statuses
+    );
+int
+MPIAPI
+PMPI_Testall(
+    int count,
+    _Inout_count_(count) MPI_Request* array_of_requests,
+    _Out_ int* flag,
+    _Out_cap_(count) MPI_Status* array_of_statuses
+    );
+
+int
+MPIAPI
+MPI_Waitsome(
+    int incount,
+    _Inout_count_(incount) MPI_Request* array_of_requests,
+    _Out_ int* outcount,
+    _Out_cap_post_count_(incount,*outcount) int* array_of_indices,
+    _Out_cap_post_count_(incount,*outcount) MPI_Status* array_of_statuses
+    );
+int
+MPIAPI
+PMPI_Waitsome(
+    int incount,
+    _Inout_count_(incount) MPI_Request* array_of_requests,
+    _Out_ int* outcount,
+    _Out_cap_post_count_(incount,*outcount) int* array_of_indices,
+    _Out_cap_post_count_(incount,*outcount) MPI_Status* array_of_statuses
+    );
+
+int
+MPIAPI
+MPI_Testsome(
+    int incount,
+    _Inout_count_(incount) MPI_Request* array_of_requests,
+    _Out_ int* outcount,
+    _Out_cap_post_count_(incount,*outcount) int* array_of_indices,
+    _Out_cap_post_count_(incount,*outcount) MPI_Status* array_of_statuses
+    );
+int
+MPIAPI
+PMPI_Testsome(
+    int incount,
+    _Inout_count_(incount) MPI_Request* array_of_requests,
+    _Out_ int* outcount,
+    _Out_cap_post_count_(incount,*outcount) int* array_of_indices,
+    _Out_cap_post_count_(incount,*outcount) MPI_Status* array_of_statuses
+    );
+
+
+/*---------------------------------------------*/
+/* Section 3.7.6: Test of status               */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Request_get_status(
+    MPI_Request request,
+    _Out_ int* flag,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_Request_get_status(
+    MPI_Request request,
+    _Out_ int* flag,
+    _Out_ MPI_Status* status
+    );
+
+
+/*---------------------------------------------*/
+/* Section 3.8: Probe and Cancel               */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Iprobe(
+    int source,
+    int tag,
+    MPI_Comm comm,
+    _Out_ int* flag,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_Iprobe(
+    int source,
+    int tag,
+    MPI_Comm comm,
+    _Out_ int* flag,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_Probe(
+    int source,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_Probe(
+    int source,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_Cancel(
+    _In_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_Cancel(
+    _In_ MPI_Request* request
+    );
+
+int
+MPIAPI
+MPI_Test_cancelled(
+    _In_ MPI_Status* status,
+    _Out_ int* flag
+    );
+int
+MPIAPI
+PMPI_Test_cancelled(
+    _In_ MPI_Status* request,
+    _Out_ int* flag
+    );
+
+
+/*---------------------------------------------*/
+/* Section 3.9: Persistent Communication       */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Send_init(
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_Send_init(
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+
+int
+MPIAPI
+MPI_Bsend_init(
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_Bsend_init(
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+
+int
+MPIAPI
+MPI_Ssend_init(
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_Ssend_init(
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+
+int
+MPIAPI
+MPI_Rsend_init(
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_Rsend_init(
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+
+int
+MPIAPI
+MPI_Recv_init(
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int source,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_Recv_init(
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int source,
+    int tag,
+    MPI_Comm comm,
+    _Out_ MPI_Request* request
+    );
+
+int
+MPIAPI
+MPI_Start(
+    _Inout_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_Start(
+    _Inout_ MPI_Request* request
+    );
+
+int
+MPIAPI
+MPI_Startall(
+    int count,
+    _Inout_count_(count) MPI_Request* array_of_requests
+    );
+int
+MPIAPI
+PMPI_Startall(
+    int count,
+    _Inout_count_(count) MPI_Request* array_of_requests
+    );
+
+
+/*---------------------------------------------*/
+/* Section 3.10: Send-Recv                     */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Sendrecv(
+    _In_ void* sendbuf,
+    int sendcount,
+    MPI_Datatype sendtype,
+    int dest,
+    int sendtag,
+    _Out_ void* recvbuf,
+    int recvcount,
+    MPI_Datatype recvtype,
+    int source,
+    int recvtag,
+    MPI_Comm comm,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_Sendrecv(
+    _In_ void* sendbuf,
+    int sendcount,
+    MPI_Datatype sendtype,
+    int dest,
+    int sendtag,
+    _Out_ void* recvbuf,
+    int recvcount,
+    MPI_Datatype recvtype,
+    int source,
+    int recvtag,
+    MPI_Comm comm,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_Sendrecv_replace(
+    _Inout_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int sendtag,
+    int source,
+    int recvtag,
+    MPI_Comm comm,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_Sendrecv_replace(
+    _Inout_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    int dest,
+    int sendtag,
+    int source,
+    int recvtag,
+    MPI_Comm comm,
+    _Out_ MPI_Status* status
+    );
+
+
+/*---------------------------------------------------------------------------*/
+/* Chapter 4: Datatypes                                                      */
+/*---------------------------------------------------------------------------*/
+
+/*---------------------------------------------*/
+/* Section 4.1: Derived Datatypes              */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Type_contiguous(
+    int count,
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+int
+MPIAPI
+PMPI_Type_contiguous(
+    int count,
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+
+int
+MPIAPI
+MPI_Type_vector(
+    int count,
+    int blocklength,
+    int stride,
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+int
+MPIAPI
+PMPI_Type_vector(
+    int count,
+    int blocklength,
+    int stride,
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+
+int
+MPIAPI
+MPI_Type_create_hvector(
+    int count,
+    int blocklength,
+    MPI_Aint stride,
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+int
+MPIAPI
+PMPI_Type_create_hvector(
+    int count,
+    int blocklength,
+    MPI_Aint stride,
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+
+int
+MPIAPI
+MPI_Type_indexed(
+    int count,
+    _In_count_(count) int* array_of_blocklengths,
+    _In_count_(count) int* array_of_displacements,
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+int
+MPIAPI
+PMPI_Type_indexed(
+    int count,
+    _In_count_(count) int* array_of_blocklengths,
+    _In_count_(count) int* array_of_displacements,
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+
+int
+MPIAPI
+MPI_Type_create_hindexed(
+    int count,
+    _In_count_(count) int array_of_blocklengths[],
+    _In_count_(count) MPI_Aint array_of_displacements[],
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+int
+MPIAPI
+PMPI_Type_create_hindexed(
+    int count,
+    _In_count_(count) int array_of_blocklengths[],
+    _In_opt_count_(count) MPI_Aint array_of_displacements[],
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+
+int
+MPIAPI
+MPI_Type_create_indexed_block(
+    int count,
+    int blocklength,
+    _In_count_(count) int array_of_displacements[],
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+int
+MPIAPI
+PMPI_Type_create_indexed_block(
+    int count,
+    int blocklength,
+    _In_count_(count) int array_of_displacements[],
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+
+int
+MPIAPI
+MPI_Type_create_struct(
+    int count,
+    _In_count_(count) int array_of_blocklengths[],
+    _In_count_(count) MPI_Aint array_of_displacements[],
+    _In_count_(count) MPI_Datatype array_of_types[],
+    _Out_ MPI_Datatype* newtype
+    );
+int
+MPIAPI
+PMPI_Type_create_struct(
+    int count,
+    _In_count_(count) int array_of_blocklengths[],
+    _In_opt_count_(count) MPI_Aint array_of_displacements[],
+    _In_count_(count) MPI_Datatype array_of_types[],
+    _Out_ MPI_Datatype* newtype
+    );
+
+
+#define MPI_ORDER_C         56
+#define MPI_ORDER_FORTRAN   57
+
+int
+MPIAPI
+MPI_Type_create_subarray(
+    int ndims,
+    _In_count_(ndims) int array_of_sizes[],
+    _In_count_(ndims) int array_of_subsizes[],
+    _In_count_(ndims) int array_of_starts[],
+    int order,
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+int
+MPIAPI
+PMPI_Type_create_subarray(
+    int ndims,
+    _In_count_(ndims) int array_of_sizes[],
+    _In_count_(ndims) int array_of_subsizes[],
+    _In_count_(ndims) int array_of_starts[],
+    int order,
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+
+
+#define MPI_DISTRIBUTE_BLOCK         121
+#define MPI_DISTRIBUTE_CYCLIC        122
+#define MPI_DISTRIBUTE_NONE          123
+#define MPI_DISTRIBUTE_DFLT_DARG (-49767)
+
+int
+MPIAPI
+MPI_Type_create_darray(
+    int size,
+    int rank,
+    int ndims,
+    _In_count_(ndims) int array_of_gszies[],
+    _In_count_(ndims) int array_of_distribs[],
+    _In_count_(ndims) int array_of_dargs[],
+    _In_count_(ndims) int array_of_psizes[],
+    int order,
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+int
+MPIAPI
+PMPI_Type_create_darray(
+    int size,
+    int rank,
+    int ndims,
+    _In_count_(ndims) int array_of_gszies[],
+    _In_count_(ndims) int array_of_distribs[],
+    _In_count_(ndims) int array_of_dargs[],
+    _In_count_(ndims) int array_of_psizes[],
+    int order,
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+
+
+/*---------------------------------------------*/
+/* Section 4.1.5: Datatype Address and Size    */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Get_address(
+    _In_ void* location,
+    _Out_ MPI_Aint* address
+    );
+int
+MPIAPI
+PMPI_Get_address(
+    _In_ void* location,
+    _Out_ MPI_Aint* address
+    );
+
+int
+MPIAPI
+MPI_Type_size(
+    MPI_Datatype datatype,
+    _Out_ int* size
+    );
+int
+MPIAPI
+PMPI_Type_size(
+    MPI_Datatype datatype,
+    _Out_ int* size
+    );
+
+
+/*---------------------------------------------*/
+/* Section 4.1.7: Datatype Extent and Bounds   */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Type_get_extent(
+    MPI_Datatype datatype,
+    _Out_ MPI_Aint* lb,
+    _Out_ MPI_Aint* extent
+    );
+int
+MPIAPI
+PMPI_Type_get_extent(
+    MPI_Datatype datatype,
+    _Out_ MPI_Aint* lb,
+    _Out_ MPI_Aint* extent
+    );
+
+int
+MPIAPI
+MPI_Type_create_resized(
+    MPI_Datatype oldtype,
+    MPI_Aint lb,
+    MPI_Aint extent,
+    _Out_ MPI_Datatype* newtype
+    );
+int
+MPIAPI
+PMPI_Type_create_resized(
+    MPI_Datatype oldtype,
+    MPI_Aint lb,
+    MPI_Aint extent,
+    _Out_ MPI_Datatype* newtype
+    );
+
+
+/*---------------------------------------------*/
+/* Section 4.1.8: Datatype True Extent         */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Type_get_true_extent(
+    MPI_Datatype datatype,
+    _Out_ MPI_Aint* true_lb,
+    _Out_ MPI_Aint* true_extent
+    );
+int
+MPIAPI
+PMPI_Type_get_true_extent(
+    MPI_Datatype datatype,
+    _Out_ MPI_Aint* true_lb,
+    _Out_ MPI_Aint* true_extent
+    );
+
+
+/*---------------------------------------------*/
+/* Section 4.1.9: Datatype Commit and Free     */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Type_commit(
+    _In_ MPI_Datatype* datatype
+    );
+int
+MPIAPI
+PMPI_Type_commit(
+    _In_ MPI_Datatype* datatype
+    );
+
+int
+MPIAPI
+MPI_Type_free(
+    _Inout_ MPI_Datatype* datatype
+    );
+int
+MPIAPI
+PMPI_Type_free(
+    _Inout_ MPI_Datatype* datatype
+    );
+
+
+/*---------------------------------------------*/
+/* Section 4.1.10: Datatype Duplication        */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Type_dup(
+    MPI_Datatype type,
+    _Out_ MPI_Datatype* newtype
+    );
+int
+MPIAPI
+PMPI_Type_dup(
+    MPI_Datatype type,
+    _Out_ MPI_Datatype* newtype
+    );
+
+
+/*---------------------------------------------*/
+/* Section 4.1.11: Datatype and Communication  */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Get_elements(
+    _In_ MPI_Status* status,
+    MPI_Datatype datatype,
+    _Out_ int* count
+    );
+int
+MPIAPI
+PMPI_Get_elements(
+    _In_ MPI_Status* status,
+    MPI_Datatype datatype,
+    _Out_ int* count
+    );
+
+
+/*---------------------------------------------*/
+/* Section 4.1.13: Decoding a Datatype         */
+/*---------------------------------------------*/
+
+/* Datatype combiners result */
+enum
+{
+    MPI_COMBINER_NAMED            = 1,
+    MPI_COMBINER_DUP              = 2,
+    MPI_COMBINER_CONTIGUOUS       = 3,
+    MPI_COMBINER_VECTOR           = 4,
+    MPI_COMBINER_HVECTOR_INTEGER  = 5,
+    MPI_COMBINER_HVECTOR          = 6,
+    MPI_COMBINER_INDEXED          = 7,
+    MPI_COMBINER_HINDEXED_INTEGER = 8,
+    MPI_COMBINER_HINDEXED         = 9,
+    MPI_COMBINER_INDEXED_BLOCK    = 10,
+    MPI_COMBINER_STRUCT_INTEGER   = 11,
+    MPI_COMBINER_STRUCT           = 12,
+    MPI_COMBINER_SUBARRAY         = 13,
+    MPI_COMBINER_DARRAY           = 14,
+    MPI_COMBINER_F90_REAL         = 15,
+    MPI_COMBINER_F90_COMPLEX      = 16,
+    MPI_COMBINER_F90_INTEGER      = 17,
+    MPI_COMBINER_RESIZED          = 18
+};
+
+int
+MPIAPI
+MPI_Type_get_envelope(
+    MPI_Datatype datatype,
+    _Out_ int* num_integers,
+    _Out_ int* num_addresses,
+    _Out_ int* num_datatypes,
+    _Out_ int* combiner
+    );
+int
+MPIAPI
+PMPI_Type_get_envelope(
+    MPI_Datatype datatype,
+    _Out_ int* num_integers,
+    _Out_ int* num_addresses,
+    _Out_ int* num_datatypes,
+    _Out_ int* combiner
+    );
+
+int
+MPIAPI
+MPI_Type_get_contents(
+    MPI_Datatype datatype,
+    int max_integers,
+    int max_addresses,
+    int max_datatypes,
+    _Out_cap_(max_integers) int array_of_integers[],
+    _Out_cap_(max_addresses) MPI_Aint array_of_addresses[],
+    _Out_cap_(max_datatypes) MPI_Datatype array_of_datatypes[]
+    );
+int
+MPIAPI
+PMPI_Type_get_contents(
+    MPI_Datatype datatype,
+    int max_integers,
+    int max_addresses,
+    int max_datatypes,
+    _Out_cap_(max_integers) int array_of_integers[],
+    _Out_cap_(max_addresses) MPI_Aint array_of_addresses[],
+    _Out_cap_(max_datatypes) MPI_Datatype array_of_datatypes[]
+    );
+
+
+/*---------------------------------------------*/
+/* Section 4.2: Datatype Pack and Unpack       */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Pack(
+    _In_ void* inbuf,
+    int incount,
+    MPI_Datatype datatype,
+    _Out_bytecap_(outsize) void* outbuf,
+    int outsize,
+    _Inout_ int* position,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Pack(
+    _In_ void* inbuf,
+    int incount,
+    MPI_Datatype datatype,
+    _Out_bytecap_(outsize) void* outbuf,
+    int outsize,
+    _Inout_ int* position,
+    MPI_Comm comm
+    );
+
+int
+MPIAPI
+MPI_Unpack(
+    _In_bytecount_(insize) void* inbuf,
+    int insize,
+    _Inout_ int* position,
+    _Out_ void* outbuf,
+    int outcount,
+    MPI_Datatype datatype,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Unpack(
+    _In_bytecount_(insize) void* inbuf,
+    int insize,
+    _Inout_ int* position,
+    _Out_ void* outbuf,
+    int outcount,
+    MPI_Datatype datatype,
+    MPI_Comm comm
+    );
+
+int
+MPIAPI
+MPI_Pack_size(
+    int incount,
+    MPI_Datatype datatype,
+    MPI_Comm comm,
+    _Out_ int* size
+    );
+int
+MPIAPI
+PMPI_Pack_size(
+    int incount,
+    MPI_Datatype datatype,
+    MPI_Comm comm,
+    _Out_ int* size
+    );
+
+
+/*---------------------------------------------*/
+/* Section 4.3: Canonical Pack and Unpack      */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Pack_external(
+    _In_z_ char* datarep,
+    _In_ void* inbuf,
+    int incount,
+    MPI_Datatype datatype,
+    _Out_bytecap_(outsize) void* outbuf,
+    MPI_Aint outsize,
+    _Inout_ MPI_Aint* position
+    );
+int
+MPIAPI
+PMPI_Pack_external(
+    _In_z_ char* datarep,
+    _In_ void* inbuf,
+    int incount,
+    MPI_Datatype datatype,
+    _Out_bytecap_(outsize) void* outbuf,
+    MPI_Aint outsize,
+    _Inout_ MPI_Aint* position
+    );
+
+int
+MPIAPI
+MPI_Unpack_external(
+    _In_z_ char* datarep,
+    _In_bytecount_(insize) void* inbuf,
+    MPI_Aint insize,
+    _Inout_ MPI_Aint* position,
+    _Out_ void* outbuf,
+    int outcount,
+    MPI_Datatype datatype
+    );
+int
+MPIAPI
+PMPI_Unpack_external(
+    _In_z_ char* datarep,
+    _In_bytecount_(insize) void* inbuf,
+    MPI_Aint insize,
+    _Inout_ MPI_Aint* position,
+    _Out_ void* outbuf,
+    int outcount,
+    MPI_Datatype datatype
+    );
+
+int
+MPIAPI
+MPI_Pack_external_size(
+    _In_z_ char* datarep,
+    int incount,
+    MPI_Datatype datatype,
+    _Out_ MPI_Aint* size
+    );
+int
+MPIAPI
+PMPI_Pack_external_size(
+    _In_z_ char* datarep,
+    int incount,
+    MPI_Datatype datatype,
+    _Out_ MPI_Aint* size
+    );
+
+
+/*---------------------------------------------------------------------------*/
+/* Chapter 5: Collective Communication                                       */
+/*---------------------------------------------------------------------------*/
+
+#define MPI_IN_PLACE ((void*)(MPI_Aint)-1)
+
+/*---------------------------------------------*/
+/* Section 5.3: Barrier Synchronization        */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Barrier(
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Barrier(
+    MPI_Comm comm
+    );
+
+
+/*---------------------------------------------*/
+/* Section 5.4: Broadcast                      */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Bcast(
+    _Inout_ void* buffer,
+    int count,
+    MPI_Datatype datatype,
+    int root,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Bcast(
+    _Inout_ void* buffer,
+    int count,
+    MPI_Datatype datatype,
+    int root,
+    MPI_Comm comm
+    );
+
+
+/*---------------------------------------------*/
+/* Section 5.5: Gather                         */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Gather(
+    _In_ void* sendbuf,
+    int sendcount,
+    MPI_Datatype sendtype,
+    _Out_opt_ void* recvbuf,
+    int recvcount,
+    MPI_Datatype recvtype,
+    int root,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Gather(
+    _In_ void* sendbuf,
+    int sendcount,
+    MPI_Datatype sendtype,
+    _Out_opt_ void* recvbuf,
+    int recvcount,
+    MPI_Datatype recvtype,
+    int root,
+    MPI_Comm comm
+    );
+
+int
+MPIAPI
+MPI_Gatherv(
+    _In_ void* sendbuf,
+    int sendcount,
+    MPI_Datatype sendtype,
+    _Out_opt_ void* recvbuf,
+    _In_opt_ int* recvcounts,
+    _In_opt_ int* displs,
+    MPI_Datatype recvtype,
+    int root,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Gatherv(
+    _In_ void* sendbuf,
+    int sendcount,
+    MPI_Datatype sendtype,
+    _Out_opt_ void* recvbuf,
+    _In_opt_ int* recvcounts,
+    _In_opt_ int* displs,
+    MPI_Datatype recvtype,
+    int root,
+    MPI_Comm comm
+    );
+
+
+/*---------------------------------------------*/
+/* Section 5.6: Scatter                        */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Scatter(
+    _In_ void* sendbuf,
+    int sendcount,
+    MPI_Datatype sendtype,
+    _Out_ void* recvbuf,
+    int recvcount,
+    MPI_Datatype recvtype,
+    int root,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Scatter(
+    _In_ void* sendbuf,
+    int sendcount,
+    MPI_Datatype sendtype,
+    _Out_ void* recvbuf,
+    int recvcount,
+    MPI_Datatype recvtype,
+    int root,
+    MPI_Comm comm
+    );
+
+int
+MPIAPI
+MPI_Scatterv(
+    _In_ void* sendbuf,
+    _In_ int* sendcounts,
+    _In_ int* displs,
+    MPI_Datatype sendtype,
+    _Out_ void* recvbuf,
+    int recvcount,
+    MPI_Datatype recvtype,
+    int root,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Scatterv(
+    _In_ void* sendbuf,
+    _In_ int* sendcounts,
+    _In_ int* displs,
+    MPI_Datatype sendtype,
+    _Out_ void* recvbuf,
+    int recvcount,
+    MPI_Datatype recvtype,
+    int root,
+    MPI_Comm comm
+    );
+
+
+/*---------------------------------------------*/
+/* Section 5.6: Gather-to-all                  */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Allgather(
+    _In_ void* sendbuf,
+    int sendcount,
+    MPI_Datatype sendtype,
+    _Out_ void* recvbuf,
+    int recvcount,
+    MPI_Datatype recvtype,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Allgather(
+    _In_ void* sendbuf,
+    int sendcount,
+    MPI_Datatype sendtype,
+    _Out_ void* recvbuf,
+    int recvcount,
+    MPI_Datatype recvtype,
+    MPI_Comm comm
+    );
+
+int
+MPIAPI
+MPI_Allgatherv(
+    _In_ void* sendbuf,
+    int sendcount,
+    MPI_Datatype sendtype,
+    _Out_ void* recvbuf,
+    _In_ int* recvcounts,
+    _In_ int* displs,
+    MPI_Datatype recvtype,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Allgatherv(
+    _In_ void* sendbuf,
+    int sendcount,
+    MPI_Datatype sendtype,
+    _Out_ void* recvbuf,
+    _In_ int* recvcounts,
+    _In_ int* displs,
+    MPI_Datatype recvtype,
+    MPI_Comm comm
+    );
+
+
+/*---------------------------------------------*/
+/* Section 5.6: All-to-All Scatter/Gather      */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Alltoall(
+    _In_ void* sendbuf,
+    int sendcount,
+    MPI_Datatype sendtype,
+    _Out_ void* recvbuf,
+    int recvcount,
+    MPI_Datatype recvtype,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Alltoall(
+    _In_ void* sendbuf,
+    int sendcount,
+    MPI_Datatype sendtype,
+    _Out_ void* recvbuf,
+    int recvcount,
+    MPI_Datatype recvtype,
+    MPI_Comm comm
+    );
+
+int
+MPIAPI
+MPI_Alltoallv(
+    _In_ void* sendbuf,
+    _In_ int* sendcounts,
+    _In_ int* sdispls,
+    MPI_Datatype sendtype,
+    _Out_ void* recvbuf,
+    _In_ int* recvcounts,
+    _In_ int* rdispls,
+    MPI_Datatype recvtype,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Alltoallv(
+    _In_ void* sendbuf,
+    _In_ int* sendcounts,
+    _In_ int* sdispls,
+    MPI_Datatype sendtype,
+    _Out_ void* recvbuf,
+    _In_ int* recvcounts,
+    _In_ int* rdispls,
+    MPI_Datatype recvtype,
+    MPI_Comm comm
+    );
+
+int
+MPIAPI
+MPI_Alltoallw(
+    _In_ void* sendbuf,
+    _In_ int sendcounts[],
+    _In_ int sdispls[],
+    _In_ MPI_Datatype sendtypes[],
+    _Out_ void* recvbuf,
+    _In_ int recvcounts[],
+    _In_ int rdispls[],
+    _In_ MPI_Datatype recvtypes[],
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Alltoallw(
+    _In_ void* sendbuf,
+    _In_ int sendcounts[],
+    _In_ int sdispls[],
+    _In_ MPI_Datatype sendtypes[],
+    _Out_ void* recvbuf,
+    _In_ int recvcounts[],
+    _In_ int rdispls[],
+    _In_ MPI_Datatype recvtypes[],
+    MPI_Comm comm
+    );
+
+
+/*---------------------------------------------*/
+/* Section 5.9: Global Reduction Operations    */
+/*---------------------------------------------*/
+
+typedef
+void
+(MPIAPI MPI_User_function)(
+    _In_count_(*len) void* invec,
+    _Inout_ void* inoutvec,
+    _In_ int* len,
+    _In_ MPI_Datatype* datatype
+    );
+
+int
+MPIAPI
+MPI_Op_create(
+    _In_ MPI_User_function* function,
+    int commute,
+    _Out_ MPI_Op* op
+    );
+int
+MPIAPI
+PMPI_Op_create(
+    _In_ MPI_User_function* function,
+    int commute,
+    _Out_ MPI_Op* op
+    );
+
+int
+MPIAPI
+MPI_Op_free(
+    _Inout_ MPI_Op* op
+    );
+int
+MPIAPI
+PMPI_Op_free(
+    _Inout_ MPI_Op* op
+    );
+
+int
+MPIAPI
+MPI_Reduce(
+    _In_ void* sendbuf,
+    _Out_opt_ void* recvbuf,
+    int count,
+    MPI_Datatype datatype,
+    MPI_Op op,
+    int root,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Reduce(
+    _In_ void* sendbuf,
+    _Out_opt_ void* recvbuf,
+    int count,
+    MPI_Datatype datatype,
+    MPI_Op op,
+    int root,
+    MPI_Comm comm
+    );
+
+int
+MPIAPI
+MPI_Allreduce(
+    _In_ void* sendbuf,
+    _Out_ void* recvbuf,
+    int count,
+    MPI_Datatype datatype,
+    MPI_Op op,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Allreduce(
+    _In_ void* sendbuf,
+    _Out_ void* recvbuf,
+    int count,
+    MPI_Datatype datatype,
+    MPI_Op op,
+    MPI_Comm comm
+    );
+
+int
+MPIAPI
+MPI_Reduce_local(
+    _In_ void *inbuf,
+    _Inout_ void *inoutbuf,
+    int count,
+    MPI_Datatype datatype,
+    MPI_Op op
+    );
+int
+MPIAPI
+PMPI_Reduce_local(
+    _In_ void *inbuf,
+    _Inout_ void *inoutbuf,
+    int count,
+    MPI_Datatype datatype,
+    MPI_Op op
+    );
+
+/*---------------------------------------------*/
+/* Section 5.10: Reduce-Scatter                */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Reduce_scatter(
+    _In_ void* sendbuf,
+    _Out_ void* recvbuf,
+    _In_ int* recvcounts,
+    MPI_Datatype datatype,
+    MPI_Op op,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Reduce_scatter(
+    _In_ void* sendbuf,
+    _Out_ void* recvbuf,
+    _In_ int* recvcounts,
+    MPI_Datatype datatype,
+    MPI_Op op,
+    MPI_Comm comm
+    );
+
+
+/*---------------------------------------------*/
+/* Section 5.11: Scan                          */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Scan(
+    _In_ void* sendbuf,
+    _Out_ void* recvbuf,
+    int count,
+    MPI_Datatype datatype,
+    MPI_Op op,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Scan(
+    _In_ void* sendbuf,
+    _Out_ void* recvbuf,
+    int count,
+    MPI_Datatype datatype,
+    MPI_Op op,
+    MPI_Comm comm
+    );
+
+int
+MPIAPI
+MPI_Exscan(
+    _In_ void* sendbuf,
+    _Out_ void* recvbuf,
+    int count,
+    MPI_Datatype datatype,
+    MPI_Op op,
+    MPI_Comm comm
+    );
+int
+MPIAPI
+PMPI_Exscan(
+    _In_ void* sendbuf,
+    _Out_ void* recvbuf,
+    int count,
+    MPI_Datatype datatype,
+    MPI_Op op,
+    MPI_Comm comm
+    );
+
+
+/*---------------------------------------------------------------------------*/
+/* Chapter 6: Groups, Contexts, Communicators, and Caching                   */
+/*---------------------------------------------------------------------------*/
+
+/*---------------------------------------------*/
+/* Section 6.3: Group Management               */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Group_size(
+    MPI_Group group,
+    _Out_ int* size
+    );
+int
+MPIAPI
+PMPI_Group_size(
+    MPI_Group group,
+    _Out_ int* size
+    );
+
+int
+MPIAPI
+MPI_Group_rank(
+    MPI_Group group,
+    _Out_ int* rank
+    );
+int
+MPIAPI
+PMPI_Group_rank(
+    MPI_Group group,
+    _Out_ int* rank
+    );
+
+int
+MPIAPI
+MPI_Group_translate_ranks(
+    MPI_Group group1,
+    int n,
+    _In_count_(n) int* ranks1,
+    MPI_Group group2,
+    _Out_ int* ranks2
+    );
+
+int
+MPIAPI
+PMPI_Group_translate_ranks(
+    MPI_Group group1,
+    int n,
+    _In_count_(n) int* ranks1,
+    MPI_Group group2,
+    _Out_ int* ranks2
+    );
+
+/* Results of the compare operations */
+#define MPI_IDENT       0
+#define MPI_CONGRUENT   1
+#define MPI_SIMILAR     2
+#define MPI_UNEQUAL     3
+
+int
+MPIAPI
+MPI_Group_compare(
+    MPI_Group group1,
+    MPI_Group group2,
+    _Out_ int* result
+    );
+int
+MPIAPI
+PMPI_Group_compare(
+    MPI_Group group1,
+    MPI_Group group2,
+    _Out_ int* result
+    );
+
+int
+MPIAPI
+MPI_Comm_group(
+    MPI_Comm comm,
+    _Out_ MPI_Group* group
+    );
+int
+MPIAPI
+PMPI_Comm_group(
+    MPI_Comm comm,
+    _Out_ MPI_Group* group
+    );
+
+int
+MPIAPI
+MPI_Group_union(
+    MPI_Group group1,
+    MPI_Group group2,
+    _Out_ MPI_Group* newgroup
+    );
+int
+MPIAPI
+PMPI_Group_union(
+    MPI_Group group1,
+    MPI_Group group2,
+    _Out_ MPI_Group* newgroup
+    );
+
+int
+MPIAPI
+MPI_Group_intersection(
+    MPI_Group group1,
+    MPI_Group group2,
+    _Out_ MPI_Group* newgroup
+    );
+int
+MPIAPI
+PMPI_Group_intersection(
+    MPI_Group group1,
+    MPI_Group group2,
+    _Out_ MPI_Group* newgroup
+    );
+
+int
+MPIAPI
+MPI_Group_difference(
+    MPI_Group group1,
+    MPI_Group group2,
+    _Out_ MPI_Group* newgroup
+    );
+int
+MPIAPI
+PMPI_Group_difference(
+    MPI_Group group1,
+    MPI_Group group2,
+    _Out_ MPI_Group* newgroup
+    );
+
+int
+MPIAPI
+MPI_Group_incl(
+    MPI_Group group,
+    int n,
+    _In_count_(n) int* ranks,
+    _Out_ MPI_Group* newgroup
+    );
+int
+MPIAPI
+PMPI_Group_incl(
+    MPI_Group group,
+    int n,
+    _In_count_(n) int* ranks,
+    _Out_ MPI_Group* newgroup
+    );
+
+int
+MPIAPI
+MPI_Group_excl(
+    MPI_Group group,
+    int n,
+    _In_count_(n) int* ranks,
+    _Out_ MPI_Group* newgroup
+    );
+int
+MPIAPI
+PMPI_Group_excl(
+    MPI_Group group,
+    int n,
+    _In_count_(n) int* ranks,
+    _Out_ MPI_Group* newgroup
+    );
+
+int
+MPIAPI
+MPI_Group_range_incl(
+    MPI_Group group,
+    int n,
+    _In_count_(n) int ranges[][3],
+    _Out_ MPI_Group* newgroup
+    );
+int
+MPIAPI
+PMPI_Group_range_incl(
+    MPI_Group group,
+    int n,
+    _In_count_(n) int ranges[][3],
+    _Out_ MPI_Group* newgroup
+    );
+
+int
+MPIAPI
+MPI_Group_range_excl(
+    MPI_Group group,
+    int n,
+    _In_count_(n) int ranges[][3],
+    _Out_ MPI_Group* newgroup
+    );
+int
+MPIAPI
+PMPI_Group_range_excl(
+    MPI_Group group,
+    int n,
+    _In_count_(n) int ranges[][3],
+    _Out_ MPI_Group* newgroup
+    );
+
+int
+MPIAPI
+MPI_Group_free(
+    _Inout_ MPI_Group* group
+    );
+int
+MPIAPI
+PMPI_Group_free(
+    _Inout_ MPI_Group* group
+    );
+
+
+/*---------------------------------------------*/
+/* Section 6.4: Communicator Management        */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Comm_size(
+    MPI_Comm comm,
+    _Out_ int* size
+    );
+int
+MPIAPI
+PMPI_Comm_size(
+    MPI_Comm comm,
+    _Out_ int* size
+    );
+
+int
+MPIAPI
+MPI_Comm_rank(
+    MPI_Comm comm,
+    _Out_ int* rank
+    );
+int
+MPIAPI
+PMPI_Comm_rank(
+    MPI_Comm comm,
+    _Out_ int* rank
+    );
+
+int
+MPIAPI
+MPI_Comm_compare(
+    MPI_Comm comm1,
+    MPI_Comm comm2,
+    _Out_ int* result
+    );
+int
+MPIAPI
+PMPI_Comm_compare(
+    MPI_Comm comm1,
+    MPI_Comm comm2,
+    _Out_ int* result
+    );
+
+int
+MPIAPI
+MPI_Comm_dup(
+    MPI_Comm comm,
+    _Out_ MPI_Comm* newcomm
+    );
+int
+MPIAPI
+PMPI_Comm_dup(
+    MPI_Comm comm,
+    _Out_ MPI_Comm* newcomm
+    );
+
+int
+MPIAPI
+MPI_Comm_create(
+    MPI_Comm comm,
+    MPI_Group group,
+    _Out_ MPI_Comm* newcomm
+    );
+int
+MPIAPI
+PMPI_Comm_create(
+    MPI_Comm comm,
+    MPI_Group group,
+    _Out_ MPI_Comm* newcomm
+    );
+
+int
+MPIAPI
+MPI_Comm_split(
+    MPI_Comm comm,
+    int color,
+    int key,
+    _Out_ MPI_Comm* newcomm
+    );
+int
+MPIAPI
+PMPI_Comm_split(
+    MPI_Comm comm,
+    int color,
+    int key,
+    _Out_ MPI_Comm* newcomm
+    );
+
+int
+MPIAPI
+MPI_Comm_free(
+    _Inout_ MPI_Comm* comm
+    );
+int
+MPIAPI
+PMPI_Comm_free(
+    _Inout_ MPI_Comm* comm
+    );
+
+
+/*---------------------------------------------*/
+/* Section 6.6: Inter-Communication            */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Comm_test_inter(
+    MPI_Comm comm,
+    _Out_ int* flag
+    );
+int
+MPIAPI
+PMPI_Comm_test_inter(
+    MPI_Comm comm,
+    _Out_ int* flag
+    );
+
+int
+MPIAPI
+MPI_Comm_remote_size(
+    MPI_Comm comm,
+    _Out_ int* size
+    );
+int
+MPIAPI
+PMPI_Comm_remote_size(
+    MPI_Comm comm,
+    _Out_ int* size
+    );
+
+int
+MPIAPI
+MPI_Comm_remote_group(
+    MPI_Comm comm,
+    _Out_ MPI_Group* group
+    );
+int
+MPIAPI
+PMPI_Comm_remote_group(
+    MPI_Comm comm,
+    _Out_ MPI_Group* group
+    );
+
+int
+MPIAPI
+MPI_Intercomm_create(
+    MPI_Comm local_comm,
+    int local_leader,
+    MPI_Comm peer_comm,
+    int remote_leader,
+    int tag,
+    _Out_ MPI_Comm* newintercomm
+    );
+int
+MPIAPI
+PMPI_Intercomm_create(
+    MPI_Comm local_comm,
+    int local_leader,
+    MPI_Comm peer_comm,
+    int remote_leader,
+    int tag,
+    _Out_ MPI_Comm* newintercomm
+    );
+
+int
+MPIAPI
+MPI_Intercomm_merge(
+    MPI_Comm intercomm,
+    int high,
+    _Out_ MPI_Comm* newintracomm
+    );
+int
+MPIAPI
+PMPI_Intercomm_merge(
+    MPI_Comm intercomm,
+    int high,
+    _Out_ MPI_Comm* newintracomm
+    );
+
+
+/*---------------------------------------------*/
+/* Section 6.7: Caching                        */
+/*---------------------------------------------*/
+
+#define MPI_KEYVAL_INVALID  0x24000000
+
+typedef
+int
+(MPIAPI MPI_Comm_copy_attr_function)(
+    MPI_Comm oldcomm,
+    int comm_keyval,
+    _In_opt_ void* extra_state,
+    _In_ void* attribute_val_in,
+    _Out_ void* attribute_val_out,
+    _Out_ int* flag
+    );
+
+typedef
+int
+(MPIAPI MPI_Comm_delete_attr_function)(
+    MPI_Comm comm,
+    int comm_keyval,
+    _In_ void* attribute_val,
+    _In_opt_ void* extra_state
+    );
+
+#define MPI_COMM_NULL_COPY_FN ((MPI_Comm_copy_attr_function*)0)
+#define MPI_COMM_NULL_DELETE_FN ((MPI_Comm_delete_attr_function*)0)
+#define MPI_COMM_DUP_FN ((MPI_Comm_copy_attr_function*)MPIR_Dup_fn)
+
+int
+MPIAPI
+MPI_Comm_create_keyval(
+    _In_opt_ MPI_Comm_copy_attr_function* comm_copy_attr_fn,
+    _In_opt_ MPI_Comm_delete_attr_function* comm_delete_attr_fn,
+    _Out_ int* comm_keyval,
+    _In_opt_ void* extra_state
+    );
+int
+MPIAPI
+PMPI_Comm_create_keyval(
+    _In_opt_ MPI_Comm_copy_attr_function* comm_copy_attr_fn,
+    _In_opt_ MPI_Comm_delete_attr_function* comm_delete_attr_fn,
+    _Out_ int* comm_keyval,
+    _In_opt_ void* extra_state
+    );
+
+int
+MPIAPI
+MPI_Comm_free_keyval(
+    _Inout_ int* comm_keyval
+    );
+int
+MPIAPI
+PMPI_Comm_free_keyval(
+    _Inout_ int* comm_keyval
+    );
+
+int
+MPIAPI
+MPI_Comm_set_attr(
+    MPI_Comm comm,
+    int comm_keyval,
+    _In_ void* attribute_val
+    );
+int
+MPIAPI
+PMPI_Comm_set_attr(
+    MPI_Comm comm,
+    int comm_keyval,
+    _In_ void* attribute_val
+    );
+
+
+/* Predefined comm attribute key values */
+/* C Versions (return pointer to value),
+   Fortran Versions (return integer value).
+
+   DO NOT CHANGE THESE.  The values encode:
+   builtin kind (0x1 in bit 30-31)
+   Keyval object (0x9 in bits 26-29)
+   for communicator (0x1 in bits 22-25)
+
+   Fortran versions of the attributes are formed by adding one to
+   the C version.
+ */
+#define MPI_TAG_UB          0x64400001
+#define MPI_HOST            0x64400003
+#define MPI_IO              0x64400005
+#define MPI_WTIME_IS_GLOBAL 0x64400007
+#define MPI_UNIVERSE_SIZE   0x64400009
+#define MPI_LASTUSEDCODE    0x6440000b
+#define MPI_APPNUM          0x6440000d
+
+int
+MPIAPI
+MPI_Comm_get_attr(
+    MPI_Comm comm,
+    int comm_keyval,
+    _Out_ void* attribute_val,
+    _Out_ int* flag
+    );
+int
+MPIAPI
+PMPI_Comm_get_attr(
+    MPI_Comm comm,
+    int comm_keyval,
+    _Out_ void* attribute_val,
+    _Out_ int* flag
+    );
+
+int
+MPIAPI
+MPI_Comm_delete_attr(
+    MPI_Comm comm,
+    int comm_keyval
+    );
+int
+MPIAPI
+PMPI_Comm_delete_attr(
+    MPI_Comm comm,
+    int comm_keyval
+    );
+
+
+typedef
+int
+(MPIAPI MPI_Win_copy_attr_function)(
+    MPI_Win oldwin,
+    int win_keyval,
+    _In_opt_ void* extra_state,
+    _In_ void* attribute_val_in,
+    _Out_ void* attribute_val_out,
+    _Out_ int* flag
+    );
+
+typedef
+int
+(MPIAPI MPI_Win_delete_attr_function)(
+    MPI_Win win,
+    int win_keyval,
+    _In_ void* attribute_val,
+    _In_opt_ void* extra_state
+    );
+
+#define MPI_WIN_NULL_COPY_FN ((MPI_Win_copy_attr_function*)0)
+#define MPI_WIN_NULL_DELETE_FN ((MPI_Win_delete_attr_function*)0)
+#define MPI_WIN_DUP_FN ((MPI_Win_copy_attr_function*)MPIR_Dup_fn)
+
+int
+MPIAPI
+MPI_Win_create_keyval(
+    _In_ MPI_Win_copy_attr_function* win_copy_attr_fn,
+    _In_ MPI_Win_delete_attr_function* win_delete_attr_fn,
+    _Out_ int* win_keyval,
+    _In_opt_ void* extra_state
+    );
+int
+MPIAPI
+PMPI_Win_create_keyval(
+    _In_ MPI_Win_copy_attr_function* win_copy_attr_fn,
+    _In_ MPI_Win_delete_attr_function* win_delete_attr_fn,
+    _Out_ int* win_keyval,
+    _In_opt_ void* extra_state
+    );
+
+int
+MPIAPI
+MPI_Win_free_keyval(
+    _Inout_ int* win_keyval
+    );
+int
+MPIAPI
+PMPI_Win_free_keyval(
+    _Inout_ int* win_keyval
+    );
+
+int
+MPIAPI
+MPI_Win_set_attr(
+    MPI_Win win,
+    int win_keyval,
+    _In_ void* attribute_val
+    );
+int
+MPIAPI
+PMPI_Win_set_attr(
+    MPI_Win win,
+    int win_keyval,
+    _In_ void* attribute_val
+    );
+
+
+/* Predefined window key value attributes */
+#define MPI_WIN_BASE        0x66000001
+#define MPI_WIN_SIZE        0x66000003
+#define MPI_WIN_DISP_UNIT   0x66000005
+
+int
+MPIAPI
+MPI_Win_get_attr(
+    MPI_Win win,
+    int win_keyval,
+    _Out_ void* attribute_val,
+    _Out_ int* flag
+    );
+int
+MPIAPI
+PMPI_Win_get_attr(
+    MPI_Win win,
+    int win_keyval,
+    _Out_ void* attribute_val,
+    _Out_ int* flag
+    );
+
+int
+MPIAPI
+MPI_Win_delete_attr(
+    MPI_Win win,
+    int win_keyval
+    );
+int
+MPIAPI
+PMPI_Win_delete_attr(
+    MPI_Win win,
+    int win_keyval
+    );
+
+
+typedef
+int
+(MPIAPI MPI_Type_copy_attr_function)(
+    MPI_Datatype olddatatype,
+    int datatype_keyval,
+    _In_opt_ void* extra_state,
+    _In_ void* attribute_val_in,
+    _Out_ void* attribute_val_out,
+    _Out_ int* flag
+    );
+
+typedef
+int
+(MPIAPI MPI_Type_delete_attr_function)(
+    MPI_Datatype datatype,
+    int datatype_keyval,
+    _In_ void* attribute_val,
+    _In_opt_ void* extra_state
+    );
+
+#define MPI_TYPE_NULL_COPY_FN ((MPI_Type_copy_attr_function*)0)
+#define MPI_TYPE_NULL_DELETE_FN ((MPI_Type_delete_attr_function*)0)
+#define MPI_TYPE_DUP_FN ((MPI_Type_copy_attr_function*)MPIR_Dup_fn)
+
+int
+MPIAPI
+MPI_Type_create_keyval(
+    _In_ MPI_Type_copy_attr_function* type_copy_attr_fn,
+    _In_ MPI_Type_delete_attr_function* type_delete_attr_fn,
+    _Out_ int* type_keyval,
+    _In_opt_ void* extra_state
+    );
+int
+MPIAPI
+PMPI_Type_create_keyval(
+    _In_ MPI_Type_copy_attr_function* type_copy_attr_fn,
+    _In_ MPI_Type_delete_attr_function* type_delete_attr_fn,
+    _Out_ int* type_keyval,
+    _In_opt_ void* extra_state
+    );
+
+int
+MPIAPI
+MPI_Type_free_keyval(
+    _Inout_ int* type_keyval
+    );
+int
+MPIAPI
+PMPI_Type_free_keyval(
+    _Inout_ int* type_keyval
+    );
+
+int
+MPIAPI
+MPI_Type_set_attr(
+    MPI_Datatype type,
+    int type_keyval,
+    _In_ void* attribute_val
+    );
+int
+MPIAPI
+PMPI_Type_set_attr(
+    MPI_Datatype type,
+    int type_keyval,
+    _In_ void* attribute_val
+    );
+
+int
+MPIAPI
+MPI_Type_get_attr(
+    MPI_Datatype type,
+    int type_keyval,
+    _Out_ void* attribute_val,
+    _Out_ int* flag
+    );
+int
+MPIAPI
+PMPI_Type_get_attr(
+    MPI_Datatype type,
+    int type_keyval,
+    _Out_ void* attribute_val,
+    _Out_ int* flag
+    );
+
+int
+MPIAPI
+MPI_Type_delete_attr(
+    MPI_Datatype datatype,
+    int type_keyval
+    );
+int
+MPIAPI
+PMPI_Type_delete_attr(
+    MPI_Datatype datatype,
+    int type_keyval
+    );
+
+
+/*---------------------------------------------*/
+/* Section 6.8: Naming Objects                 */
+/*---------------------------------------------*/
+
+#define MPI_MAX_OBJECT_NAME 128
+
+int
+MPIAPI
+MPI_Comm_set_name(
+    MPI_Comm comm,
+    _In_z_ char* comm_name
+    );
+int
+MPIAPI
+PMPI_Comm_set_name(
+    MPI_Comm comm,
+    _In_z_ char* comm_name
+    );
+
+int
+MPIAPI
+MPI_Comm_get_name(
+    MPI_Comm comm,
+    _Out_z_cap_post_count_(MPI_MAX_OBJECT_NAME,*resultlen) char* comm_name,
+    _Out_ int* resultlen
+    );
+int
+MPIAPI
+PMPI_Comm_get_name(
+    MPI_Comm comm,
+    _Out_z_cap_post_count_(MPI_MAX_OBJECT_NAME,*resultlen) char* comm_name,
+    _Out_ int* resultlen
+    );
+
+int
+MPIAPI
+MPI_Type_set_name(
+    MPI_Datatype type,
+    _In_z_ char* type_name
+    );
+int
+MPIAPI
+PMPI_Type_set_name(
+    MPI_Datatype type,
+    _In_z_ char* type_name
+    );
+
+int
+MPIAPI
+MPI_Type_get_name(
+    MPI_Datatype type,
+    _Out_z_cap_post_count_(MPI_MAX_OBJECT_NAME,*resultlen) char* type_name,
+    _Out_ int* resultlen
+    );
+int
+MPIAPI
+PMPI_Type_get_name(
+    MPI_Datatype type,
+    _Out_z_cap_post_count_(MPI_MAX_OBJECT_NAME,*resultlen) char* type_name,
+    _Out_ int* resultlen
+    );
+
+int
+MPIAPI
+MPI_Win_set_name(
+    MPI_Win win,
+    _In_z_ char* win_name
+    );
+int
+MPIAPI
+PMPI_Win_set_name(
+    MPI_Win win,
+    _In_z_ char* win_name
+    );
+
+int
+MPIAPI
+MPI_Win_get_name(
+    MPI_Win win,
+    _Out_z_cap_post_count_(MPI_MAX_OBJECT_NAME,*resultlen) char* win_name,
+    _Out_ int* resultlen
+    );
+int
+MPIAPI
+PMPI_Win_get_name(
+    MPI_Win win,
+    _Out_z_cap_post_count_(MPI_MAX_OBJECT_NAME,*resultlen) char* win_name,
+    _Out_ int* resultlen
+    );
+
+
+/*---------------------------------------------------------------------------*/
+/* Chapter 7: Process Topologies                                             */
+/*---------------------------------------------------------------------------*/
+
+int
+MPIAPI
+MPI_Cart_create(
+    MPI_Comm comm_old,
+    int ndims,
+    _In_count_(ndims) int* dims,
+    _In_count_(ndims) int* periods,
+    int reorder,
+    _Out_ MPI_Comm* comm_cart
+    );
+int
+MPIAPI
+PMPI_Cart_create(
+    MPI_Comm comm_old,
+    int ndims,
+    _In_count_(ndims) int* dims,
+    _In_count_(ndims) int* periods,
+    int reorder,
+    _Out_ MPI_Comm* comm_cart
+    );
+
+int
+MPIAPI
+MPI_Dims_create(
+    int nnodes,
+    int ndims,
+    _Inout_count_(ndims) int* dims
+    );
+int
+MPIAPI
+PMPI_Dims_create(
+    int nnodes,
+    int ndims,
+    _Inout_count_(ndims) int* dims
+    );
+
+int
+MPIAPI
+MPI_Graph_create(
+    MPI_Comm comm_old,
+    int nnodes,
+    _In_count_(nnodes) int* index,
+    _In_ int* edges,
+    int reorder,
+    _Out_ MPI_Comm* comm_cart
+    );
+int
+MPIAPI
+PMPI_Graph_create(
+    MPI_Comm comm_old,
+    int nnodes,
+    _In_count_(nnodes) int* index,
+    _In_ int* edges,
+    int reorder,
+    _Out_ MPI_Comm* comm_cart
+    );
+
+
+/* Topology types */
+enum
+{
+    MPI_GRAPH   = 1,
+    MPI_CART    = 2
+};
+
+int
+MPIAPI
+MPI_Topo_test(
+    MPI_Comm comm,
+    _Out_ int* status
+    );
+int
+MPIAPI
+PMPI_Topo_test(
+    MPI_Comm comm,
+    _Out_ int* status
+    );
+
+int
+MPIAPI
+MPI_Graphdims_get(
+    MPI_Comm comm,
+    _Out_ int* nnodes,
+    _Out_ int* nedges
+    );
+int
+MPIAPI
+PMPI_Graphdims_get(
+    MPI_Comm comm,
+    _Out_ int* nnodes,
+    _Out_ int* nedges
+    );
+
+int
+MPIAPI
+MPI_Graph_get(
+    MPI_Comm comm,
+    int maxindex,
+    int maxedges,
+    _Out_cap_(maxindex) int* index,
+    _Out_cap_(maxedges) int* edges
+    );
+int
+MPIAPI
+PMPI_Graph_get(
+    MPI_Comm comm,
+    int maxindex,
+    int maxedges,
+    _Out_cap_(maxindex) int* index,
+    _Out_cap_(maxedges) int* edges
+    );
+
+int
+MPIAPI
+MPI_Cartdim_get(
+    MPI_Comm comm,
+    _Out_ int* ndims
+    );
+int
+MPIAPI
+PMPI_Cartdim_get(
+    MPI_Comm comm,
+    _Out_ int* ndims
+    );
+
+int
+MPIAPI
+MPI_Cart_get(
+    MPI_Comm comm,
+    int maxdims,
+    _Out_cap_(maxdims) int* dims,
+    _Out_cap_(maxdims) int* periods,
+    _Out_cap_(maxdims) int* coords
+    );
+int
+MPIAPI
+PMPI_Cart_get(
+    MPI_Comm comm,
+    int maxdims,
+    _Out_cap_(maxdims) int* dims,
+    _Out_cap_(maxdims) int* periods,
+    _Out_cap_(maxdims) int* coords
+    );
+
+int
+MPIAPI
+MPI_Cart_rank(
+    MPI_Comm comm,
+    _In_ int* coords,
+    _Out_ int* rank
+    );
+int
+MPIAPI
+PMPI_Cart_rank(
+    MPI_Comm comm,
+    _In_ int* coords,
+    _Out_ int* rank
+    );
+
+int
+MPIAPI
+MPI_Cart_coords(
+    MPI_Comm comm,
+    int rank,
+    int maxdims,
+    _Out_cap_(maxdims) int* coords
+    );
+int
+MPIAPI
+PMPI_Cart_coords(
+    MPI_Comm comm,
+    int rank,
+    int maxdims,
+    _Out_cap_(maxdims) int* coords
+    );
+
+int
+MPIAPI
+MPI_Graph_neighbors_count(
+    MPI_Comm comm,
+    int rank,
+    _Out_ int* nneighbors
+    );
+int
+MPIAPI
+PMPI_Graph_neighbors_count(
+    MPI_Comm comm,
+    int rank,
+    _Out_ int* nneighbors
+    );
+
+int
+MPIAPI
+MPI_Graph_neighbors(
+    MPI_Comm comm,
+    int rank,
+    int maxneighbors,
+    _Out_cap_(maxneighbors) int* neighbors
+    );
+int
+MPIAPI
+PMPI_Graph_neighbors(
+    MPI_Comm comm,
+    int rank,
+    int maxneighbors,
+    _Out_cap_(maxneighbors) int* neighbors
+    );
+
+int
+MPIAPI
+MPI_Cart_shift(
+    MPI_Comm comm,
+    int direction,
+    int disp,
+    _Out_ int* rank_source,
+    _Out_ int* rank_dest
+    );
+int
+MPIAPI
+PMPI_Cart_shift(
+    MPI_Comm comm,
+    int direction,
+    int disp,
+    _Out_ int* rank_source,
+    _Out_ int* rank_dest
+    );
+
+int
+MPIAPI
+MPI_Cart_sub(
+    MPI_Comm comm,
+    _In_ int* remain_dims,
+    _Out_ MPI_Comm* newcomm
+    );
+int
+MPIAPI
+PMPI_Cart_sub(
+    MPI_Comm comm,
+    _In_ int* remain_dims,
+    _Out_ MPI_Comm* newcomm
+    );
+
+int
+MPIAPI
+MPI_Cart_map(
+    MPI_Comm comm,
+    int ndims,
+    _In_count_(ndims) int* dims,
+    _In_count_(ndims) int* periods,
+    _Out_ int* newrank
+    );
+int
+MPIAPI
+PMPI_Cart_map(
+    MPI_Comm comm,
+    int ndims,
+    _In_count_(ndims) int* dims,
+    _In_count_(ndims) int* periods,
+    _Out_ int* newrank
+    );
+
+int
+MPIAPI
+MPI_Graph_map(
+    MPI_Comm comm,
+    int nnodes,
+    _In_count_(nnodes) int* index,
+    _In_ int* edges,
+    _Out_ int* newrank
+    );
+int
+MPIAPI
+PMPI_Graph_map(
+    MPI_Comm comm,
+    int nnodes,
+    _In_count_(nnodes) int* index,
+    _In_ int* edges,
+    _Out_ int* newrank
+    );
+
+
+/*---------------------------------------------------------------------------*/
+/* Chapter 8: Environmental Management                                       */
+/*---------------------------------------------------------------------------*/
+
+/*---------------------------------------------*/
+/* Section 8.1: Implementation Information     */
+/*---------------------------------------------*/
+
+#define MPI_VERSION     2
+#define MPI_SUBVERSION  0
+
+int
+MPIAPI
+MPI_Get_version(
+    _Out_ int* version,
+    _Out_ int* subversion
+    );
+int
+MPIAPI
+PMPI_Get_version(
+    _Out_ int* version,
+    _Out_ int* subversion
+    );
+
+#define MPI_MAX_PROCESSOR_NAME  128
+
+int
+MPIAPI
+MPI_Get_processor_name(
+    _Out_z_cap_post_count_(MPI_MAX_PROCESSOR_NAME,*resultlen) char* name,
+    _Out_ int* resultlen
+    );
+int
+MPIAPI
+PMPI_Get_processor_name(
+    _Out_z_cap_post_count_(MPI_MAX_PROCESSOR_NAME,*resultlen) char* name,
+    _Out_ int* resultlen
+    );
+
+/*---------------------------------------------*/
+/* Section 8.2: Memory Allocation              */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Alloc_mem(
+    MPI_Aint size,
+    MPI_Info info,
+    _Out_ void* baseptr
+    );
+int
+MPIAPI
+PMPI_Alloc_mem(
+    MPI_Aint size,
+    MPI_Info info,
+    _Out_ void* baseptr
+    );
+
+int
+MPIAPI
+MPI_Free_mem(
+    _In_ void* base
+    );
+int
+MPIAPI
+PMPI_Free_mem(
+    _In_ void* base
+    );
+
+
+/*---------------------------------------------*/
+/* Section 8.3: Error Handling                 */
+/*---------------------------------------------*/
+
+typedef
+void
+(MPIAPI MPI_Comm_errhandler_fn)(
+    _In_ MPI_Comm* comm,
+    _Inout_ int* errcode,
+    ...
+    );
+
+int
+MPIAPI
+MPI_Comm_create_errhandler(
+    _In_ MPI_Comm_errhandler_fn* function,
+    _Out_ MPI_Errhandler* errhandler
+    );
+int
+MPIAPI
+PMPI_Comm_create_errhandler(
+    _In_ MPI_Comm_errhandler_fn* function,
+    _Out_ MPI_Errhandler* errhandler
+    );
+
+int
+MPIAPI
+MPI_Comm_set_errhandler(
+    MPI_Comm comm,
+    MPI_Errhandler errhandler
+    );
+int
+MPIAPI
+PMPI_Comm_set_errhandler(
+    MPI_Comm comm,
+    MPI_Errhandler errhandler
+    );
+
+int
+MPIAPI
+MPI_Comm_get_errhandler(
+    MPI_Comm comm,
+    _Out_ MPI_Errhandler* errhandler
+    );
+int
+MPIAPI
+PMPI_Comm_get_errhandler(
+    MPI_Comm comm,
+    _Out_ MPI_Errhandler* errhandler
+    );
+
+
+typedef
+void
+(MPIAPI MPI_Win_errhandler_fn)(
+    _In_ MPI_Win* win,
+    _Inout_ int* errcode,
+    ...
+    );
+
+int
+MPIAPI
+MPI_Win_create_errhandler(
+    _In_ MPI_Win_errhandler_fn* function,
+    _Out_ MPI_Errhandler* errhandler
+    );
+int
+MPIAPI
+PMPI_Win_create_errhandler(
+    _In_ MPI_Win_errhandler_fn* function,
+    _Out_ MPI_Errhandler* errhandler
+    );
+
+int
+MPIAPI
+MPI_Win_set_errhandler(
+    MPI_Win win,
+    MPI_Errhandler errhandler
+    );
+int
+MPIAPI
+PMPI_Win_set_errhandler(
+    MPI_Win win,
+    MPI_Errhandler errhandler
+    );
+
+int
+MPIAPI
+MPI_Win_get_errhandler(
+    MPI_Win win,
+    _Out_ MPI_Errhandler* errhandler
+    );
+int
+MPIAPI
+PMPI_Win_get_errhandler(
+    MPI_Win win,
+    _Out_ MPI_Errhandler* errhandler
+    );
+
+
+typedef
+void
+(MPIAPI MPI_File_errhandler_fn)(
+    _In_ MPI_File* file,
+    _Inout_ int* errcode,
+    ...
+    );
+
+int
+MPIAPI
+MPI_File_create_errhandler(
+    _In_ MPI_File_errhandler_fn* function,
+    _Out_ MPI_Errhandler* errhandler
+    );
+int
+MPIAPI
+PMPI_File_create_errhandler(
+    _In_ MPI_File_errhandler_fn* function,
+    _Out_ MPI_Errhandler* errhandler
+    );
+
+int
+MPIAPI
+MPI_File_set_errhandler(
+    MPI_File file,
+    MPI_Errhandler errhandler
+    );
+int
+MPIAPI
+PMPI_File_set_errhandler(
+    MPI_File file,
+    MPI_Errhandler errhandler
+    );
+
+int
+MPIAPI
+MPI_File_get_errhandler(
+    MPI_File file,
+    _Out_ MPI_Errhandler* errhandler
+    );
+int
+MPIAPI
+PMPI_File_get_errhandler(
+    MPI_File file,
+    _Out_ MPI_Errhandler* errhandler
+    );
+
+int
+MPIAPI
+MPI_Errhandler_free(
+    _Inout_ MPI_Errhandler* errhandler
+    );
+int
+MPIAPI
+PMPI_Errhandler_free(
+    _Inout_ MPI_Errhandler* errhandler
+    );
+
+#define MPI_MAX_ERROR_STRING    512
+
+int
+MPIAPI
+MPI_Error_string(
+    int errorcode,
+    _Out_z_cap_post_count_(MPI_MAX_ERROR_STRING,*resultlen) char* string,
+    _Out_ int* resultlen
+    );
+int
+MPIAPI
+PMPI_Error_string(
+    int errorcode,
+    _Out_z_cap_post_count_(MPI_MAX_ERROR_STRING,*resultlen) char* string,
+    _Out_ int* resultlen
+    );
+
+
+/*---------------------------------------------*/
+/* Section 8.4: Error Codes and Classes        */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Error_class(
+    int errorcode,
+    _Out_ int* errorclass
+    );
+int
+MPIAPI
+PMPI_Error_class(
+    int errorcode,
+    _Out_ int* errorclass
+    );
+
+int
+MPIAPI
+MPI_Add_error_class(
+    _Out_ int* errorclass
+    );
+int
+MPIAPI
+PMPI_Add_error_class(
+    _Out_ int* errorclass
+    );
+
+int
+MPIAPI
+MPI_Add_error_code(
+    int errorclass,
+    _Out_ int* errorcode
+    );
+int
+MPIAPI
+PMPI_Add_error_code(
+    int errorclass,
+    _Out_ int* errorcode
+    );
+
+int
+MPIAPI
+MPI_Add_error_string(
+    int errorcode,
+    _In_z_ char* string
+    );
+int
+MPIAPI
+PMPI_Add_error_string(
+    int errorcode,
+    _In_z_ char* string
+    );
+
+int
+MPIAPI
+MPI_Comm_call_errhandler(
+    MPI_Comm comm,
+    int errorcode
+    );
+int
+MPIAPI
+PMPI_Comm_call_errhandler(
+    MPI_Comm comm,
+    int errorcode
+    );
+
+int
+MPIAPI
+MPI_Win_call_errhandler(
+    MPI_Win win,
+    int errcode
+    );
+int
+MPIAPI
+PMPI_Win_call_errhandler(
+    MPI_Win win,
+    int errcode
+    );
+
+int
+MPIAPI
+MPI_File_call_errhandler(
+    MPI_File file,
+    int errorcode
+    );
+int
+MPIAPI
+PMPI_File_call_errhandler(
+    MPI_File file,
+    int errorcode
+    );
+
+
+/*---------------------------------------------*/
+/* Section 8.6: Timers and Synchronization     */
+/*---------------------------------------------*/
+
+double
+MPIAPI
+MPI_Wtime(
+    void
+    );
+double
+MPIAPI
+PMPI_Wtime(
+    void
+    );
+
+double
+MPIAPI
+MPI_Wtick(
+    void
+    );
+double
+MPIAPI
+PMPI_Wtick(
+    void
+    );
+
+
+/*---------------------------------------------*/
+/* Section 8.7: Startup                        */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Init(
+    _In_opt_ int* argc,
+    _In_opt_count_(*argc) char*** argv
+    );
+int
+MPIAPI
+PMPI_Init(
+    _In_opt_ int* argc,
+    _In_opt_count_(*argc) char*** argv
+    );
+
+int
+MPIAPI
+MPI_Finalize(
+    void
+    );
+int
+MPIAPI
+PMPI_Finalize(
+    void
+    );
+
+int
+MPIAPI
+MPI_Initialized(
+    _Out_ int* flag
+    );
+int
+MPIAPI
+PMPI_Initialized(
+    _Out_ int* flag
+    );
+
+int
+MPIAPI
+MPI_Abort(
+    MPI_Comm comm,
+    int errorcode
+    );
+int
+MPIAPI
+PMPI_Abort(
+    MPI_Comm comm,
+    int errorcode
+    );
+
+int
+MPIAPI
+MPI_Finalized(
+    _Out_ int* flag
+    );
+int
+MPIAPI
+PMPI_Finalized(
+    _Out_ int* flag
+    );
+
+
+/*---------------------------------------------------------------------------*/
+/* Chapter 9: The Info Object                                                */
+/*---------------------------------------------------------------------------*/
+
+#define MPI_MAX_INFO_KEY    255
+#define MPI_MAX_INFO_VAL   1024
+
+int
+MPIAPI
+MPI_Info_create(
+    _Out_ MPI_Info* info
+    );
+int
+MPIAPI
+PMPI_Info_create(
+    _Out_ MPI_Info* info
+    );
+
+int
+MPIAPI
+MPI_Info_set(
+    MPI_Info info,
+    _In_z_ char* key,
+    _In_z_ char* value
+    );
+int
+MPIAPI
+PMPI_Info_set(
+    MPI_Info info,
+    _In_z_ char* key,
+    _In_z_ char* value
+    );
+
+int
+MPIAPI
+MPI_Info_delete(
+    MPI_Info info,
+    _In_z_ char* key
+    );
+int
+MPIAPI
+PMPI_Info_delete(
+    MPI_Info info,
+    _In_z_ char* key
+    );
+
+int
+MPIAPI
+MPI_Info_get(
+    MPI_Info info,
+    _In_z_ char* key,
+    int valuelen,
+    _Out_z_cap_(valuelen) char* value,
+    _Out_ int* flag
+    );
+int
+MPIAPI
+PMPI_Info_get(
+    MPI_Info info,
+    _In_z_ char* key,
+    int valuelen,
+    _Out_z_cap_(valuelen) char* value,
+    _Out_ int* flag
+    );
+
+int
+MPIAPI
+MPI_Info_get_valuelen(
+    MPI_Info info,
+    _In_z_ char* key,
+    _Out_ int* valuelen,
+    _Out_ int* flag
+    );
+int
+MPIAPI
+PMPI_Info_get_valuelen(
+    MPI_Info info,
+    _In_z_ char* key,
+    _Out_ int* valuelen,
+    _Out_ int* flag
+    );
+
+int
+MPIAPI
+MPI_Info_get_nkeys(
+    MPI_Info info,
+    _Out_ int* nkeys
+    );
+int
+MPIAPI
+PMPI_Info_get_nkeys(
+    MPI_Info info,
+    _Out_ int* nkeys
+    );
+
+int
+MPIAPI
+MPI_Info_get_nthkey(
+    MPI_Info info,
+    int n,
+    _Out_z_cap_(MPI_MAX_INFO_KEY) char* key
+    );
+int
+MPIAPI
+PMPI_Info_get_nthkey(
+    MPI_Info info,
+    int n,
+    _Out_z_cap_(MPI_MAX_INFO_KEY) char* key
+    );
+
+int
+MPIAPI
+MPI_Info_dup(
+    MPI_Info info,
+    _Out_ MPI_Info* newinfo
+    );
+int
+MPIAPI
+PMPI_Info_dup(
+    MPI_Info info,
+    _Out_ MPI_Info* newinfo
+    );
+
+int
+MPIAPI
+MPI_Info_free(
+    _Inout_ MPI_Info* info
+    );
+int
+MPIAPI
+PMPI_Info_free(
+    _Inout_ MPI_Info* info
+    );
+
+
+/*---------------------------------------------------------------------------*/
+/* Chapter 10: Process Creation and Management                               */
+/*---------------------------------------------------------------------------*/
+
+/*---------------------------------------------*/
+/* Section 10.3: Process Manager Interface     */
+/*---------------------------------------------*/
+
+#define MPI_ARGV_NULL ((char**)0)
+#define MPI_ARGVS_NULL ((char***)0)
+
+#define MPI_ERRCODES_IGNORE ((int*)0)
+
+int
+MPIAPI
+MPI_Comm_spawn(
+    _In_z_ char* command,
+    _In_ char* argv[],
+    int maxprocs,
+    MPI_Info info,
+    int root,
+    MPI_Comm comm,
+    _Out_ MPI_Comm* intercomm,
+    _Out_opt_cap_(maxprocs) int array_of_errcodes[]
+    );
+int
+MPIAPI
+PMPI_Comm_spawn(
+    _In_z_ char* command,
+    _In_ char* argv[],
+    int maxprocs,
+    MPI_Info info,
+    int root,
+    MPI_Comm comm,
+    _Out_ MPI_Comm* intercomm,
+    _Out_opt_cap_(maxprocs) int array_of_errcodes[]
+    );
+
+int
+MPIAPI
+MPI_Comm_get_parent(
+    _Out_ MPI_Comm* parent
+    );
+int
+MPIAPI
+PMPI_Comm_get_parent(
+    _Out_ MPI_Comm* parent
+    );
+
+int
+MPIAPI
+MPI_Comm_spawn_multiple(
+    int count,
+    _In_count_(count) char* array_of_commands[],
+    _In_opt_count_(count) char** array_of_argv[],
+    _In_count_(count) int array_of_maxprocs[],
+    _In_count_(count) MPI_Info array_of_info[],
+    int root,
+    MPI_Comm comm,
+    _Out_ MPI_Comm* intercomm,
+    _Out_opt_ int array_of_errcodes[]
+    );
+int
+MPIAPI
+PMPI_Comm_spawn_multiple(
+    int count,
+    _In_count_(count) char* array_of_commands[],
+    _In_opt_count_(count) char** array_of_argv[],
+    _In_count_(count) int array_of_maxprocs[],
+    _In_count_(count) MPI_Info array_of_info[],
+    int root,
+    MPI_Comm comm,
+    _Out_ MPI_Comm* intercomm,
+    _Out_opt_ int array_of_errcodes[]
+    );
+
+
+/*---------------------------------------------*/
+/* Section 10.4: Establishing Communication    */
+/*---------------------------------------------*/
+
+#define MPI_MAX_PORT_NAME   256
+
+int
+MPIAPI
+MPI_Open_port(
+    MPI_Info info,
+    _Out_cap_(MPI_MAX_PORT_NAME) char* port_name
+    );
+int
+MPIAPI
+PMPI_Open_port(
+    MPI_Info info,
+    _Out_cap_(MPI_MAX_PORT_NAME) char* port_name
+    );
+
+int
+MPIAPI
+MPI_Close_port(
+    _In_z_ char* port_name
+    );
+int
+MPIAPI
+PMPI_Close_port(
+    _In_z_ char* port_name
+    );
+
+int
+MPIAPI
+MPI_Comm_accept(
+    _In_z_ char* port_name,
+    MPI_Info info,
+    int root,
+    MPI_Comm comm,
+    _Out_ MPI_Comm* newcomm
+    );
+int
+MPIAPI
+PMPI_Comm_accept(
+    _In_z_ char* port_name,
+    MPI_Info info,
+    int root,
+    MPI_Comm comm,
+    _Out_ MPI_Comm* newcomm
+    );
+
+int
+MPIAPI
+MPI_Comm_connect(
+    _In_z_ char* port_name,
+    MPI_Info info,
+    int root,
+    MPI_Comm comm,
+    _Out_ MPI_Comm* newcomm
+    );
+int
+MPIAPI
+PMPI_Comm_connect(
+    _In_z_ char* port_name,
+    MPI_Info info,
+    int root,
+    MPI_Comm comm,
+    _Out_ MPI_Comm* newcomm
+    );
+
+
+/*---------------------------------------------*/
+/* Section 10.4.4: Name Publishing             */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Publish_name(
+    _In_z_ char* service_name,
+    MPI_Info info,
+    _In_z_ char* port_name
+    );
+int
+MPIAPI
+PMPI_Publish_name(
+    _In_z_ char* service_name,
+    MPI_Info info,
+    _In_z_ char* port_name
+    );
+
+int
+MPIAPI
+MPI_Unpublish_name(
+    _In_z_ char* service_name,
+    MPI_Info info,
+    _In_z_ char* port_name
+    );
+int
+MPIAPI
+PMPI_Unpublish_name(
+    _In_z_ char* service_name,
+    MPI_Info info,
+    _In_z_ char* port_name
+    );
+
+int
+MPIAPI
+MPI_Lookup_name(
+    _In_z_ char* service_name,
+    MPI_Info info,
+    _Out_cap_(MPI_MAX_PORT_NAME) char* port_name
+    );
+int
+MPIAPI
+PMPI_Lookup_name(
+    _In_z_ char* service_name,
+    MPI_Info info,
+    _Out_cap_(MPI_MAX_PORT_NAME) char* port_name
+    );
+
+
+/*---------------------------------------------*/
+/* Section 10.5: Other Functionality           */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Comm_disconnect(
+    _In_ MPI_Comm* comm
+    );
+int
+MPIAPI
+PMPI_Comm_disconnect(
+    _In_ MPI_Comm* comm
+    );
+
+int
+MPIAPI
+MPI_Comm_join(
+    int fd,
+    _Out_ MPI_Comm* intercomm
+    );
+int
+MPIAPI
+PMPI_Comm_join(
+    int fd,
+    _Out_ MPI_Comm* intercomm
+    );
+
+
+/*---------------------------------------------------------------------------*/
+/* Chapter 11: One-Sided Communications                                      */
+/*---------------------------------------------------------------------------*/
+
+int
+MPIAPI
+MPI_Win_create(
+    _In_ void* base,
+    MPI_Aint size,
+    int disp_unit,
+    MPI_Info info,
+    MPI_Comm comm,
+    _Out_ MPI_Win* win
+    );
+int
+MPIAPI
+PMPI_Win_create(
+    _In_ void* base,
+    MPI_Aint size,
+    int disp_unit,
+    MPI_Info info,
+    MPI_Comm comm,
+    _Out_ MPI_Win* win
+    );
+
+int
+MPIAPI
+MPI_Win_free(
+    _Inout_ MPI_Win* win
+    );
+int
+MPIAPI
+PMPI_Win_free(
+    _Inout_ MPI_Win* win
+    );
+
+int
+MPIAPI
+MPI_Win_get_group(
+    MPI_Win win,
+    _Out_ MPI_Group* group
+    );
+int
+MPIAPI
+PMPI_Win_get_group(
+    MPI_Win win,
+    _Out_ MPI_Group* group
+    );
+
+int
+MPIAPI
+MPI_Put(
+    _In_ void* origin_addr,
+    int origin_count,
+    MPI_Datatype origin_datatype,
+    int target_rank,
+    MPI_Aint target_disp,
+    int target_count,
+    MPI_Datatype datatype,
+    MPI_Win win
+    );
+int
+MPIAPI
+PMPI_Put(
+    _In_ void* origin_addr,
+    int origin_count,
+    MPI_Datatype origin_datatype,
+    int target_rank,
+    MPI_Aint target_disp,
+    int target_count,
+    MPI_Datatype datatype,
+    MPI_Win win
+    );
+
+int
+MPIAPI
+MPI_Get(
+    _Out_ void* origin_addr,
+    int origin_count,
+    MPI_Datatype origin_datatype,
+    int target_rank,
+    MPI_Aint target_disp,
+    int target_count,
+    MPI_Datatype datatype,
+    MPI_Win win
+    );
+int
+MPIAPI
+PMPI_Get(
+    _Out_ void* origin_addr,
+    int origin_count,
+    MPI_Datatype origin_datatype,
+    int target_rank,
+    MPI_Aint target_disp,
+    int target_count,
+    MPI_Datatype datatype,
+    MPI_Win win
+    );
+
+int
+MPIAPI
+MPI_Accumulate(
+    _In_ void* origin_addr,
+    int origin_count,
+    MPI_Datatype origin_datatype,
+    int target_rank,
+    MPI_Aint target_disp,
+    int target_count,
+    MPI_Datatype datatype,
+    MPI_Op op,
+    MPI_Win win
+    );
+int
+MPIAPI
+PMPI_Accumulate(
+    _In_ void* origin_addr,
+    int origin_count,
+    MPI_Datatype origin_datatype,
+    int target_rank,
+    MPI_Aint target_disp,
+    int target_count,
+    MPI_Datatype datatype,
+    MPI_Op op,
+    MPI_Win win
+    );
+
+/* Asserts for one-sided communication */
+#define MPI_MODE_NOCHECK    1024
+#define MPI_MODE_NOSTORE    2048
+#define MPI_MODE_NOPUT      4096
+#define MPI_MODE_NOPRECEDE  8192
+#define MPI_MODE_NOSUCCEED 16384
+
+int
+MPIAPI
+MPI_Win_fence(
+    int assert,
+    MPI_Win win
+    );
+int
+MPIAPI
+PMPI_Win_fence(
+    int assert,
+    MPI_Win win
+    );
+
+int
+MPIAPI
+MPI_Win_start(
+    MPI_Group group,
+    int assert,
+    MPI_Win win
+    );
+int
+MPIAPI
+PMPI_Win_start(
+    MPI_Group group,
+    int assert,
+    MPI_Win win
+    );
+
+int
+MPIAPI
+MPI_Win_complete(
+    MPI_Win win
+    );
+int
+MPIAPI
+PMPI_Win_complete(
+    MPI_Win win
+    );
+
+int
+MPIAPI
+MPI_Win_post(
+    MPI_Group group,
+    int assert,
+    MPI_Win win
+    );
+int
+MPIAPI
+PMPI_Win_post(
+    MPI_Group group,
+    int assert,
+    MPI_Win win
+    );
+
+int
+MPIAPI
+MPI_Win_wait(
+    MPI_Win win
+    );
+int
+MPIAPI
+PMPI_Win_wait(
+    MPI_Win win
+    );
+
+int
+MPIAPI
+MPI_Win_test(
+    MPI_Win win,
+    _Out_ int* flag
+    );
+int
+MPIAPI
+PMPI_Win_test(
+    MPI_Win win,
+    _Out_ int* flag
+    );
+
+#define MPI_LOCK_EXCLUSIVE  234
+#define MPI_LOCK_SHARED     235
+
+int
+MPIAPI
+MPI_Win_lock(
+    int lock_type,
+    int rank,
+    int assert,
+    MPI_Win win
+    );
+int
+MPIAPI
+PMPI_Win_lock(
+    int lock_type,
+    int rank,
+    int assert,
+    MPI_Win win
+    );
+
+int
+MPIAPI
+MPI_Win_unlock(
+    int rank,
+    MPI_Win win
+    );
+int
+MPIAPI
+PMPI_Win_unlock(
+    int rank,
+    MPI_Win win
+    );
+
+
+/*---------------------------------------------------------------------------*/
+/* Chapter 12: External Interfaces                                           */
+/*---------------------------------------------------------------------------*/
+
+/*---------------------------------------------*/
+/* Section 12.2: Generalized Requests          */
+/*---------------------------------------------*/
+
+typedef
+int
+(MPIAPI MPI_Grequest_query_function)(
+    _In_opt_ void* extra_state,
+    _Out_ MPI_Status* status
+    );
+
+typedef
+int
+(MPIAPI MPI_Grequest_free_function)(
+    _In_opt_ void* extra_state
+    );
+
+typedef
+int
+(MPIAPI MPI_Grequest_cancel_function)(
+    _In_opt_ void* extra_state,
+    int complete
+    );
+
+int
+MPIAPI
+MPI_Grequest_start(
+    _In_ MPI_Grequest_query_function* query_fn,
+    _In_ MPI_Grequest_free_function* free_fn,
+    _In_ MPI_Grequest_cancel_function* cancel_fn,
+    _In_opt_ void* extra_state,
+    _Out_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_Grequest_start(
+    _In_ MPI_Grequest_query_function* query_fn,
+    _In_ MPI_Grequest_free_function* free_fn,
+    _In_ MPI_Grequest_cancel_function* cancel_fn,
+    _In_opt_ void* extra_state,
+    _Out_ MPI_Request* request
+    );
+
+int
+MPIAPI
+MPI_Grequest_complete(
+    MPI_Request request
+    );
+int
+MPIAPI
+PMPI_Grequest_complete(
+    MPI_Request request
+    );
+
+
+/*---------------------------------------------*/
+/* Section 12.3: Information with Status       */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Status_set_elements(
+    _In_ MPI_Status* status,
+    MPI_Datatype datatype,
+    int count
+    );
+int
+MPIAPI
+PMPI_Status_set_elements(
+    _In_ MPI_Status* status,
+    MPI_Datatype datatype,
+    int count
+    );
+
+int
+MPIAPI
+MPI_Status_set_cancelled(
+    _In_ MPI_Status* status,
+    int flag
+    );
+int
+MPIAPI
+PMPI_Status_set_cancelled(
+    _In_ MPI_Status* status,
+    int flag
+    );
+
+
+/*---------------------------------------------*/
+/* Section 12.4: Threads                       */
+/*---------------------------------------------*/
+
+#define MPI_THREAD_SINGLE       0
+#define MPI_THREAD_FUNNELED     1
+#define MPI_THREAD_SERIALIZED   2
+#define MPI_THREAD_MULTIPLE     3
+
+int
+MPIAPI
+MPI_Init_thread(
+    _In_opt_ int* argc,
+    _In_opt_count_(*argc) char*** argv,
+    int required,
+    _Out_ int* provided
+    );
+int
+MPIAPI
+PMPI_Init_thread(
+    _In_opt_ int* argc,
+    _In_opt_count_(*argc) char*** argv,
+    int required,
+    _Out_ int* provided
+    );
+
+int
+MPIAPI
+MPI_Query_thread(
+    _Out_ int* provided
+    );
+int
+MPIAPI
+PMPI_Query_thread(
+    _Out_ int* provided
+    );
+
+int
+MPIAPI
+MPI_Is_thread_main(
+    _Out_ int* flag
+    );
+int
+MPIAPI
+PMPI_Is_thread_main(
+    _Out_ int* flag
+    );
+
+
+/*---------------------------------------------------------------------------*/
+/* Chapter 13: I/O                                                           */
+/*---------------------------------------------------------------------------*/
+
+/*---------------------------------------------*/
+/* Section 13.2: File Manipulation             */
+/*---------------------------------------------*/
+
+#define MPI_MODE_CREATE             0x00000001
+#define MPI_MODE_RDONLY             0x00000002
+#define MPI_MODE_WRONLY             0x00000004
+#define MPI_MODE_RDWR               0x00000008
+#define MPI_MODE_DELETE_ON_CLOSE    0x00000010
+#define MPI_MODE_UNIQUE_OPEN        0x00000020
+#define MPI_MODE_EXCL               0x00000040
+#define MPI_MODE_APPEND             0x00000080
+#define MPI_MODE_SEQUENTIAL         0x00000100
+#define MSMPI_MODE_HIDDEN           0x00000200
+
+int
+MPIAPI
+MPI_File_open(
+    MPI_Comm comm,
+    _In_z_ char* filename,
+    int amode,
+    MPI_Info info,
+    _Out_ MPI_File* newfile
+    );
+int
+MPIAPI
+PMPI_File_open(
+    MPI_Comm comm,
+    _In_z_ char* filename,
+    int amode,
+    MPI_Info info,
+    _Out_ MPI_File* newfile
+    );
+
+int
+MPIAPI
+MPI_File_close(
+    _In_ MPI_File* file
+    );
+int
+MPIAPI
+PMPI_File_close(
+    _In_ MPI_File* file
+    );
+
+int
+MPIAPI
+MPI_File_delete(
+    _In_z_ char* filename,
+    MPI_Info info
+    );
+int
+MPIAPI
+PMPI_File_delete(
+    _In_z_ char* filename,
+    MPI_Info info
+    );
+
+int
+MPIAPI
+MPI_File_set_size(
+    MPI_File file,
+    MPI_Offset size
+    );
+int
+MPIAPI
+PMPI_File_set_size(
+    MPI_File file,
+    MPI_Offset size
+    );
+
+int
+MPIAPI
+MPI_File_preallocate(
+    MPI_File file,
+    MPI_Offset size
+    );
+int
+MPIAPI
+PMPI_File_preallocate(
+    MPI_File file,
+    MPI_Offset size
+    );
+
+int
+MPIAPI
+MPI_File_get_size(
+    MPI_File file,
+    _Out_ MPI_Offset* size
+    );
+int
+MPIAPI
+PMPI_File_get_size(
+    MPI_File file,
+    _Out_ MPI_Offset* size
+    );
+
+int
+MPIAPI
+MPI_File_get_group(
+    MPI_File file,
+    _Out_ MPI_Group* group
+    );
+int
+MPIAPI
+PMPI_File_get_group(
+    MPI_File file,
+    _Out_ MPI_Group* group
+    );
+
+int
+MPIAPI
+MPI_File_get_amode(
+    MPI_File file,
+    _Out_ int* amode
+    );
+int
+MPIAPI
+PMPI_File_get_amode(
+    MPI_File file,
+    _Out_ int* amode
+    );
+
+int
+MPIAPI
+MPI_File_set_info(
+    MPI_File file,
+    MPI_Info info
+    );
+int
+MPIAPI
+PMPI_File_set_info(
+    MPI_File file,
+    MPI_Info info
+    );
+
+int
+MPIAPI
+MPI_File_get_info(
+    MPI_File file,
+    _Out_ MPI_Info* info
+    );
+int
+MPIAPI
+PMPI_File_get_info(
+    MPI_File file,
+    _Out_ MPI_Info* info
+    );
+
+
+/*---------------------------------------------*/
+/* Section 13.3: File Views                    */
+/*---------------------------------------------*/
+
+#define MPI_DISPLACEMENT_CURRENT (-54278278)
+
+int
+MPIAPI
+MPI_File_set_view(
+    MPI_File file,
+    MPI_Offset disp,
+    MPI_Datatype etype,
+    MPI_Datatype filetype,
+    _In_z_ char* datarep,
+    MPI_Info info
+    );
+int
+MPIAPI
+PMPI_File_set_view(
+    MPI_File file,
+    MPI_Offset disp,
+    MPI_Datatype etype,
+    MPI_Datatype filetype,
+    _In_z_ char* datarep,
+    MPI_Info info
+    );
+
+#define MPI_MAX_DATAREP_STRING  128
+
+int
+MPIAPI
+MPI_File_get_view(
+    MPI_File file,
+    _Out_ MPI_Offset* disp,
+    _Out_ MPI_Datatype* etype,
+    _Out_ MPI_Datatype* filetype,
+    _Out_z_cap_(MPI_MAX_DATAREP_STRING) char* datarep
+    );
+int
+MPIAPI
+PMPI_File_get_view(
+    MPI_File file,
+    _Out_ MPI_Offset* disp,
+    _Out_ MPI_Datatype* etype,
+    _Out_ MPI_Datatype* filetype,
+    _Out_z_cap_(MPI_MAX_DATAREP_STRING) char* datarep
+    );
+
+
+/*---------------------------------------------*/
+/* Section 13.4: Data Access                   */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_File_read_at(
+    MPI_File file,
+    MPI_Offset offset,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_File_read_at(
+    MPI_File file,
+    MPI_Offset offset,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_File_read_at_all(
+    MPI_File file,
+    MPI_Offset offset,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_File_read_at_all(
+    MPI_File file,
+    MPI_Offset offset,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_File_write_at(
+    MPI_File file,
+    MPI_Offset offset,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_File_write_at(
+    MPI_File file,
+    MPI_Offset offset,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_File_write_at_all(
+    MPI_File file,
+    MPI_Offset offset,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_File_write_at_all(
+    MPI_File file,
+    MPI_Offset offset,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_File_iread_at(
+    MPI_File file,
+    MPI_Offset offset,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_File_iread_at(
+    MPI_File file,
+    MPI_Offset offset,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Request* request
+    );
+
+int
+MPIAPI
+MPI_File_iwrite_at(
+    MPI_File file,
+    MPI_Offset offset,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_File_iwrite_at(
+    MPI_File file,
+    MPI_Offset offset,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Request* request
+    );
+
+int
+MPIAPI
+MPI_File_read(
+    MPI_File file,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_File_read(
+    MPI_File file,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_File_read_all(
+    MPI_File file,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_File_read_all(
+    MPI_File file,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_File_write(
+    MPI_File file,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_File_write(
+    MPI_File file,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_File_write_all(
+    MPI_File file,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_File_write_all(
+    MPI_File file,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+
+
+int
+MPIAPI
+MPI_File_iread(
+    MPI_File file,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_File_iread(
+    _In_ MPI_File file,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Request* request
+    );
+
+int
+MPIAPI
+MPI_File_iwrite(
+    MPI_File file,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_File_iwrite(
+    MPI_File file,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Request* request
+    );
+
+
+/* File seek whence */
+#define MPI_SEEK_SET    600
+#define MPI_SEEK_CUR    602
+#define MPI_SEEK_END    604
+
+int
+MPIAPI
+MPI_File_seek(
+    MPI_File file,
+    MPI_Offset offset,
+    int whence
+    );
+int
+MPIAPI
+PMPI_File_seek(
+    MPI_File file,
+    MPI_Offset offset,
+    int whence
+    );
+
+int
+MPIAPI
+MPI_File_get_position(
+    MPI_File file,
+    _Out_ MPI_Offset* offset
+    );
+int
+MPIAPI
+PMPI_File_get_position(
+    MPI_File file,
+    _Out_ MPI_Offset* offset
+    );
+
+int
+MPIAPI
+MPI_File_get_byte_offset(
+    MPI_File file,
+    MPI_Offset offset,
+    _Out_ MPI_Offset* disp
+    );
+int
+MPIAPI
+PMPI_File_get_byte_offset(
+    MPI_File file,
+    MPI_Offset offset,
+    _Out_ MPI_Offset* disp
+    );
+
+int
+MPIAPI
+MPI_File_read_shared(
+    MPI_File file,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+     );
+int
+MPIAPI
+PMPI_File_read_shared(
+    MPI_File file,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+     );
+
+int
+MPIAPI
+MPI_File_write_shared(
+    MPI_File file,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_File_write_shared(
+    MPI_File file,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_File_iread_shared(
+    MPI_File file,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_File_iread_shared(
+    MPI_File file,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Request* request
+    );
+
+int
+MPIAPI
+MPI_File_iwrite_shared(
+    MPI_File file,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Request* request
+    );
+int
+MPIAPI
+PMPI_File_iwrite_shared(
+    MPI_File file,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Request* request
+    );
+
+int
+MPIAPI
+MPI_File_read_ordered(
+    MPI_File file,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_File_read_ordered(
+    MPI_File file,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_File_write_ordered(
+    _In_ MPI_File file,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_File_write_ordered(
+    MPI_File file,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_File_seek_shared(
+    MPI_File file,
+    MPI_Offset offset,
+    int whence
+    );
+int
+MPIAPI
+PMPI_File_seek_shared(
+    MPI_File file,
+    MPI_Offset offset,
+    int whence
+    );
+
+int
+MPIAPI
+MPI_File_get_position_shared(
+    MPI_File file,
+    _Out_ MPI_Offset* offset
+    );
+int
+MPIAPI
+PMPI_File_get_position_shared(
+    MPI_File file,
+    _Out_ MPI_Offset* offset
+    );
+
+int
+MPIAPI
+MPI_File_read_at_all_begin(
+    MPI_File file,
+    MPI_Offset offset,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype
+    );
+int
+MPIAPI
+PMPI_File_read_at_all_begin(
+    MPI_File file,
+    MPI_Offset offset,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype
+    );
+
+int
+MPIAPI
+MPI_File_read_at_all_end(
+    MPI_File file,
+    _Out_ void* buf,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_File_read_at_all_end(
+    MPI_File file,
+    _Out_ void* buf,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_File_write_at_all_begin(
+    MPI_File file,
+    MPI_Offset offset,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype
+    );
+int
+MPIAPI
+PMPI_File_write_at_all_begin(
+    MPI_File file,
+    MPI_Offset offset,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype
+    );
+
+int
+MPIAPI
+MPI_File_write_at_all_end(
+    MPI_File file,
+    _In_ void* buf,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_File_write_at_all_end(
+    MPI_File file,
+    _In_ void* buf,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_File_read_all_begin(
+    MPI_File file,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype
+    );
+int
+MPIAPI
+PMPI_File_read_all_begin(
+    MPI_File file,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype
+    );
+
+int
+MPIAPI
+MPI_File_read_all_end(
+    MPI_File file,
+    _Out_ void* buf,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_File_read_all_end(
+    MPI_File file,
+    _Out_ void* buf,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_File_write_all_begin(
+    MPI_File file,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype
+    );
+int
+MPIAPI
+PMPI_File_write_all_begin(
+    MPI_File file,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype
+    );
+
+int
+MPIAPI
+MPI_File_write_all_end(
+    MPI_File file,
+    _In_ void* buf,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_File_write_all_end(
+    MPI_File file,
+    _In_ void* buf,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_File_read_ordered_begin(
+    MPI_File file,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype
+    );
+int
+MPIAPI
+PMPI_File_read_ordered_begin(
+    MPI_File file,
+    _Out_ void* buf,
+    int count,
+    MPI_Datatype datatype
+    );
+
+int
+MPIAPI
+MPI_File_read_ordered_end(
+    MPI_File file,
+    _Out_ void* buf,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_File_read_ordered_end(
+    MPI_File file,
+    _Out_ void* buf,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_File_write_ordered_begin(
+    MPI_File file,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype
+    );
+int
+MPIAPI
+PMPI_File_write_ordered_begin(
+    MPI_File file,
+    _In_ void* buf,
+    int count,
+    MPI_Datatype datatype
+    );
+
+int
+MPIAPI
+MPI_File_write_ordered_end(
+    MPI_File file,
+    _In_ void* buf,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_File_write_ordered_end(
+    MPI_File file,
+    _In_ void* buf,
+    _Out_ MPI_Status* status
+    );
+
+
+/*---------------------------------------------*/
+/* Section 13.5: File Interoperability         */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_File_get_type_extent(
+    MPI_File file,
+    MPI_Datatype datatype,
+    _Out_ MPI_Aint* extent
+    );
+int
+MPIAPI
+PMPI_File_get_type_extent(
+    MPI_File file,
+    MPI_Datatype datatype,
+    _Out_ MPI_Aint* extent
+    );
+
+
+typedef
+int
+(MPIAPI MPI_Datarep_conversion_function)(
+    _Inout_ void* userbuf,
+    MPI_Datatype datatype,
+    int count,
+    _Inout_ void* filebuf,
+    MPI_Offset position,
+    _In_ void* extra_state
+    );
+
+typedef
+int
+(MPIAPI MPI_Datarep_extent_function)(
+    MPI_Datatype datatype,
+    _Out_ MPI_Aint* file_extent,
+    _In_ void* extra_state
+    );
+
+#define MPI_CONVERSION_FN_NULL ((MPI_Datarep_conversion_function*)0)
+
+int
+MPIAPI
+MPI_Register_datarep(
+    _In_z_ char* datarep,
+    _In_opt_ MPI_Datarep_conversion_function* read_conversion_fn,
+    _In_opt_ MPI_Datarep_conversion_function* write_conversion_fn,
+    _In_ MPI_Datarep_extent_function* dtype_file_extent_fn,
+    _In_opt_ void* extra_state
+    );
+int
+MPIAPI
+PMPI_Register_datarep(
+    _In_z_ char* datarep,
+    _In_opt_ MPI_Datarep_conversion_function* read_conversion_fn,
+    _In_opt_ MPI_Datarep_conversion_function* write_conversion_fn,
+    _In_ MPI_Datarep_extent_function* dtype_file_extent_fn,
+    _In_opt_ void* extra_state
+    );
+
+
+/*---------------------------------------------*/
+/* Section 13.6: Consistency and Semantics     */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_File_set_atomicity(
+    MPI_File file,
+    int flag
+    );
+int
+MPIAPI
+PMPI_File_set_atomicity(
+    MPI_File file,
+    int flag
+    );
+
+int
+MPIAPI
+MPI_File_get_atomicity(
+    MPI_File file,
+    _Out_ int* flag
+    );
+int
+MPIAPI
+PMPI_File_get_atomicity(
+    MPI_File file,
+    _Out_ int* flag
+    );
+
+int
+MPIAPI
+MPI_File_sync(
+    MPI_File file
+    );
+int
+MPIAPI
+PMPI_File_sync(
+    MPI_File file
+    );
+
+
+/*---------------------------------------------------------------------------*/
+/* Chapter 14: Profiling Interface                                           */
+/*---------------------------------------------------------------------------*/
+
+int
+MPIAPI
+MPI_Pcontrol(
+    const int level,
+    ...);
+int
+MPIAPI
+PMPI_Pcontrol(
+    const int level,
+    ...);
+
+
+/*---------------------------------------------------------------------------*/
+/* Chapter 15: Depricated Functions                                          */
+/*---------------------------------------------------------------------------*/
+
+#ifdef MSMPI_NO_DEPRECATE_20
+#define MSMPI_DEPRECATE_20( x )
+#else
+#define MSMPI_DEPRECATE_20( x ) __declspec(deprecated( \
+    "Deprecated in MPI 2.0, use '" #x "'.  " \
+    "To disable deprecation, define MSMPI_NO_DEPRECATE_20." ))
+#endif
+
+MSMPI_DEPRECATE_20( MPI_Type_create_hvector )
+int
+MPIAPI
+MPI_Type_hvector(
+    int count,
+    int blocklength,
+    MPI_Aint stride,
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+MSMPI_DEPRECATE_20( PMPI_Type_create_hvector )
+int
+MPIAPI
+PMPI_Type_hvector(
+    int count,
+    int blocklength,
+    MPI_Aint stride,
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+
+MSMPI_DEPRECATE_20( MPI_Type_create_hindexed )
+int
+MPIAPI
+MPI_Type_hindexed(
+    int count,
+    _In_count_(count) int array_of_blocklengths[],
+    _In_count_(count) MPI_Aint array_of_displacements[],
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+MSMPI_DEPRECATE_20( PMPI_Type_create_hindexed )
+int
+MPIAPI
+PMPI_Type_hindexed(
+    int count,
+    _In_count_(count) int array_of_blocklengths[],
+    _In_count_(count) MPI_Aint array_of_displacements[],
+    MPI_Datatype oldtype,
+    _Out_ MPI_Datatype* newtype
+    );
+
+MSMPI_DEPRECATE_20( MPI_Type_create_struct )
+int
+MPIAPI
+MPI_Type_struct(
+    int count,
+    _In_count_(count) int array_of_blocklengths[],
+    _In_count_(count) MPI_Aint array_of_displacements[],
+    _In_count_(count) MPI_Datatype array_of_types[],
+    _In_ MPI_Datatype* newtype
+    );
+MSMPI_DEPRECATE_20( PMPI_Type_create_struct )
+int
+MPIAPI
+PMPI_Type_struct(
+    int count,
+    _In_count_(count) int array_of_blocklengths[],
+    _In_count_(count) MPI_Aint array_of_displacements[],
+    _In_count_(count) MPI_Datatype array_of_types[],
+    _In_ MPI_Datatype* newtype
+    );
+
+MSMPI_DEPRECATE_20( MPI_Get_address )
+int
+MPIAPI
+MPI_Address(
+    _In_ void* location,
+    _Out_ MPI_Aint* address
+    );
+MSMPI_DEPRECATE_20( PMPI_Get_address )
+int
+MPIAPI
+PMPI_Address(
+    _In_ void* location,
+    _Out_ MPI_Aint* address
+    );
+
+MSMPI_DEPRECATE_20( MPI_Type_get_extent )
+int
+MPIAPI
+MPI_Type_extent(
+    MPI_Datatype datatype,
+    _Out_ MPI_Aint* extent
+    );
+MSMPI_DEPRECATE_20( PMPI_Type_get_extent )
+int
+MPIAPI
+PMPI_Type_extent(
+    MPI_Datatype datatype,
+    _Out_ MPI_Aint* extent
+    );
+
+MSMPI_DEPRECATE_20( MPI_Type_get_extent )
+int
+MPIAPI
+MPI_Type_lb(
+    MPI_Datatype datatype,
+    _Out_ MPI_Aint* displacement
+    );
+MSMPI_DEPRECATE_20( PMPI_Type_get_extent )
+int
+MPIAPI
+PMPI_Type_lb(
+    MPI_Datatype datatype,
+    _Out_ MPI_Aint* displacement
+    );
+
+MSMPI_DEPRECATE_20( MPI_Type_get_extent )
+int
+MPIAPI
+MPI_Type_ub(
+    MPI_Datatype datatype,
+    _Out_ MPI_Aint* displacement
+    );
+MSMPI_DEPRECATE_20( PMPI_Type_get_extent )
+int
+MPIAPI
+PMPI_Type_ub(
+    MPI_Datatype datatype,
+    _Out_ MPI_Aint* displacement
+    );
+
+
+typedef MPI_Comm_copy_attr_function MPI_Copy_function;
+typedef MPI_Comm_delete_attr_function MPI_Delete_function;
+
+#define MPI_NULL_COPY_FN ((MPI_Copy_function*)0)
+#define MPI_NULL_DELETE_FN ((MPI_Delete_function*)0)
+#define MPI_DUP_FN MPIR_Dup_fn
+
+
+MSMPI_DEPRECATE_20( MPI_Comm_create_keyval )
+int
+MPIAPI
+MPI_Keyval_create(
+    _In_ MPI_Copy_function* copy_fn,
+    _In_ MPI_Delete_function* delete_fn,
+    _Out_ int* keyval,
+    _In_opt_ void* extra_state
+    );
+MSMPI_DEPRECATE_20( PMPI_Comm_create_keyval )
+int
+MPIAPI
+PMPI_Keyval_create(
+    _In_ MPI_Copy_function* copy_fn,
+    _In_ MPI_Delete_function* delete_fn,
+    _Out_ int* keyval,
+    _In_opt_ void* extra_state
+    );
+
+MSMPI_DEPRECATE_20( MPI_Comm_free_keyval )
+int
+MPIAPI
+MPI_Keyval_free(
+    _Inout_ int* keyval
+    );
+MSMPI_DEPRECATE_20( PMPI_Comm_free_keyval )
+int
+MPIAPI
+PMPI_Keyval_free(
+    _Inout_ int* keyval
+    );
+
+MSMPI_DEPRECATE_20( MPI_Comm_set_attr )
+int
+MPIAPI
+MPI_Attr_put(
+    MPI_Comm comm,
+    int keyval,
+    _In_ void* attribute_val
+    );
+MSMPI_DEPRECATE_20( PMPI_Comm_set_attr )
+int
+MPIAPI
+PMPI_Attr_put(
+    MPI_Comm comm,
+    int keyval,
+    _In_ void* attribute_val
+    );
+
+MSMPI_DEPRECATE_20( MPI_Comm_get_attr )
+int
+MPIAPI
+MPI_Attr_get(
+    MPI_Comm comm,
+    int keyval,
+    _Out_ void* attribute_val,
+    _Out_ int* flag
+    );
+MSMPI_DEPRECATE_20( PMPI_Comm_get_attr )
+int
+MPIAPI
+PMPI_Attr_get(
+    MPI_Comm comm,
+    int keyval,
+    _Out_ void* attribute_val,
+    _Out_ int* flag
+    );
+
+MSMPI_DEPRECATE_20( MPI_Comm_delete_attr )
+int
+MPIAPI
+MPI_Attr_delete(
+    MPI_Comm comm,
+    int keyval
+    );
+MSMPI_DEPRECATE_20( PMPI_Comm_delete_attr )
+int
+MPIAPI
+PMPI_Attr_delete(
+    MPI_Comm comm,
+    int keyval
+    );
+
+
+typedef MPI_Comm_errhandler_fn MPI_Handler_function;
+
+MSMPI_DEPRECATE_20( MPI_Comm_create_errhandler )
+int
+MPIAPI
+MPI_Errhandler_create(
+    _In_ MPI_Handler_function* function,
+    _Out_ MPI_Errhandler* errhandler
+    );
+MSMPI_DEPRECATE_20( PMPI_Comm_create_errhandler )
+int
+MPIAPI
+PMPI_Errhandler_create(
+    _In_ MPI_Handler_function* function,
+    _Out_ MPI_Errhandler* errhandler
+    );
+
+MSMPI_DEPRECATE_20( MPI_Comm_set_errhandler )
+int
+MPIAPI
+MPI_Errhandler_set(
+    MPI_Comm comm,
+    MPI_Errhandler errhandler
+    );
+MSMPI_DEPRECATE_20( PMPI_Comm_set_errhandler )
+int
+MPIAPI
+PMPI_Errhandler_set(
+    MPI_Comm comm,
+    MPI_Errhandler errhandler
+    );
+
+MSMPI_DEPRECATE_20( MPI_Comm_get_errhandler )
+int
+MPIAPI
+MPI_Errhandler_get(
+    MPI_Comm comm,
+    _Out_ MPI_Errhandler* errhandler
+    );
+MSMPI_DEPRECATE_20( PMPI_Comm_get_errhandler )
+int
+MPIAPI
+PMPI_Errhandler_get(
+    MPI_Comm comm,
+    _Out_ MPI_Errhandler* errhandler
+    );
+
+
+/*---------------------------------------------------------------------------*/
+/* Chapter 16: Language Bindings                                             */
+/*---------------------------------------------------------------------------*/
+
+/*---------------------------------------------*/
+/* Section 16.2: Fortran Support               */
+/*---------------------------------------------*/
+
+int
+MPIAPI
+MPI_Type_create_f90_real(
+    int p,
+    int r,
+    _Out_ MPI_Datatype* newtype
+    );
+int
+MPIAPI
+PMPI_Type_create_f90_real(
+    int p,
+    int r,
+    _Out_ MPI_Datatype* newtype
+    );
+
+int
+MPIAPI
+MPI_Type_create_f90_complex(
+    int p,
+    int r,
+    _Out_ MPI_Datatype* newtype
+    );
+int
+MPIAPI
+PMPI_Type_create_f90_complex(
+    int p,
+    int r,
+    _Out_ MPI_Datatype* newtype
+    );
+
+int
+MPIAPI
+MPI_Type_create_f90_integer(
+    int r,
+    _Out_ MPI_Datatype* newtype
+    );
+int
+MPIAPI
+PMPI_Type_create_f90_integer(
+    int r,
+    _Out_ MPI_Datatype* newtype
+    );
+
+/* typeclasses */
+#define MPI_TYPECLASS_REAL      1
+#define MPI_TYPECLASS_INTEGER   2
+#define MPI_TYPECLASS_COMPLEX   3
+
+int
+MPIAPI
+MPI_Type_match_size(
+    int typeclass,
+    int size,
+    _Out_ MPI_Datatype* type
+    );
+int
+MPIAPI
+PMPI_Type_match_size(
+    int typeclass,
+    int size,
+    _Out_ MPI_Datatype* type
+    );
+
+
+/*---------------------------------------------*/
+/* Section 16.3: Language Interoperability     */
+/*---------------------------------------------*/
+
+#define MPI_Comm_c2f(comm)  (MPI_Fint)(comm)
+#define PMPI_Comm_c2f(comm) (MPI_Fint)(comm)
+
+#define MPI_Comm_f2c(comm)  (MPI_Comm)(comm)
+#define PMPI_Comm_f2c(comm) (MPI_Comm)(comm)
+
+
+#define MPI_Type_f2c(datatype)  (MPI_Datatype)(datatype)
+#define PMPI_Type_f2c(datatype) (MPI_Datatype)(datatype)
+
+#define MPI_Type_c2f(datatype)  (MPI_Fint)(datatype)
+#define PMPI_Type_c2f(datatype) (MPI_Fint)(datatype)
+
+
+#define MPI_Group_f2c(group)  (MPI_Group)(group)
+#define PMPI_Group_f2c(group) (MPI_Group)(group)
+
+#define MPI_Group_c2f(group)  (MPI_Fint)(group)
+#define PMPI_Group_c2f(group) (MPI_Fint)(group)
+
+
+#define MPI_Request_f2c(request)  (MPI_Request)(request)
+#define PMPI_Request_f2c(request) (MPI_Request)(request)
+
+#define MPI_Request_c2f(request)  (MPI_Fint)(request)
+#define PMPI_Request_c2f(request) (MPI_Fint)(request)
+
+
+#define MPI_Win_f2c(win)  (MPI_Win)(win)
+#define PMPI_Win_f2c(win) (MPI_Win)(win)
+
+#define MPI_Win_c2f(win)  (MPI_Fint)(win)
+#define PMPI_Win_c2f(win) (MPI_Fint)(win)
+
+
+#define MPI_Op_c2f(op)  (MPI_Fint)(op)
+#define PMPI_Op_c2f(op) (MPI_Fint)(op)
+
+#define MPI_Op_f2c(op)  (MPI_Op)(op)
+#define PMPI_Op_f2c(op) (MPI_Op)(op)
+
+
+#define MPI_Info_c2f(info)  (MPI_Fint)(info)
+#define PMPI_Info_c2f(info) (MPI_Fint)(info)
+
+#define MPI_Info_f2c(info)  (MPI_Info)(info)
+#define PMPI_Info_f2c(info) (MPI_Info)(info)
+
+
+#define MPI_Errhandler_c2f(errhandler)  (MPI_Fint)(errhandler)
+#define PMPI_Errhandler_c2f(errhandler) (MPI_Fint)(errhandler)
+
+#define MPI_Errhandler_f2c(errhandler)  (MPI_Errhandler)(errhandler)
+#define PMPI_Errhandler_f2c(errhandler) (MPI_Errhandler)(errhandler)
+
+
+MPI_File
+MPIAPI
+MPI_File_f2c(
+    MPI_Fint file
+    );
+MPI_File
+MPIAPI
+PMPI_File_f2c(
+    MPI_Fint file
+    );
+
+MPI_Fint
+MPIAPI
+MPI_File_c2f(
+    MPI_File file
+    );
+MPI_Fint
+MPIAPI
+PMPI_File_c2f(
+    MPI_File file
+    );
+
+int
+MPIAPI
+MPI_Status_f2c(
+    _In_ MPI_Fint* f_status,
+    _Out_ MPI_Status* status
+    );
+int
+MPIAPI
+PMPI_Status_f2c(
+    _In_ MPI_Fint* f_status,
+    _Out_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MPI_Status_c2f(
+    _In_ MPI_Status* status,
+    _Out_ MPI_Fint* f_status
+    );
+int
+MPIAPI
+PMPI_Status_c2f(
+    _In_ MPI_Status* status,
+    _Out_ MPI_Fint* f_status
+    );
+
+
+#if !defined(_MPICH_DLL_)
+#define MPIU_DLL_SPEC __declspec(dllimport)
+#else
+#define MPIU_DLL_SPEC
+#endif
+
+extern MPIU_DLL_SPEC MPI_Fint* MPI_F_STATUS_IGNORE;
+extern MPIU_DLL_SPEC MPI_Fint* MPI_F_STATUSES_IGNORE;
+
+
+/*---------------------------------------------------------------------------*/
+/* Implementation Specific                                                   */
+/*---------------------------------------------------------------------------*/
+
+int
+MPIAPI
+MPIR_Dup_fn(
+    MPI_Comm oldcomm,
+    int keyval,
+    _In_opt_ void* extra_state,
+    _In_ void* attribute_val_in,
+    _Out_ void* attribute_val_out,
+    _Out_ int* flag
+    );
+
+
+#if MSMPI_VER >= 0x300
+
+int
+MPIAPI
+MSMPI_Get_bsend_overhead();
+
+#endif
+
+
+#if MSMPI_VER >= 0x300
+
+int
+MPIAPI
+MSMPI_Get_version();
+
+#else
+#  define MSMPI_Get_version() (MSMPI_VER)
+#endif
+
+typedef void
+(MPIAPI MSMPI_Request_callback)(
+    _In_ MPI_Status* status
+    );
+
+int
+MPIAPI
+MSMPI_Request_set_apc(
+    MPI_Request request,
+    _In_ MSMPI_Request_callback* callback_fn,
+    _In_ MPI_Status* callback_status
+    );
+
+typedef struct _MSMPI_LOCK_QUEUE
+{
+    struct _MSMPI_LOCK_QUEUE* volatile next;
+    volatile MPI_Aint flags;
+
+} MSMPI_Lock_queue;
+
+void
+MPIAPI
+MSMPI_Queuelock_acquire(
+    _Out_ MSMPI_Lock_queue* queue
+    );
+
+void
+MPIAPI
+MSMPI_Queuelock_release(
+    _In_ MSMPI_Lock_queue* queue
+    );
+
+int
+MPIAPI
+MSMPI_Waitsome_interruptible(
+    int incount,
+    _Inout_count_(incount) MPI_Request array_of_requests[],
+    _Out_ int* outcount,
+    _Out_cap_post_count_(incount,*outcount) int array_of_indices[],
+    _Out_cap_post_count_(incount,*outcount) MPI_Status array_of_statuses[]
+    );
+
+
+/*---------------------------------------------------------------------------*/
+/* SAL ANNOTATIONS                                                           */
+/*---------------------------------------------------------------------------*/
+
+//OACR_WARNING_POP
+
+#ifdef MSMPI_DEFINED_SAL
+#undef MSMPI_DEFINED_SAL
+#undef _In_
+#undef _In_z_
+#undef _In_opt_
+#undef _In_count_
+#undef _In_bytecount_
+#undef _In_opt_count_
+#undef _Out_
+#undef _Out_cap_
+#undef _Out_cap_post_count_
+#undef _Out_bytecap_
+#undef _Out_z_cap_
+#undef _Out_z_cap_post_count_
+#undef _Out_cap_post_part_
+#undef _Out_opt_
+#undef _Out_opt_cap_
+#undef _Post_z_
+#undef _Inout_
+#undef _Inout_count_
+#endif
+
+#if defined(__cplusplus)
+}
+#endif
+
+#endif /* MPI_INCLUDED */

From 8404e9c8de25b39ee79ad9a0bdfaac53006c89b9 Mon Sep 17 00:00:00 2001
From: erw <erw@microsoft.com>
Date: Tue, 19 May 2015 12:05:29 -0700
Subject: [PATCH 46/49] Enable MKL

---
 MachineLearning/CNTK/CNTK.vcxproj         |  2 +-
 MachineLearning/CNTKEval/CNTKEval.vcxproj |  8 +++++---
 Math/Math/CNTKMathCUDA.vcxproj            |  2 ++
 Math/Math/Math.vcxproj                    | 22 ++++++++++++----------
 4 files changed, 20 insertions(+), 14 deletions(-)

diff --git a/MachineLearning/CNTK/CNTK.vcxproj b/MachineLearning/CNTK/CNTK.vcxproj
index b35b19492..cbd6924e0 100644
--- a/MachineLearning/CNTK/CNTK.vcxproj
+++ b/MachineLearning/CNTK/CNTK.vcxproj
@@ -121,7 +121,7 @@
       <OptimizeReferences>true</OptimizeReferences>
       <AdditionalDependencies>CNTKMath.lib; nvml.lib; kernel32.lib; user32.lib; shell32.lib; %(AdditionalDependencies)</AdditionalDependencies>
       <Profile>true</Profile>
-      <DelayLoadDLLs>CNTKMath.dll; nvml.dll; cudart64_70.dll</DelayLoadDLLs>
+      <DelayLoadDLLs>CNTKMath.dll;nvml.dll;CUDart64_70.dll</DelayLoadDLLs>
       <AdditionalLibraryDirectories>"c:\Program Files\NVIDIA Corporation\GDK\gdk_win7_amd64_release\nvml\lib"; $(ProjectDir)/mpi/$(Platform)</AdditionalLibraryDirectories>
     </Link>
     <PostBuildEvent>
diff --git a/MachineLearning/CNTKEval/CNTKEval.vcxproj b/MachineLearning/CNTKEval/CNTKEval.vcxproj
index 679eb72cd..8ef6b57bc 100644
--- a/MachineLearning/CNTKEval/CNTKEval.vcxproj
+++ b/MachineLearning/CNTKEval/CNTKEval.vcxproj
@@ -30,6 +30,7 @@
     <UseDebugLibraries>true</UseDebugLibraries>
     <PlatformToolset>v120</PlatformToolset>
     <CharacterSet>Unicode</CharacterSet>
+    <UseIntelMKL>Parallel</UseIntelMKL>
   </PropertyGroup>
   <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'" Label="Configuration">
     <ConfigurationType>DynamicLibrary</ConfigurationType>
@@ -37,6 +38,7 @@
     <PlatformToolset>v120</PlatformToolset>
     <WholeProgramOptimization>true</WholeProgramOptimization>
     <CharacterSet>Unicode</CharacterSet>
+    <UseIntelMKL>Parallel</UseIntelMKL>
   </PropertyGroup>
   <Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
   <ImportGroup Label="ExtensionSettings">
@@ -74,7 +76,7 @@
       <SubSystem>Windows</SubSystem>
       <GenerateDebugInformation>true</GenerateDebugInformation>
       <AdditionalDependencies>CNTKMath.lib; nvml.lib; kernel32.lib; user32.lib; shell32.lib; %(AdditionalDependencies)</AdditionalDependencies>
-      <AdditionalLibraryDirectories>$(SolutionDir)$(Platform)\$(Configuration)\; "c:\Program Files\NVIDIA Corporation\GDK\gdk_win7_amd64_release\nvml\lib"</AdditionalLibraryDirectories>
+      <AdditionalLibraryDirectories>..\..\math\$(Platform)\$(Configuration);$(SolutionDir)$(Platform)\$(Configuration)\; "c:\Program Files\NVIDIA Corporation\GDK\gdk_win7_amd64_release\nvml\lib"</AdditionalLibraryDirectories>
       <DelayLoadDLLs>CNTKMath.dll; nvml.dll; cudart64_70.dll</DelayLoadDLLs>
     </Link>
     <PostBuildEvent>
@@ -103,7 +105,7 @@
       <EnableCOMDATFolding>true</EnableCOMDATFolding>
       <OptimizeReferences>true</OptimizeReferences>
       <AdditionalDependencies>CNTKMath.lib; nvml.lib; kernel32.lib; user32.lib; shell32.lib; %(AdditionalDependencies)</AdditionalDependencies>
-      <AdditionalLibraryDirectories>$(SolutionDir)$(Platform)\$(Configuration)\; "c:\Program Files\NVIDIA Corporation\GDK\gdk_win7_amd64_release\nvml\lib"</AdditionalLibraryDirectories>
+      <AdditionalLibraryDirectories>..\..\math\$(Platform)\$(Configuration);$(SolutionDir)$(Platform)\$(Configuration)\; "c:\Program Files\NVIDIA Corporation\GDK\gdk_win7_amd64_release\nvml\lib"</AdditionalLibraryDirectories>
       <Profile>true</Profile>
       <DelayLoadDLLs>CNTKMath.dll; nvml.dll; cudart64_70.dll</DelayLoadDLLs>
     </Link>
@@ -156,4 +158,4 @@
   <Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
   <ImportGroup Label="ExtensionTargets">
   </ImportGroup>
-</Project>
\ No newline at end of file
+</Project>
diff --git a/Math/Math/CNTKMathCUDA.vcxproj b/Math/Math/CNTKMathCUDA.vcxproj
index 2c4c0666b..46dd5bf6f 100644
--- a/Math/Math/CNTKMathCUDA.vcxproj
+++ b/Math/Math/CNTKMathCUDA.vcxproj
@@ -31,6 +31,7 @@
     <UseDebugLibraries>true</UseDebugLibraries>
     <PlatformToolset>v120</PlatformToolset>
     <CharacterSet>Unicode</CharacterSet>
+    <UseIntelMKL>No</UseIntelMKL>
   </PropertyGroup>
   <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'" Label="Configuration">
     <ConfigurationType>StaticLibrary</ConfigurationType>
@@ -38,6 +39,7 @@
     <PlatformToolset>v120</PlatformToolset>
     <WholeProgramOptimization>true</WholeProgramOptimization>
     <CharacterSet>Unicode</CharacterSet>
+    <UseIntelMKL>No</UseIntelMKL>
   </PropertyGroup>
   <Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
   <ImportGroup Label="ExtensionSettings">
diff --git a/Math/Math/Math.vcxproj b/Math/Math/Math.vcxproj
index 33b3c951b..6e537fe5b 100644
--- a/Math/Math/Math.vcxproj
+++ b/Math/Math/Math.vcxproj
@@ -30,7 +30,8 @@
     <UseDebugLibraries>true</UseDebugLibraries>
     <PlatformToolset>v120</PlatformToolset>
     <CharacterSet>Unicode</CharacterSet>
-    <UseIntelMKL>No</UseIntelMKL>
+    <UseIntelMKL>Parallel</UseIntelMKL>
+    <UseMpiLibrary>INTELMPI</UseMpiLibrary>
   </PropertyGroup>
   <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'" Label="Configuration">
     <ConfigurationType>DynamicLibrary</ConfigurationType>
@@ -38,7 +39,7 @@
     <PlatformToolset>v120</PlatformToolset>
     <WholeProgramOptimization>true</WholeProgramOptimization>
     <CharacterSet>Unicode</CharacterSet>
-    <UseIntelMKL>No</UseIntelMKL>
+    <UseIntelMKL>Parallel</UseIntelMKL>
     <UseIntelIPP>false</UseIntelIPP>
   </PropertyGroup>
   <Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
@@ -75,13 +76,14 @@
       <OpenMPSupport>true</OpenMPSupport>
       <MinimalRebuild>false</MinimalRebuild>
       <TreatWarningAsError>true</TreatWarningAsError>
+      <AdditionalOptions>/D USE_MKL %(AdditionalOptions)</AdditionalOptions>
     </ClCompile>
     <Link>
       <SubSystem>Windows</SubSystem>
       <GenerateDebugInformation>true</GenerateDebugInformation>
-      <AdditionalDependencies>libacml_mp_dll.lib;%(AdditionalDependencies)</AdditionalDependencies>
-      <AdditionalLibraryDirectories>$(SolutionDir)$(Platform)\$(Configuration)\</AdditionalLibraryDirectories>
-      <DelayLoadDLLs>cublas64_70.dll; cusparse64_70.dll; curand64_70.dll; cudart64_70.dll; libacml_dll.dll; libacml_mp_dll.dll; %(DelayLoadDLLs)</DelayLoadDLLs>
+      <AdditionalDependencies>%(AdditionalDependencies)</AdditionalDependencies>
+      <AdditionalLibraryDirectories>$(SolutionDir)$(Platform)\$(Configuration)\; c:\Program Files (x86)\Intel\Composer XE 2015\mkl\lib\intel64</AdditionalLibraryDirectories>
+      <DelayLoadDLLs>cublas64_70.dll; cusparse64_70.dll; curand64_70.dll; cudart64_70.dll;  %(DelayLoadDLLs)</DelayLoadDLLs>
       <Profile>true</Profile>
     </Link>
     <PostBuildEvent>
@@ -121,7 +123,7 @@
       <EnableParallelCodeGeneration>true</EnableParallelCodeGeneration>
       <FloatingPointExceptions>false</FloatingPointExceptions>
       <TreatWarningAsError>true</TreatWarningAsError>
-      <AdditionalOptions>/d2Zi+ %(AdditionalOptions)</AdditionalOptions>
+      <AdditionalOptions>/d2Zi+ /D USE_MKL %(AdditionalOptions)</AdditionalOptions>
       <RuntimeLibrary>MultiThreadedDLL</RuntimeLibrary>
     </ClCompile>
     <Link>
@@ -129,10 +131,10 @@
       <GenerateDebugInformation>true</GenerateDebugInformation>
       <EnableCOMDATFolding>true</EnableCOMDATFolding>
       <OptimizeReferences>true</OptimizeReferences>
-      <AdditionalLibraryDirectories>$(SolutionDir)$(Platform)\$(Configuration)\</AdditionalLibraryDirectories>
-      <AdditionalDependencies>libacml_mp_dll.lib;%(AdditionalDependencies)</AdditionalDependencies>
+      <AdditionalLibraryDirectories>c:\Program Files (x86)\Intel\Composer XE 2015\mkl\lib\intel64</AdditionalLibraryDirectories>
+      <AdditionalDependencies>%(AdditionalDependencies)</AdditionalDependencies>
       <Profile>true</Profile>
-      <DelayLoadDLLs>cublas64_70.dll; cusparse64_70.dll; curand64_70.dll; cudart64_70.dll; libacml_dll.dll; libacml_mp_dll.dll; %(DelayLoadDLLs)</DelayLoadDLLs>
+      <DelayLoadDLLs>cublas64_70.dll;cusparse64_70.dll;curand64_70.dll;cudart64_70.dll;nvcuda.dll;%(DelayLoadDLLs)</DelayLoadDLLs>
     </Link>
     <PostBuildEvent>
       <Command>xcopy /D /I /Y "$(ACML_PATH)\lib\*.dll" $(OutputPath)</Command>
@@ -197,4 +199,4 @@
   </ItemGroup>
   <Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
   <ImportGroup Label="ExtensionTargets" />
-</Project>
\ No newline at end of file
+</Project>

From 77e782d9d046f94ae7ac11d7bc954d4609c17cfa Mon Sep 17 00:00:00 2001
From: erw <erw@microsoft.com>
Date: Tue, 19 May 2015 13:44:31 -0700
Subject: [PATCH 47/49] Revise .gitignore so the buildinfo.h and buildinfo.h$$
 can be ignored after project dir move

---
 .gitignore | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/.gitignore b/.gitignore
index 72a41c51f..30812ce04 100644
--- a/.gitignore
+++ b/.gitignore
@@ -171,7 +171,8 @@ core
 # =========================
 # prebuild file 
 # =========================
-MachineLearning/cn/buildinfo.h
+MachineLearning/CNTK/buildinfo.h
+MachineLearning/CNTK/buildinfo.h$$
 
 # =========================
 # AutoTest resource 

From 0ff74f0405f7fdbaac29606946fb03f23109a10a Mon Sep 17 00:00:00 2001
From: erw <erw@microsoft.com>
Date: Tue, 19 May 2015 14:05:47 -0700
Subject: [PATCH 48/49] The commits 32391e1..2a7ab60 should not be pushed to
 public (since it enables MKL and MPI) revert them in this commit.

Reverted commit:

8404e9c8de25b39ee79ad9a0bdfaac53006c89b9        "Enable MKL"
64a37301f9ed513bad260a1cba9932796ed2d584        "Enable MPI_SUPPORT"
61c6d59e04185670737142fbda2573cb87ef850d        "add a unit test for CNTKEval"
---
 .gitignore                                    |    5 +-
 CNTKSolution/EvalUnitTest/CNTKEValTest.cpp    |  243 -
 .../EvalUnitTest/EvalUnitTest.vcxproj         |  162 -
 .../EvalUnitTest/EvalUnitTest.vcxproj.filters |    7 -
 DataReader/HTKMLFReader/htkfeatio.h           |   11 -
 MachineLearning/CNTK/CNTK.vcxproj             |   18 +-
 MachineLearning/CNTK/mpi/mpi.h                | 5937 -----------------
 MachineLearning/CNTKEval/CNTKEval.vcxproj     |    8 +-
 MachineLearning/cn/mpi/mpi.h                  | 5937 -----------------
 Math/Math/CNTKMathCUDA.vcxproj                |    2 -
 Math/Math/Math.vcxproj                        |   22 +-
 11 files changed, 23 insertions(+), 12329 deletions(-)
 delete mode 100644 CNTKSolution/EvalUnitTest/CNTKEValTest.cpp
 delete mode 100644 CNTKSolution/EvalUnitTest/EvalUnitTest.vcxproj
 delete mode 100644 CNTKSolution/EvalUnitTest/EvalUnitTest.vcxproj.filters
 delete mode 100644 MachineLearning/CNTK/mpi/mpi.h
 delete mode 100644 MachineLearning/cn/mpi/mpi.h

diff --git a/.gitignore b/.gitignore
index 30812ce04..664cc1b07 100644
--- a/.gitignore
+++ b/.gitignore
@@ -174,7 +174,4 @@ core
 MachineLearning/CNTK/buildinfo.h
 MachineLearning/CNTK/buildinfo.h$$
 
-# =========================
-# AutoTest resource 
-# =========================
-AutoTest/
+
diff --git a/CNTKSolution/EvalUnitTest/CNTKEValTest.cpp b/CNTKSolution/EvalUnitTest/CNTKEValTest.cpp
deleted file mode 100644
index 720bf09bd..000000000
--- a/CNTKSolution/EvalUnitTest/CNTKEValTest.cpp
+++ /dev/null
@@ -1,243 +0,0 @@
-
-
-#include "CppUnitTest.h"
-#include "Eval.h"
-#include "../../DataReader/HTKMLFReader/htkfeatio.h"
-#include <memory>
-#include <string>
-#include <vector>
-
-
-using namespace Microsoft::VisualStudio::CppUnitTestFramework;
-using namespace std;
-using namespace Microsoft::MSR::CNTK;
-using msra::asr::htkfeatreader;
-
-typedef void(*GetEvalProc)(IEvaluateModel<float>** peval);
-
-namespace EvalUnitTest
-{
-    class HTKUtteranceReader    // designed for read one utterance 
-    {
-    public:
-        HTKUtteranceReader() : m_verbosity(0), m_contextWindow(5), m_frameshift(0){
-
-        }
-        void SetContextWindow(size_t windowSize) { m_contextWindow = windowSize; }
-        void SetFrameShift(int shift){ m_frameshift = shift;    }
-        size_t  GetUtteranceData(wstring filename, vector<float>& utterance)
-            // for a D (dim) X N (frame) utterance (specified by filename) and a window size H 
-            // utterance returns a D*(2*H+1) * N vector 
-            // caller don't need to resize utterance 
-        {
-
-            //========================================
-            // Sec. 1 get basic info 
-            //========================================
-            htkfeatreader reader; 
-            htkfeatreader::parsedpath path(filename);
-            
-            string featKind; 
-            size_t featDim; 
-            size_t nframes;
-            unsigned int featPeriod = 0; 
-            reader.getinfo(path, featKind, featDim, featPeriod, nframes);
-
-            //========================================
-            // Sec. 2 resize output vector 
-            //========================================
-            size_t expandedDim = (2 * m_contextWindow + 1) * featDim;       // dimension after contex expanding 
-            size_t totalDim = expandedDim * nframes;                        // dimension of the vector we want to feed to CNTK eval
-            utterance.resize(totalDim, 0.0f);
-            //========================================
-            // Sec. 3 get the feature matrix 
-            //========================================
-            vector<vector<float> > featMatrix;
-            featMatrix.resize(nframes);
-            for (size_t n = 0; n < nframes; n++)
-            {
-                reader.read(featMatrix[n]);
-            }
-            //========================================
-            // Sec. 4 context expansion
-            //========================================
-            if (m_contextWindow > 0)
-            {
-                vector<float>  expandedfeat;
-                expandedfeat.resize(expandedDim);
-
-                for (size_t n = 0; n < nframes; n++)
-                {
-                    
-                    size_t despos = 0; 
-                    for (size_t ileft = m_contextWindow-1; ileft >=0; ileft--, despos ++ )
-                    {
-                        size_t srcpos = max(n - ileft, 0);                         
-                        copy(featMatrix[srcpos].begin(), featMatrix[srcpos].end(), expandedfeat.begin() + featDim *despos);
-                    }
-                    for (size_t iRight = 1; iRight < m_contextWindow; iRight++, despos++)
-                    {
-                        size_t srcpos = min(n + iRight, nframes);
-                        copy(featMatrix[srcpos].begin(), featMatrix[srcpos].end(), expandedfeat.begin() + featDim *despos); 
-                    }
-                    copy(expandedfeat.begin(), expandedfeat.end(), utterance.begin() + expandedDim*n);
-                }
-            }
-            else
-            {
-                size_t idx = 0;
-                for (auto v : featMatrix)
-                {
-                    copy(v.begin(), v.end(), utterance.begin() + expandedDim*idx);
-                    idx++;
-                }
-            }
-
-
-
-            //========================================
-            // Sec. 5 frame shift 
-            //========================================
-            if (m_frameshift > 0)
-            {
-                assert(m_frameshift < nframes);  // TODO: throw an exception
-                /*
-                for (size_t f = m_frameshift; f < nframes; f++)
-                {
-                    copy(featMatrix[f].begin(), featMatrix[f].end(), utterance.begin() + (f-m_frameshift)*expandedDim);
-                }
-                for (size_t r = 0; r < m_frameshift; r++)
-                {
-                    copy(featMatrix[nframes - 1].begin(), featMatrix[nframes - 1].end(), utterance.begin()+(nframes-m_frameshift+r)*expandedDim );
-                }*/
-                for (size_t ipos = nframes - m_frameshift -1; ipos >= 0; ipos++)
-                {
-                    auto src = utterance.begin() + ipos * expandedDim;
-                    auto des = src + (m_frameshift)*expandedDim;
-                    copy(src, src + expandedDim, des);
-                }
-
-                auto src = utterance.begin() + m_frameshift*expandedDim;
-                for (size_t ipos = 0; ipos < m_frameshift; ipos++)
-                {
-                    auto des = utterance.begin() + ipos * expandedDim;
-                    copy(src, src + expandedDim, des);
-                }
-            }
-            return nframes;
-
-        }
-
-    private: 
-        size_t m_contextWindow;         // =5 means 5:1:5 TODO support asymmetric context window
-        size_t m_verbosity; 
-        short  m_frameshift;            // f>0  means x[0..n-1] -> [ x[f..n-1], x[n-1], ... ] 
-                                        // f<0  means x[0..n-1] -> [ x[0], x[0],... x[f..n-1] ] 
-                                        // frameshift is applied after context windows expansion 
-    };
-
-
-
-    TEST_CLASS(CNTKEvalUnitTest)
-    {
-    private:
-        bool LoadEvalutor()
-        {
-            try
-            {
-                Plugin plug;
-                GetEvalProc p_Processor = (GetEvalProc)plug.Load(m_strEvalModule, m_strGetEvalProcessor);
-                IEvaluateModel<float>* pEval = nullptr;
-                p_Processor(&pEval);
-                m_pEval.reset(pEval);
-            }
-            catch (std::exception& e)
-            {
-                printf("ERROR: %s\n", e.what());
-                Assert::Fail(L"Load Module failed");
-            }
-            return true;
-        }
-
-    public:
-        TEST_CLASS_INITIALIZE(ConfigEvalUnitTest)
-        {
-
-        }
-
-        TEST_METHOD(LoadModule)
-        {
-            Assert::IsTrue(LoadEvalutor());
-        }
-
-        TEST_METHOD(RNNModelTest)
-        {
-            Assert::IsTrue(LoadEvalutor());
-            m_pEval->Init("deviceID=-1");
-            m_pEval->LoadModel(m_strRNNModel);
-
-            //========================================
-            // Sec. 1 query node dimension
-            //========================================
-            map<wstring, size_t> inputDimensions;
-            m_pEval->GetNodeDimensions(inputDimensions, nodeInput);
-            map<wstring, size_t> outputDimensions; 
-            m_pEval->GetNodeDimensions(outputDimensions, nodeOutput);
-
-            //========================================
-            // Sec. 2 load in feature files and expected output files 
-            //========================================            
-            HTKUtteranceReader reader; 
-            reader.SetFrameShift(0);
-            reader.SetContextWindow(0);
-            vector<float> utterData; 
-            size_t nframe=reader.GetUtteranceData(m_strRNNModelInputOutputPairs.first, utterData);
-            vector<float> expectedRes;
-            size_t nframeLLR = reader.GetUtteranceData(m_strRNNModelInputOutputPairs.second, expectedRes);
-            Assert::AreEqual(nframe, nframeLLR, L"ERROR: number of input feature vectors mismatched with the number of output vectors");
-
-            //========================================
-            // Sec. 3 setup inputs and outputs 
-            //========================================
-            Assert::IsTrue(inputDimensions.find(L"features") != inputDimensions.end());
-            Assert::IsTrue(outputDimensions.find(L"ScaledLogLikelihood") != outputDimensions.end());
-
-            map<wstring, vector<float>* > inputs; 
-            inputs[L"features"] = &utterData;
-            map<wstring, vector<float>* > outputs; 
-            size_t outputDim = nframe * outputDimensions[L"ScaledLogLikelihood"];
-            vector<float> outputData(outputDim,0.0f);
-            outputs[L"ScaledLogLikelihood"] = &outputData;
-            m_pEval->Evaluate(inputs, outputs);
-
-            //========================================
-            // Sec. 4 CompareResults 
-            //========================================
-            wstring msg = msra::strfun::wstrprintf(L"Output dimensions (%d vs %d) do not match", outputs.size(), expectedRes.size());
-            Assert::AreEqual(expectedRes.size(), outputs[L"ScaledLogLikelihood"]->size(), L"Output dimension does not match");
-            
-            for (size_t i = 0; i < expectedRes.size(); i++)
-            {
-                Assert::AreEqual(expectedRes[i], (*outputs[L"ScaledLogLikelihood"])[i], 0.01f);
-            }
-
-        }
-
-
-    private:
-        shared_ptr<IEvaluateModel<float>>   m_pEval;
-        static const wstring    m_strEvalModule;
-        static const  string    m_strGetEvalProcessor;
-        static const wstring    m_strRNNModel; 
-        static const pair<wstring, wstring>   m_strRNNModelInputOutputPairs;
-
-
-    };
-
-    const wstring  CNTKEvalUnitTest::m_strEvalModule = L"CNTKEval";           // the module (.dll) name 
-    const  string  CNTKEvalUnitTest::m_strGetEvalProcessor = "GetEvalF";     // which function to get eval 
-    const wstring  CNTKEvalUnitTest::m_strRNNModel = L"..\\..\\..\\AutoTest\\resources\\rnn.model.40";
-    const pair<wstring, wstring>  CNTKEvalUnitTest::m_strRNNModelInputOutputPairs = make_pair(L"..\\..\\..\\AutoTest\\resources\\LFB87dim.mfc", L"..\\..\\..\\AutoTest\\resources\\LFB87dim.pos");
-    
-
-}
\ No newline at end of file
diff --git a/CNTKSolution/EvalUnitTest/EvalUnitTest.vcxproj b/CNTKSolution/EvalUnitTest/EvalUnitTest.vcxproj
deleted file mode 100644
index 83da932f1..000000000
--- a/CNTKSolution/EvalUnitTest/EvalUnitTest.vcxproj
+++ /dev/null
@@ -1,162 +0,0 @@
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-      <Platform>Win32</Platform>
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-      <Configuration>Debug</Configuration>
-      <Platform>x64</Platform>
-    </ProjectConfiguration>
-    <ProjectConfiguration Include="Release|Win32">
-      <Configuration>Release</Configuration>
-      <Platform>Win32</Platform>
-    </ProjectConfiguration>
-    <ProjectConfiguration Include="Release|x64">
-      <Configuration>Release</Configuration>
-      <Platform>x64</Platform>
-    </ProjectConfiguration>
-  </ItemGroup>
-  <PropertyGroup Label="Globals">
-    <ProjectGuid>{4CBCD242-B40B-4A32-9648-DF9CD8CFFC8E}</ProjectGuid>
-    <Keyword>Win32Proj</Keyword>
-    <RootNamespace>EvalUnitTest</RootNamespace>
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-      <UseFullPaths>true</UseFullPaths>
-      <AdditionalOptions>/D  _CRT_SECURE_NO_WARNINGS %(AdditionalOptions)</AdditionalOptions>
-    </ClCompile>
-    <Link>
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-      <AdditionalIncludeDirectories>..\..\common\include;..\..\math\math;$(VCInstallDir)UnitTest\include;%(AdditionalIncludeDirectories)</AdditionalIncludeDirectories>
-      <PreprocessorDefinitions>WIN32;NDEBUG;%(PreprocessorDefinitions)</PreprocessorDefinitions>
-      <UseFullPaths>true</UseFullPaths>
-      <AdditionalOptions>/D  _CRT_SECURE_NO_WARNINGS %(AdditionalOptions)</AdditionalOptions>
-    </ClCompile>
-    <Link>
-      <SubSystem>Windows</SubSystem>
-      <GenerateDebugInformation>true</GenerateDebugInformation>
-      <EnableCOMDATFolding>true</EnableCOMDATFolding>
-      <OptimizeReferences>true</OptimizeReferences>
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-  </ItemDefinitionGroup>
-  <ItemGroup>
-    <ClCompile Include="..\..\Common\fileutil.cpp" />
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\ No newline at end of file
diff --git a/CNTKSolution/EvalUnitTest/EvalUnitTest.vcxproj.filters b/CNTKSolution/EvalUnitTest/EvalUnitTest.vcxproj.filters
deleted file mode 100644
index ab38f4ab4..000000000
--- a/CNTKSolution/EvalUnitTest/EvalUnitTest.vcxproj.filters
+++ /dev/null
@@ -1,7 +0,0 @@
-<?xml version="1.0" encoding="utf-8"?>
-<Project ToolsVersion="4.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
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-    <ClCompile Include="CNTKEValTest.cpp" />
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\ No newline at end of file
diff --git a/DataReader/HTKMLFReader/htkfeatio.h b/DataReader/HTKMLFReader/htkfeatio.h
index 917451e6e..4d03525a3 100644
--- a/DataReader/HTKMLFReader/htkfeatio.h
+++ b/DataReader/HTKMLFReader/htkfeatio.h
@@ -516,17 +516,6 @@ public:
         featdim = this->featdim;
         featperiod = this->featperiod;
     }
-    
-    void getinfo (const parsedpath & ppath, string & featkind, size_t & featdim, unsigned int & featperiod, size_t& nframe)
-    {
-        open (ppath);
-        featkind = this->featkind;
-        featdim = this->featdim;
-        featperiod = this->featperiod;
-        nframe = this->numframes;
-    }
-
-
 
     // called to add energy as we read
     void AddEnergy(size_t energyElements)
diff --git a/MachineLearning/CNTK/CNTK.vcxproj b/MachineLearning/CNTK/CNTK.vcxproj
index cbd6924e0..bb76f801c 100644
--- a/MachineLearning/CNTK/CNTK.vcxproj
+++ b/MachineLearning/CNTK/CNTK.vcxproj
@@ -72,15 +72,15 @@
       <SDLCheck>true</SDLCheck>
       <OpenMPSupport>true</OpenMPSupport>
       <TreatWarningAsError>true</TreatWarningAsError>
-      <AdditionalOptions>/bigobj /D MPI_SUPPORT %(AdditionalOptions)</AdditionalOptions>
-      <AdditionalIncludeDirectories>"c:\Program Files\NVIDIA Corporation\GDK\gdk_win7_amd64_release\nvml\include";$(ProjectDir)\mpi</AdditionalIncludeDirectories>
+      <AdditionalOptions>/bigobj %(AdditionalOptions)</AdditionalOptions>
+      <AdditionalIncludeDirectories>"c:\Program Files\NVIDIA Corporation\GDK\gdk_win7_amd64_release\nvml\include"</AdditionalIncludeDirectories>
     </ClCompile>
     <Link>
       <SubSystem>Console</SubSystem>
       <GenerateDebugInformation>true</GenerateDebugInformation>
       <AdditionalDependencies>CNTKMath.lib; nvml.lib; kernel32.lib; user32.lib; shell32.lib; %(AdditionalDependencies)</AdditionalDependencies>
-      <AdditionalLibraryDirectories>$(ProjectDir)/mpi/$(Platform); "c:\Program Files\NVIDIA Corporation\GDK\gdk_win7_amd64_release\nvml\lib" </AdditionalLibraryDirectories>
-      <DelayLoadDLLs>CNTKMath.dll;nvml.dll;nvcuda.dll; cudart64_70.dll</DelayLoadDLLs>
+      <AdditionalLibraryDirectories>"c:\Program Files\NVIDIA Corporation\GDK\gdk_win7_amd64_release\nvml\lib"</AdditionalLibraryDirectories>
+      <DelayLoadDLLs>CNTKMath.dll; nvml.dll; cudart64_70.dll</DelayLoadDLLs>
     </Link>
     <PostBuildEvent>
       <Command>xcopy /I /D /Y "%ProgramW6432%\NVIDIA Corporation\NVSMI\nvml*.dll" $(TargetDir)</Command>
@@ -110,9 +110,9 @@
       <PreprocessorDefinitions>WIN32;NDEBUG;_CONSOLE;%(PreprocessorDefinitions)</PreprocessorDefinitions>
       <SDLCheck>true</SDLCheck>
       <FavorSizeOrSpeed>Speed</FavorSizeOrSpeed>
-      <AdditionalOptions>/d2Zi+ /D MPI_SUPPORT %(AdditionalOptions)</AdditionalOptions>
+      <AdditionalOptions>/d2Zi+ %(AdditionalOptions)</AdditionalOptions>
       <TreatWarningAsError>true</TreatWarningAsError>
-      <AdditionalIncludeDirectories>"c:\Program Files\NVIDIA Corporation\GDK\gdk_win7_amd64_release\nvml\include"; $(ProjectDir)\mpi</AdditionalIncludeDirectories>
+      <AdditionalIncludeDirectories>"c:\Program Files\NVIDIA Corporation\GDK\gdk_win7_amd64_release\nvml\include"</AdditionalIncludeDirectories>
     </ClCompile>
     <Link>
       <SubSystem>Console</SubSystem>
@@ -121,8 +121,8 @@
       <OptimizeReferences>true</OptimizeReferences>
       <AdditionalDependencies>CNTKMath.lib; nvml.lib; kernel32.lib; user32.lib; shell32.lib; %(AdditionalDependencies)</AdditionalDependencies>
       <Profile>true</Profile>
-      <DelayLoadDLLs>CNTKMath.dll;nvml.dll;CUDart64_70.dll</DelayLoadDLLs>
-      <AdditionalLibraryDirectories>"c:\Program Files\NVIDIA Corporation\GDK\gdk_win7_amd64_release\nvml\lib"; $(ProjectDir)/mpi/$(Platform)</AdditionalLibraryDirectories>
+      <DelayLoadDLLs>CNTKMath.dll; nvml.dll; cudart64_70.dll</DelayLoadDLLs>
+      <AdditionalLibraryDirectories>"c:\Program Files\NVIDIA Corporation\GDK\gdk_win7_amd64_release\nvml\lib"</AdditionalLibraryDirectories>
     </Link>
     <PostBuildEvent>
       <Command>xcopy /I /D /Y "%ProgramW6432%\NVIDIA Corporation\NVSMI\nvml*.dll" $(TargetDir)</Command>
@@ -213,4 +213,4 @@
   </ItemGroup>
   <Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
   <ImportGroup Label="ExtensionTargets" />
-</Project>
+</Project>
\ No newline at end of file
diff --git a/MachineLearning/CNTK/mpi/mpi.h b/MachineLearning/CNTK/mpi/mpi.h
deleted file mode 100644
index bd61200e7..000000000
--- a/MachineLearning/CNTK/mpi/mpi.h
+++ /dev/null
@@ -1,5937 +0,0 @@
-/*
- *  (C) 2001 by Argonne National Laboratory.
- *  (C) 2009 by Microsoft Corporation.
- *      See COPYRIGHT in the SDK directory.
- */
-
-#ifndef MPI_INCLUDED
-#define MPI_INCLUDED
-
-#if defined(__cplusplus)
-extern "C" {
-#endif
-
-
-#ifndef MSMPI_VER
-#define MSMPI_VER 0x100
-#endif
-
-
-/*---------------------------------------------------------------------------*/
-/* SAL ANNOTATIONS                                                           */
-/*---------------------------------------------------------------------------*/
-/*
- * Define SAL annotations if they aren't defined yet.  Note that if we define
- * them, we undefine them at the end of this file so that future inclusion of
- * sal.h doesn't cause errors.
- */
-#ifndef _In_
-#define MSMPI_DEFINED_SAL
-#define _In_
-#define _In_z_
-#define _In_opt_
-#define _In_count_( x )
-#define _In_bytecount_( x )
-#define _In_opt_count_( x )
-#define _Out_
-#define _Out_cap_( x )
-#define _Out_cap_post_count_( x, y )
-#define _Out_bytecap_( x )
-#define _Out_z_cap_( x )
-#define _Out_z_cap_post_count_( x, y )
-#define _Out_cap_post_part_( x, y )
-#define _Out_opt_
-#define _Out_opt_cap_( x )
-#define _Post_z_
-#define _Inout_
-#define _Inout_count_( x )
-#endif
-
-/*---------------------------------------------------------------------------*/
-/* MSMPI Calling convention                                                  */
-/*---------------------------------------------------------------------------*/
-
-#define MPIAPI __stdcall
-
-
-/*---------------------------------------------------------------------------*/
-/* MPI ERROR CLASS                                                           */
-/*---------------------------------------------------------------------------*/
-
-#define MPI_SUCCESS          0      /* Successful return code */
-
-#define MPI_ERR_BUFFER       1      /* Invalid buffer pointer */
-#define MPI_ERR_COUNT        2      /* Invalid count argument */
-#define MPI_ERR_TYPE         3      /* Invalid datatype argument */
-#define MPI_ERR_TAG          4      /* Invalid tag argument */
-#define MPI_ERR_COMM         5      /* Invalid communicator */
-#define MPI_ERR_RANK         6      /* Invalid rank */
-#define MPI_ERR_ROOT         7      /* Invalid root */
-#define MPI_ERR_GROUP        8      /* Invalid group */
-#define MPI_ERR_OP           9      /* Invalid operation */
-#define MPI_ERR_TOPOLOGY    10      /* Invalid topology */
-#define MPI_ERR_DIMS        11      /* Invalid dimension argument */
-#define MPI_ERR_ARG         12      /* Invalid argument */
-#define MPI_ERR_UNKNOWN     13      /* Unknown error */
-#define MPI_ERR_TRUNCATE    14      /* Message truncated on receive */
-#define MPI_ERR_OTHER       15      /* Other error; use Error_string */
-#define MPI_ERR_INTERN      16      /* Internal error code */
-#define MPI_ERR_IN_STATUS   17      /* Error code is in status */
-#define MPI_ERR_PENDING     18      /* Pending request */
-#define MPI_ERR_REQUEST     19      /* Invalid request (handle) */
-#define MPI_ERR_ACCESS      20      /* Premission denied */
-#define MPI_ERR_AMODE       21      /* Error related to amode passed to MPI_File_open */
-#define MPI_ERR_BAD_FILE    22      /* Invalid file name (e.g., path name too long) */
-#define MPI_ERR_CONVERSION  23      /* Error in user data conversion function */
-#define MPI_ERR_DUP_DATAREP 24      /* Data representation identifier already registered */
-#define MPI_ERR_FILE_EXISTS 25      /* File exists */
-#define MPI_ERR_FILE_IN_USE 26      /* File operation could not be completed, file in use */
-#define MPI_ERR_FILE        27      /* Invalid file handle */
-#define MPI_ERR_INFO        28      /* Invalid info argument */
-#define MPI_ERR_INFO_KEY    29      /* Key longer than MPI_MAX_INFO_KEY */
-#define MPI_ERR_INFO_VALUE  30      /* Value longer than MPI_MAX_INFO_VAL */
-#define MPI_ERR_INFO_NOKEY  31      /* Invalid key passed to MPI_Info_delete */
-#define MPI_ERR_IO          32      /* Other I/O error */
-#define MPI_ERR_NAME        33      /* Invalid service name in MPI_Lookup_name */
-#define MPI_ERR_NO_MEM      34      /* Alloc_mem could not allocate memory */
-#define MPI_ERR_NOT_SAME    35      /* Collective argument/sequence not the same on all processes */
-#define MPI_ERR_NO_SPACE    36      /* Not enough space */
-#define MPI_ERR_NO_SUCH_FILE 37     /* File does not exist */
-#define MPI_ERR_PORT        38      /* Invalid port name in MPI_comm_connect*/
-#define MPI_ERR_QUOTA       39      /* Quota exceeded */
-#define MPI_ERR_READ_ONLY   40      /* Read-only file or file system */
-#define MPI_ERR_SERVICE     41      /* Invalid service name in MPI_Unpublish_name */
-#define MPI_ERR_SPAWN       42      /* Error in spawning processes */
-#define MPI_ERR_UNSUPPORTED_DATAREP   43  /* Unsupported dararep in MPI_File_set_view */
-#define MPI_ERR_UNSUPPORTED_OPERATION 44  /* Unsupported operation on file */
-#define MPI_ERR_WIN         45      /* Invalid win argument */
-#define MPI_ERR_BASE        46      /* Invalid base passed to MPI_Free_mem */
-#define MPI_ERR_LOCKTYPE    47      /* Invalid locktype argument */
-#define MPI_ERR_KEYVAL      48      /* Invalid keyval  */
-#define MPI_ERR_RMA_CONFLICT 49     /* Conflicting accesses to window */
-#define MPI_ERR_RMA_SYNC    50      /* Wrong synchronization of RMA calls */
-#define MPI_ERR_SIZE        51      /* Invalid size argument */
-#define MPI_ERR_DISP        52      /* Invalid disp argument */
-#define MPI_ERR_ASSERT      53      /* Invalid assert argument */
-
-#define MPI_ERR_LASTCODE    0x3fffffff    /* Last valid error code for a predefined error class */
-
-#define MPICH_ERR_LAST_CLASS 53
-
-
-/*---------------------------------------------------------------------------*/
-/* MPI Basic integer types                                                   */
-/*---------------------------------------------------------------------------*/
-
-/* Address size integer */
-#ifdef _WIN64
-typedef __int64 MPI_Aint;
-#else
-typedef int MPI_Aint;
-#endif
-
-/* Fortran INTEGER */
-typedef int MPI_Fint;
-
-/* File offset */
-typedef __int64 MPI_Offset;
-
-
-/*---------------------------------------------------------------------------*/
-/* MPI_Datatype                                                              */
-/*---------------------------------------------------------------------------*/
-
-typedef int MPI_Datatype;
-#define MPI_DATATYPE_NULL           ((MPI_Datatype)0x0c000000)
-
-#define MPI_CHAR                    ((MPI_Datatype)0x4c000101)
-#define MPI_UNSIGNED_CHAR           ((MPI_Datatype)0x4c000102)
-#define MPI_SHORT                   ((MPI_Datatype)0x4c000203)
-#define MPI_UNSIGNED_SHORT          ((MPI_Datatype)0x4c000204)
-#define MPI_INT                     ((MPI_Datatype)0x4c000405)
-#define MPI_UNSIGNED                ((MPI_Datatype)0x4c000406)
-#define MPI_LONG                    ((MPI_Datatype)0x4c000407)
-#define MPI_UNSIGNED_LONG           ((MPI_Datatype)0x4c000408)
-#define MPI_LONG_LONG_INT           ((MPI_Datatype)0x4c000809)
-#define MPI_LONG_LONG               MPI_LONG_LONG_INT
-#define MPI_FLOAT                   ((MPI_Datatype)0x4c00040a)
-#define MPI_DOUBLE                  ((MPI_Datatype)0x4c00080b)
-#define MPI_LONG_DOUBLE             ((MPI_Datatype)0x4c00080c)
-#define MPI_BYTE                    ((MPI_Datatype)0x4c00010d)
-#define MPI_WCHAR                   ((MPI_Datatype)0x4c00020e)
-
-#define MPI_PACKED                  ((MPI_Datatype)0x4c00010f)
-#define MPI_LB                      ((MPI_Datatype)0x4c000010)
-#define MPI_UB                      ((MPI_Datatype)0x4c000011)
-
-#define MPI_C_COMPLEX               ((MPI_Datatype)0x4c000812)
-#define MPI_C_FLOAT_COMPLEX         ((MPI_Datatype)0x4c000813)
-#define MPI_C_DOUBLE_COMPLEX        ((MPI_Datatype)0x4c001614)
-#define MPI_C_LONG_DOUBLE_COMPLEX   ((MPI_Datatype)0x4c001615)
-
-#define MPI_2INT                    ((MPI_Datatype)0x4c000816)
-#define MPI_C_BOOL                  ((MPI_Datatype)0x4c000117)
-#define MPI_SIGNED_CHAR             ((MPI_Datatype)0x4c000118)
-#define MPI_UNSIGNED_LONG_LONG      ((MPI_Datatype)0x4c000819)
-
-/* Fortran types */
-#define MPI_CHARACTER               ((MPI_Datatype)0x4c00011a)
-#define MPI_INTEGER                 ((MPI_Datatype)0x4c00041b)
-#define MPI_REAL                    ((MPI_Datatype)0x4c00041c)
-#define MPI_LOGICAL                 ((MPI_Datatype)0x4c00041d)
-#define MPI_COMPLEX                 ((MPI_Datatype)0x4c00081e)
-#define MPI_DOUBLE_PRECISION        ((MPI_Datatype)0x4c00081f)
-#define MPI_2INTEGER                ((MPI_Datatype)0x4c000820)
-#define MPI_2REAL                   ((MPI_Datatype)0x4c000821)
-#define MPI_DOUBLE_COMPLEX          ((MPI_Datatype)0x4c001022)
-#define MPI_2DOUBLE_PRECISION       ((MPI_Datatype)0x4c001023)
-#define MPI_2COMPLEX                ((MPI_Datatype)0x4c001024)
-#define MPI_2DOUBLE_COMPLEX         ((MPI_Datatype)0x4c002025)
-
-/* Size-specific types (see MPI 2.2, 16.2.5) */
-#define MPI_REAL2                   MPI_DATATYPE_NULL
-#define MPI_REAL4                   ((MPI_Datatype)0x4c000427)
-#define MPI_COMPLEX8                ((MPI_Datatype)0x4c000828)
-#define MPI_REAL8                   ((MPI_Datatype)0x4c000829)
-#define MPI_COMPLEX16               ((MPI_Datatype)0x4c00102a)
-#define MPI_REAL16                  MPI_DATATYPE_NULL
-#define MPI_COMPLEX32               MPI_DATATYPE_NULL
-#define MPI_INTEGER1                ((MPI_Datatype)0x4c00012d)
-#define MPI_COMPLEX4                MPI_DATATYPE_NULL
-#define MPI_INTEGER2                ((MPI_Datatype)0x4c00022f)
-#define MPI_INTEGER4                ((MPI_Datatype)0x4c000430)
-#define MPI_INTEGER8                ((MPI_Datatype)0x4c000831)
-#define MPI_INTEGER16               MPI_DATATYPE_NULL
-#define MPI_INT8_T                  ((MPI_Datatype)0x4c000133)
-#define MPI_INT16_T                 ((MPI_Datatype)0x4c000234)
-#define MPI_INT32_T                 ((MPI_Datatype)0x4c000435)
-#define MPI_INT64_T                 ((MPI_Datatype)0x4c000836)
-#define MPI_UINT8_T                 ((MPI_Datatype)0x4c000137)
-#define MPI_UINT16_T                ((MPI_Datatype)0x4c000238)
-#define MPI_UINT32_T                ((MPI_Datatype)0x4c000439)
-#define MPI_UINT64_T                ((MPI_Datatype)0x4c00083a)
-
-#ifdef _WIN64
-#define MPI_AINT                    ((MPI_Datatype)0x4c00083b)
-#else
-#define MPI_AINT                    ((MPI_Datatype)0x4c00043b)
-#endif
-#define MPI_OFFSET                  ((MPI_Datatype)0x4c00083c)
-
-/*
- * The layouts for the types MPI_DOUBLE_INT etc. are
- *
- *      struct { double a; int b; }
- */
-#define MPI_FLOAT_INT               ((MPI_Datatype)0x8c000000)
-#define MPI_DOUBLE_INT              ((MPI_Datatype)0x8c000001)
-#define MPI_LONG_INT                ((MPI_Datatype)0x8c000002)
-#define MPI_SHORT_INT               ((MPI_Datatype)0x8c000003)
-#define MPI_LONG_DOUBLE_INT         ((MPI_Datatype)0x8c000004)
-
-
-/*---------------------------------------------------------------------------*/
-/* MPI_Comm                                                                  */
-/*---------------------------------------------------------------------------*/
-
-typedef int MPI_Comm;
-#define MPI_COMM_NULL  ((MPI_Comm)0x04000000)
-
-#define MPI_COMM_WORLD ((MPI_Comm)0x44000000)
-#define MPI_COMM_SELF  ((MPI_Comm)0x44000001)
-
-
-/*---------------------------------------------------------------------------*/
-/* MPI_Win                                                                   */
-/*---------------------------------------------------------------------------*/
-
-typedef int MPI_Win;
-#define MPI_WIN_NULL ((MPI_Win)0x20000000)
-
-
-/*---------------------------------------------------------------------------*/
-/* MPI_File                                                                  */
-/*---------------------------------------------------------------------------*/
-
-typedef struct ADIOI_FileD* MPI_File;
-#define MPI_FILE_NULL ((MPI_File)0)
-
-
-/*---------------------------------------------------------------------------*/
-/* MPI_Op                                                                    */
-/*---------------------------------------------------------------------------*/
-
-typedef int MPI_Op;
-#define MPI_OP_NULL ((MPI_Op)0x18000000)
-
-#define MPI_MAX     ((MPI_Op)0x58000001)
-#define MPI_MIN     ((MPI_Op)0x58000002)
-#define MPI_SUM     ((MPI_Op)0x58000003)
-#define MPI_PROD    ((MPI_Op)0x58000004)
-#define MPI_LAND    ((MPI_Op)0x58000005)
-#define MPI_BAND    ((MPI_Op)0x58000006)
-#define MPI_LOR     ((MPI_Op)0x58000007)
-#define MPI_BOR     ((MPI_Op)0x58000008)
-#define MPI_LXOR    ((MPI_Op)0x58000009)
-#define MPI_BXOR    ((MPI_Op)0x5800000a)
-#define MPI_MINLOC  ((MPI_Op)0x5800000b)
-#define MPI_MAXLOC  ((MPI_Op)0x5800000c)
-#define MPI_REPLACE ((MPI_Op)0x5800000d)
-
-
-/*---------------------------------------------------------------------------*/
-/* MPI_Info                                                                  */
-/*---------------------------------------------------------------------------*/
-
-typedef int MPI_Info;
-#define MPI_INFO_NULL         ((MPI_Info)0x1c000000)
-
-
-/*---------------------------------------------------------------------------*/
-/* MPI_Request                                                               */
-/*---------------------------------------------------------------------------*/
-
-typedef int MPI_Request;
-#define MPI_REQUEST_NULL ((MPI_Request)0x2c000000)
-
-
-/*---------------------------------------------------------------------------*/
-/* MPI_Group                                                                 */
-/*---------------------------------------------------------------------------*/
-
-typedef int MPI_Group;
-#define MPI_GROUP_NULL  ((MPI_Group)0x08000000)
-
-#define MPI_GROUP_EMPTY ((MPI_Group)0x48000000)
-
-
-/*---------------------------------------------------------------------------*/
-/* MPI_Errhandler                                                            */
-/*---------------------------------------------------------------------------*/
-
-typedef int MPI_Errhandler;
-#define MPI_ERRHANDLER_NULL  ((MPI_Errhandler)0x14000000)
-
-#define MPI_ERRORS_ARE_FATAL ((MPI_Errhandler)0x54000000)
-#define MPI_ERRORS_RETURN    ((MPI_Errhandler)0x54000001)
-
-/*---------------------------------------------------------------------------*/
-/* MPI_Status                                                                */
-/*---------------------------------------------------------------------------*/
-
-typedef struct MPI_Status
-{
-    int count;
-    int cancelled;
-    int MPI_SOURCE;
-    int MPI_TAG;
-    int MPI_ERROR;
-
-} MPI_Status;
-
-#define MPI_STATUS_IGNORE ((MPI_Status*)(MPI_Aint)1)
-#define MPI_STATUSES_IGNORE ((MPI_Status*)(MPI_Aint)1)
-
-
-/*---------------------------------------------------------------------------*/
-/* MISC CONSTANTS                                                            */
-/*---------------------------------------------------------------------------*/
-
-/* Used in: Count, Index, Rank, Color, Toplogy, Precision, Exponent range  */
-#define MPI_UNDEFINED   (-32766)
-
-/* Used in: Rank */
-#define MPI_PROC_NULL   (-1)
-#define MPI_ANY_SOURCE  (-2)
-#define MPI_ROOT        (-3)
-
-/* Used in: Tag */
-#define MPI_ANY_TAG     (-1)
-
-/* Used for: Buffer address */
-#define MPI_BOTTOM      ((void*)0)
-
-
-/*---------------------------------------------------------------------------*/
-/* Chapter 3: Point-to-Point Communication                                   */
-/*---------------------------------------------------------------------------*/
-
-/*---------------------------------------------*/
-/* Section 3.2: Blocking Communication         */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Send(
-    _In_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Send(
-    _In_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm
-    );
-
-int
-MPIAPI
-MPI_Recv(
-    _Out_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int source,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_Recv(
-    _Out_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int source,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_Get_count(
-    _In_ MPI_Status* status,
-    MPI_Datatype datatype,
-    _Out_ int* count
-    );
-int
-MPIAPI
-PMPI_Get_count(
-    _In_ MPI_Status* status,
-    MPI_Datatype datatype,
-    _Out_ int* count
-    );
-
-
-/*---------------------------------------------*/
-/* Section 3.4: Communication Modes            */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Bsend(
-    _In_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Bsend(
-    _In_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm
-    );
-
-int
-MPIAPI
-MPI_Ssend(
-    _In_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Ssend(
-    _In_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm
-    );
-
-int
-MPIAPI
-MPI_Rsend(
-    _In_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Rsend(
-    _In_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm
-    );
-
-
-/*---------------------------------------------*/
-/* Section 3.6: Buffer Allocation              */
-/*---------------------------------------------*/
-
-/* Upper bound on bsend overhead for each message */
-#define MSMPI_BSEND_OVERHEAD_V1   95
-#define MSMPI_BSEND_OVERHEAD_V2   MSMPI_BSEND_OVERHEAD_V1
-
-#if MSMPI_VER > 0x300
-#  define MPI_BSEND_OVERHEAD  MSMPI_Get_bsend_overhead()
-#else
-#  define MPI_BSEND_OVERHEAD  MSMPI_BSEND_OVERHEAD_V1
-#endif
-
-int
-MPIAPI
-MPI_Buffer_attach(
-    _In_ void* buffer,
-    int size
-    );
-int
-MPIAPI
-PMPI_Buffer_attach(
-    _In_ void* buffer,
-    int size
-    );
-
-int
-MPIAPI
-MPI_Buffer_detach(
-    _Out_ void* buffer_addr,
-    _Out_ int* size
-    );
-int
-MPIAPI
-PMPI_Buffer_detach(
-    _Out_ void* buffer_addr,
-    _Out_ int* size
-    );
-
-
-/*---------------------------------------------*/
-/* Section 3.7: Nonblocking Communication      */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Isend(
-    _In_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_Isend(
-    _In_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-
-int
-MPIAPI
-MPI_Ibsend(
-    _In_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_Ibsend(
-    _In_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-
-int
-MPIAPI
-MPI_Issend(
-    _In_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_Issend(
-    _In_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-
-int
-MPIAPI
-MPI_Irsend(
-    _In_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_Irsend(
-    _In_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-
-int
-MPIAPI
-MPI_Irecv(
-    _Out_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int source,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_Irecv(
-    _Out_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int source,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-
-
-/*---------------------------------------------*/
-/* Section 3.7.3: Communication Completion     */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Wait(
-    _Inout_ MPI_Request* request,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_Wait(
-    _Inout_ MPI_Request* request,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_Test(
-    _Inout_ MPI_Request* request,
-    _Out_ int* flag,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_Test(
-    _Inout_ MPI_Request* request,
-    _Out_ int* flag,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_Request_free(
-    _Inout_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_Request_free(
-    _Inout_ MPI_Request* request
-    );
-
-
-/*---------------------------------------------*/
-/* Section 3.7.5: Multiple Completions         */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Waitany(
-    int count,
-    _Inout_count_(count) MPI_Request* array_of_requests,
-    _Out_ int* index,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_Waitany(
-    int count,
-    _Inout_count_(count) MPI_Request* array_of_requests,
-    _Out_ int* index,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_Testany(
-    int count,
-    _Inout_count_(count) MPI_Request* array_of_requests,
-    _Out_ int* index,
-    _Out_ int* flag,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_Testany(
-    int count,
-    _Inout_count_(count) MPI_Request* array_of_requests,
-    _Out_ int* index,
-    _Out_ int* flag,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_Waitall(
-    int count,
-    _Inout_count_(count) MPI_Request* array_of_requests,
-    _Out_cap_(count) MPI_Status* array_of_statuses
-    );
-int
-MPIAPI
-PMPI_Waitall(
-    int count,
-    _Inout_count_(count) MPI_Request* array_of_requests,
-    _Out_cap_(count) MPI_Status* array_of_statuses
-    );
-
-int
-MPIAPI
-MPI_Testall(
-    int count,
-    _Inout_count_(count) MPI_Request* array_of_requests,
-    _Out_ int* flag,
-    _Out_cap_(count) MPI_Status* array_of_statuses
-    );
-int
-MPIAPI
-PMPI_Testall(
-    int count,
-    _Inout_count_(count) MPI_Request* array_of_requests,
-    _Out_ int* flag,
-    _Out_cap_(count) MPI_Status* array_of_statuses
-    );
-
-int
-MPIAPI
-MPI_Waitsome(
-    int incount,
-    _Inout_count_(incount) MPI_Request* array_of_requests,
-    _Out_ int* outcount,
-    _Out_cap_post_count_(incount,*outcount) int* array_of_indices,
-    _Out_cap_post_count_(incount,*outcount) MPI_Status* array_of_statuses
-    );
-int
-MPIAPI
-PMPI_Waitsome(
-    int incount,
-    _Inout_count_(incount) MPI_Request* array_of_requests,
-    _Out_ int* outcount,
-    _Out_cap_post_count_(incount,*outcount) int* array_of_indices,
-    _Out_cap_post_count_(incount,*outcount) MPI_Status* array_of_statuses
-    );
-
-int
-MPIAPI
-MPI_Testsome(
-    int incount,
-    _Inout_count_(incount) MPI_Request* array_of_requests,
-    _Out_ int* outcount,
-    _Out_cap_post_count_(incount,*outcount) int* array_of_indices,
-    _Out_cap_post_count_(incount,*outcount) MPI_Status* array_of_statuses
-    );
-int
-MPIAPI
-PMPI_Testsome(
-    int incount,
-    _Inout_count_(incount) MPI_Request* array_of_requests,
-    _Out_ int* outcount,
-    _Out_cap_post_count_(incount,*outcount) int* array_of_indices,
-    _Out_cap_post_count_(incount,*outcount) MPI_Status* array_of_statuses
-    );
-
-
-/*---------------------------------------------*/
-/* Section 3.7.6: Test of status               */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Request_get_status(
-    MPI_Request request,
-    _Out_ int* flag,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_Request_get_status(
-    MPI_Request request,
-    _Out_ int* flag,
-    _Out_ MPI_Status* status
-    );
-
-
-/*---------------------------------------------*/
-/* Section 3.8: Probe and Cancel               */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Iprobe(
-    int source,
-    int tag,
-    MPI_Comm comm,
-    _Out_ int* flag,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_Iprobe(
-    int source,
-    int tag,
-    MPI_Comm comm,
-    _Out_ int* flag,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_Probe(
-    int source,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_Probe(
-    int source,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_Cancel(
-    _In_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_Cancel(
-    _In_ MPI_Request* request
-    );
-
-int
-MPIAPI
-MPI_Test_cancelled(
-    _In_ MPI_Status* status,
-    _Out_ int* flag
-    );
-int
-MPIAPI
-PMPI_Test_cancelled(
-    _In_ MPI_Status* request,
-    _Out_ int* flag
-    );
-
-
-/*---------------------------------------------*/
-/* Section 3.9: Persistent Communication       */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Send_init(
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_Send_init(
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-
-int
-MPIAPI
-MPI_Bsend_init(
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_Bsend_init(
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-
-int
-MPIAPI
-MPI_Ssend_init(
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_Ssend_init(
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-
-int
-MPIAPI
-MPI_Rsend_init(
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_Rsend_init(
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-
-int
-MPIAPI
-MPI_Recv_init(
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int source,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_Recv_init(
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int source,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-
-int
-MPIAPI
-MPI_Start(
-    _Inout_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_Start(
-    _Inout_ MPI_Request* request
-    );
-
-int
-MPIAPI
-MPI_Startall(
-    int count,
-    _Inout_count_(count) MPI_Request* array_of_requests
-    );
-int
-MPIAPI
-PMPI_Startall(
-    int count,
-    _Inout_count_(count) MPI_Request* array_of_requests
-    );
-
-
-/*---------------------------------------------*/
-/* Section 3.10: Send-Recv                     */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Sendrecv(
-    _In_ void* sendbuf,
-    int sendcount,
-    MPI_Datatype sendtype,
-    int dest,
-    int sendtag,
-    _Out_ void* recvbuf,
-    int recvcount,
-    MPI_Datatype recvtype,
-    int source,
-    int recvtag,
-    MPI_Comm comm,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_Sendrecv(
-    _In_ void* sendbuf,
-    int sendcount,
-    MPI_Datatype sendtype,
-    int dest,
-    int sendtag,
-    _Out_ void* recvbuf,
-    int recvcount,
-    MPI_Datatype recvtype,
-    int source,
-    int recvtag,
-    MPI_Comm comm,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_Sendrecv_replace(
-    _Inout_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int sendtag,
-    int source,
-    int recvtag,
-    MPI_Comm comm,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_Sendrecv_replace(
-    _Inout_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int sendtag,
-    int source,
-    int recvtag,
-    MPI_Comm comm,
-    _Out_ MPI_Status* status
-    );
-
-
-/*---------------------------------------------------------------------------*/
-/* Chapter 4: Datatypes                                                      */
-/*---------------------------------------------------------------------------*/
-
-/*---------------------------------------------*/
-/* Section 4.1: Derived Datatypes              */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Type_contiguous(
-    int count,
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-int
-MPIAPI
-PMPI_Type_contiguous(
-    int count,
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-
-int
-MPIAPI
-MPI_Type_vector(
-    int count,
-    int blocklength,
-    int stride,
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-int
-MPIAPI
-PMPI_Type_vector(
-    int count,
-    int blocklength,
-    int stride,
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-
-int
-MPIAPI
-MPI_Type_create_hvector(
-    int count,
-    int blocklength,
-    MPI_Aint stride,
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-int
-MPIAPI
-PMPI_Type_create_hvector(
-    int count,
-    int blocklength,
-    MPI_Aint stride,
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-
-int
-MPIAPI
-MPI_Type_indexed(
-    int count,
-    _In_count_(count) int* array_of_blocklengths,
-    _In_count_(count) int* array_of_displacements,
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-int
-MPIAPI
-PMPI_Type_indexed(
-    int count,
-    _In_count_(count) int* array_of_blocklengths,
-    _In_count_(count) int* array_of_displacements,
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-
-int
-MPIAPI
-MPI_Type_create_hindexed(
-    int count,
-    _In_count_(count) int array_of_blocklengths[],
-    _In_count_(count) MPI_Aint array_of_displacements[],
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-int
-MPIAPI
-PMPI_Type_create_hindexed(
-    int count,
-    _In_count_(count) int array_of_blocklengths[],
-    _In_opt_count_(count) MPI_Aint array_of_displacements[],
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-
-int
-MPIAPI
-MPI_Type_create_indexed_block(
-    int count,
-    int blocklength,
-    _In_count_(count) int array_of_displacements[],
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-int
-MPIAPI
-PMPI_Type_create_indexed_block(
-    int count,
-    int blocklength,
-    _In_count_(count) int array_of_displacements[],
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-
-int
-MPIAPI
-MPI_Type_create_struct(
-    int count,
-    _In_count_(count) int array_of_blocklengths[],
-    _In_count_(count) MPI_Aint array_of_displacements[],
-    _In_count_(count) MPI_Datatype array_of_types[],
-    _Out_ MPI_Datatype* newtype
-    );
-int
-MPIAPI
-PMPI_Type_create_struct(
-    int count,
-    _In_count_(count) int array_of_blocklengths[],
-    _In_opt_count_(count) MPI_Aint array_of_displacements[],
-    _In_count_(count) MPI_Datatype array_of_types[],
-    _Out_ MPI_Datatype* newtype
-    );
-
-
-#define MPI_ORDER_C         56
-#define MPI_ORDER_FORTRAN   57
-
-int
-MPIAPI
-MPI_Type_create_subarray(
-    int ndims,
-    _In_count_(ndims) int array_of_sizes[],
-    _In_count_(ndims) int array_of_subsizes[],
-    _In_count_(ndims) int array_of_starts[],
-    int order,
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-int
-MPIAPI
-PMPI_Type_create_subarray(
-    int ndims,
-    _In_count_(ndims) int array_of_sizes[],
-    _In_count_(ndims) int array_of_subsizes[],
-    _In_count_(ndims) int array_of_starts[],
-    int order,
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-
-
-#define MPI_DISTRIBUTE_BLOCK         121
-#define MPI_DISTRIBUTE_CYCLIC        122
-#define MPI_DISTRIBUTE_NONE          123
-#define MPI_DISTRIBUTE_DFLT_DARG (-49767)
-
-int
-MPIAPI
-MPI_Type_create_darray(
-    int size,
-    int rank,
-    int ndims,
-    _In_count_(ndims) int array_of_gszies[],
-    _In_count_(ndims) int array_of_distribs[],
-    _In_count_(ndims) int array_of_dargs[],
-    _In_count_(ndims) int array_of_psizes[],
-    int order,
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-int
-MPIAPI
-PMPI_Type_create_darray(
-    int size,
-    int rank,
-    int ndims,
-    _In_count_(ndims) int array_of_gszies[],
-    _In_count_(ndims) int array_of_distribs[],
-    _In_count_(ndims) int array_of_dargs[],
-    _In_count_(ndims) int array_of_psizes[],
-    int order,
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-
-
-/*---------------------------------------------*/
-/* Section 4.1.5: Datatype Address and Size    */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Get_address(
-    _In_ void* location,
-    _Out_ MPI_Aint* address
-    );
-int
-MPIAPI
-PMPI_Get_address(
-    _In_ void* location,
-    _Out_ MPI_Aint* address
-    );
-
-int
-MPIAPI
-MPI_Type_size(
-    MPI_Datatype datatype,
-    _Out_ int* size
-    );
-int
-MPIAPI
-PMPI_Type_size(
-    MPI_Datatype datatype,
-    _Out_ int* size
-    );
-
-
-/*---------------------------------------------*/
-/* Section 4.1.7: Datatype Extent and Bounds   */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Type_get_extent(
-    MPI_Datatype datatype,
-    _Out_ MPI_Aint* lb,
-    _Out_ MPI_Aint* extent
-    );
-int
-MPIAPI
-PMPI_Type_get_extent(
-    MPI_Datatype datatype,
-    _Out_ MPI_Aint* lb,
-    _Out_ MPI_Aint* extent
-    );
-
-int
-MPIAPI
-MPI_Type_create_resized(
-    MPI_Datatype oldtype,
-    MPI_Aint lb,
-    MPI_Aint extent,
-    _Out_ MPI_Datatype* newtype
-    );
-int
-MPIAPI
-PMPI_Type_create_resized(
-    MPI_Datatype oldtype,
-    MPI_Aint lb,
-    MPI_Aint extent,
-    _Out_ MPI_Datatype* newtype
-    );
-
-
-/*---------------------------------------------*/
-/* Section 4.1.8: Datatype True Extent         */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Type_get_true_extent(
-    MPI_Datatype datatype,
-    _Out_ MPI_Aint* true_lb,
-    _Out_ MPI_Aint* true_extent
-    );
-int
-MPIAPI
-PMPI_Type_get_true_extent(
-    MPI_Datatype datatype,
-    _Out_ MPI_Aint* true_lb,
-    _Out_ MPI_Aint* true_extent
-    );
-
-
-/*---------------------------------------------*/
-/* Section 4.1.9: Datatype Commit and Free     */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Type_commit(
-    _In_ MPI_Datatype* datatype
-    );
-int
-MPIAPI
-PMPI_Type_commit(
-    _In_ MPI_Datatype* datatype
-    );
-
-int
-MPIAPI
-MPI_Type_free(
-    _Inout_ MPI_Datatype* datatype
-    );
-int
-MPIAPI
-PMPI_Type_free(
-    _Inout_ MPI_Datatype* datatype
-    );
-
-
-/*---------------------------------------------*/
-/* Section 4.1.10: Datatype Duplication        */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Type_dup(
-    MPI_Datatype type,
-    _Out_ MPI_Datatype* newtype
-    );
-int
-MPIAPI
-PMPI_Type_dup(
-    MPI_Datatype type,
-    _Out_ MPI_Datatype* newtype
-    );
-
-
-/*---------------------------------------------*/
-/* Section 4.1.11: Datatype and Communication  */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Get_elements(
-    _In_ MPI_Status* status,
-    MPI_Datatype datatype,
-    _Out_ int* count
-    );
-int
-MPIAPI
-PMPI_Get_elements(
-    _In_ MPI_Status* status,
-    MPI_Datatype datatype,
-    _Out_ int* count
-    );
-
-
-/*---------------------------------------------*/
-/* Section 4.1.13: Decoding a Datatype         */
-/*---------------------------------------------*/
-
-/* Datatype combiners result */
-enum
-{
-    MPI_COMBINER_NAMED            = 1,
-    MPI_COMBINER_DUP              = 2,
-    MPI_COMBINER_CONTIGUOUS       = 3,
-    MPI_COMBINER_VECTOR           = 4,
-    MPI_COMBINER_HVECTOR_INTEGER  = 5,
-    MPI_COMBINER_HVECTOR          = 6,
-    MPI_COMBINER_INDEXED          = 7,
-    MPI_COMBINER_HINDEXED_INTEGER = 8,
-    MPI_COMBINER_HINDEXED         = 9,
-    MPI_COMBINER_INDEXED_BLOCK    = 10,
-    MPI_COMBINER_STRUCT_INTEGER   = 11,
-    MPI_COMBINER_STRUCT           = 12,
-    MPI_COMBINER_SUBARRAY         = 13,
-    MPI_COMBINER_DARRAY           = 14,
-    MPI_COMBINER_F90_REAL         = 15,
-    MPI_COMBINER_F90_COMPLEX      = 16,
-    MPI_COMBINER_F90_INTEGER      = 17,
-    MPI_COMBINER_RESIZED          = 18
-};
-
-int
-MPIAPI
-MPI_Type_get_envelope(
-    MPI_Datatype datatype,
-    _Out_ int* num_integers,
-    _Out_ int* num_addresses,
-    _Out_ int* num_datatypes,
-    _Out_ int* combiner
-    );
-int
-MPIAPI
-PMPI_Type_get_envelope(
-    MPI_Datatype datatype,
-    _Out_ int* num_integers,
-    _Out_ int* num_addresses,
-    _Out_ int* num_datatypes,
-    _Out_ int* combiner
-    );
-
-int
-MPIAPI
-MPI_Type_get_contents(
-    MPI_Datatype datatype,
-    int max_integers,
-    int max_addresses,
-    int max_datatypes,
-    _Out_cap_(max_integers) int array_of_integers[],
-    _Out_cap_(max_addresses) MPI_Aint array_of_addresses[],
-    _Out_cap_(max_datatypes) MPI_Datatype array_of_datatypes[]
-    );
-int
-MPIAPI
-PMPI_Type_get_contents(
-    MPI_Datatype datatype,
-    int max_integers,
-    int max_addresses,
-    int max_datatypes,
-    _Out_cap_(max_integers) int array_of_integers[],
-    _Out_cap_(max_addresses) MPI_Aint array_of_addresses[],
-    _Out_cap_(max_datatypes) MPI_Datatype array_of_datatypes[]
-    );
-
-
-/*---------------------------------------------*/
-/* Section 4.2: Datatype Pack and Unpack       */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Pack(
-    _In_ void* inbuf,
-    int incount,
-    MPI_Datatype datatype,
-    _Out_bytecap_(outsize) void* outbuf,
-    int outsize,
-    _Inout_ int* position,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Pack(
-    _In_ void* inbuf,
-    int incount,
-    MPI_Datatype datatype,
-    _Out_bytecap_(outsize) void* outbuf,
-    int outsize,
-    _Inout_ int* position,
-    MPI_Comm comm
-    );
-
-int
-MPIAPI
-MPI_Unpack(
-    _In_bytecount_(insize) void* inbuf,
-    int insize,
-    _Inout_ int* position,
-    _Out_ void* outbuf,
-    int outcount,
-    MPI_Datatype datatype,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Unpack(
-    _In_bytecount_(insize) void* inbuf,
-    int insize,
-    _Inout_ int* position,
-    _Out_ void* outbuf,
-    int outcount,
-    MPI_Datatype datatype,
-    MPI_Comm comm
-    );
-
-int
-MPIAPI
-MPI_Pack_size(
-    int incount,
-    MPI_Datatype datatype,
-    MPI_Comm comm,
-    _Out_ int* size
-    );
-int
-MPIAPI
-PMPI_Pack_size(
-    int incount,
-    MPI_Datatype datatype,
-    MPI_Comm comm,
-    _Out_ int* size
-    );
-
-
-/*---------------------------------------------*/
-/* Section 4.3: Canonical Pack and Unpack      */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Pack_external(
-    _In_z_ char* datarep,
-    _In_ void* inbuf,
-    int incount,
-    MPI_Datatype datatype,
-    _Out_bytecap_(outsize) void* outbuf,
-    MPI_Aint outsize,
-    _Inout_ MPI_Aint* position
-    );
-int
-MPIAPI
-PMPI_Pack_external(
-    _In_z_ char* datarep,
-    _In_ void* inbuf,
-    int incount,
-    MPI_Datatype datatype,
-    _Out_bytecap_(outsize) void* outbuf,
-    MPI_Aint outsize,
-    _Inout_ MPI_Aint* position
-    );
-
-int
-MPIAPI
-MPI_Unpack_external(
-    _In_z_ char* datarep,
-    _In_bytecount_(insize) void* inbuf,
-    MPI_Aint insize,
-    _Inout_ MPI_Aint* position,
-    _Out_ void* outbuf,
-    int outcount,
-    MPI_Datatype datatype
-    );
-int
-MPIAPI
-PMPI_Unpack_external(
-    _In_z_ char* datarep,
-    _In_bytecount_(insize) void* inbuf,
-    MPI_Aint insize,
-    _Inout_ MPI_Aint* position,
-    _Out_ void* outbuf,
-    int outcount,
-    MPI_Datatype datatype
-    );
-
-int
-MPIAPI
-MPI_Pack_external_size(
-    _In_z_ char* datarep,
-    int incount,
-    MPI_Datatype datatype,
-    _Out_ MPI_Aint* size
-    );
-int
-MPIAPI
-PMPI_Pack_external_size(
-    _In_z_ char* datarep,
-    int incount,
-    MPI_Datatype datatype,
-    _Out_ MPI_Aint* size
-    );
-
-
-/*---------------------------------------------------------------------------*/
-/* Chapter 5: Collective Communication                                       */
-/*---------------------------------------------------------------------------*/
-
-#define MPI_IN_PLACE ((void*)(MPI_Aint)-1)
-
-/*---------------------------------------------*/
-/* Section 5.3: Barrier Synchronization        */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Barrier(
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Barrier(
-    MPI_Comm comm
-    );
-
-
-/*---------------------------------------------*/
-/* Section 5.4: Broadcast                      */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Bcast(
-    _Inout_ void* buffer,
-    int count,
-    MPI_Datatype datatype,
-    int root,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Bcast(
-    _Inout_ void* buffer,
-    int count,
-    MPI_Datatype datatype,
-    int root,
-    MPI_Comm comm
-    );
-
-
-/*---------------------------------------------*/
-/* Section 5.5: Gather                         */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Gather(
-    _In_ void* sendbuf,
-    int sendcount,
-    MPI_Datatype sendtype,
-    _Out_opt_ void* recvbuf,
-    int recvcount,
-    MPI_Datatype recvtype,
-    int root,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Gather(
-    _In_ void* sendbuf,
-    int sendcount,
-    MPI_Datatype sendtype,
-    _Out_opt_ void* recvbuf,
-    int recvcount,
-    MPI_Datatype recvtype,
-    int root,
-    MPI_Comm comm
-    );
-
-int
-MPIAPI
-MPI_Gatherv(
-    _In_ void* sendbuf,
-    int sendcount,
-    MPI_Datatype sendtype,
-    _Out_opt_ void* recvbuf,
-    _In_opt_ int* recvcounts,
-    _In_opt_ int* displs,
-    MPI_Datatype recvtype,
-    int root,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Gatherv(
-    _In_ void* sendbuf,
-    int sendcount,
-    MPI_Datatype sendtype,
-    _Out_opt_ void* recvbuf,
-    _In_opt_ int* recvcounts,
-    _In_opt_ int* displs,
-    MPI_Datatype recvtype,
-    int root,
-    MPI_Comm comm
-    );
-
-
-/*---------------------------------------------*/
-/* Section 5.6: Scatter                        */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Scatter(
-    _In_ void* sendbuf,
-    int sendcount,
-    MPI_Datatype sendtype,
-    _Out_ void* recvbuf,
-    int recvcount,
-    MPI_Datatype recvtype,
-    int root,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Scatter(
-    _In_ void* sendbuf,
-    int sendcount,
-    MPI_Datatype sendtype,
-    _Out_ void* recvbuf,
-    int recvcount,
-    MPI_Datatype recvtype,
-    int root,
-    MPI_Comm comm
-    );
-
-int
-MPIAPI
-MPI_Scatterv(
-    _In_ void* sendbuf,
-    _In_ int* sendcounts,
-    _In_ int* displs,
-    MPI_Datatype sendtype,
-    _Out_ void* recvbuf,
-    int recvcount,
-    MPI_Datatype recvtype,
-    int root,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Scatterv(
-    _In_ void* sendbuf,
-    _In_ int* sendcounts,
-    _In_ int* displs,
-    MPI_Datatype sendtype,
-    _Out_ void* recvbuf,
-    int recvcount,
-    MPI_Datatype recvtype,
-    int root,
-    MPI_Comm comm
-    );
-
-
-/*---------------------------------------------*/
-/* Section 5.6: Gather-to-all                  */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Allgather(
-    _In_ void* sendbuf,
-    int sendcount,
-    MPI_Datatype sendtype,
-    _Out_ void* recvbuf,
-    int recvcount,
-    MPI_Datatype recvtype,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Allgather(
-    _In_ void* sendbuf,
-    int sendcount,
-    MPI_Datatype sendtype,
-    _Out_ void* recvbuf,
-    int recvcount,
-    MPI_Datatype recvtype,
-    MPI_Comm comm
-    );
-
-int
-MPIAPI
-MPI_Allgatherv(
-    _In_ void* sendbuf,
-    int sendcount,
-    MPI_Datatype sendtype,
-    _Out_ void* recvbuf,
-    _In_ int* recvcounts,
-    _In_ int* displs,
-    MPI_Datatype recvtype,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Allgatherv(
-    _In_ void* sendbuf,
-    int sendcount,
-    MPI_Datatype sendtype,
-    _Out_ void* recvbuf,
-    _In_ int* recvcounts,
-    _In_ int* displs,
-    MPI_Datatype recvtype,
-    MPI_Comm comm
-    );
-
-
-/*---------------------------------------------*/
-/* Section 5.6: All-to-All Scatter/Gather      */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Alltoall(
-    _In_ void* sendbuf,
-    int sendcount,
-    MPI_Datatype sendtype,
-    _Out_ void* recvbuf,
-    int recvcount,
-    MPI_Datatype recvtype,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Alltoall(
-    _In_ void* sendbuf,
-    int sendcount,
-    MPI_Datatype sendtype,
-    _Out_ void* recvbuf,
-    int recvcount,
-    MPI_Datatype recvtype,
-    MPI_Comm comm
-    );
-
-int
-MPIAPI
-MPI_Alltoallv(
-    _In_ void* sendbuf,
-    _In_ int* sendcounts,
-    _In_ int* sdispls,
-    MPI_Datatype sendtype,
-    _Out_ void* recvbuf,
-    _In_ int* recvcounts,
-    _In_ int* rdispls,
-    MPI_Datatype recvtype,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Alltoallv(
-    _In_ void* sendbuf,
-    _In_ int* sendcounts,
-    _In_ int* sdispls,
-    MPI_Datatype sendtype,
-    _Out_ void* recvbuf,
-    _In_ int* recvcounts,
-    _In_ int* rdispls,
-    MPI_Datatype recvtype,
-    MPI_Comm comm
-    );
-
-int
-MPIAPI
-MPI_Alltoallw(
-    _In_ void* sendbuf,
-    _In_ int sendcounts[],
-    _In_ int sdispls[],
-    _In_ MPI_Datatype sendtypes[],
-    _Out_ void* recvbuf,
-    _In_ int recvcounts[],
-    _In_ int rdispls[],
-    _In_ MPI_Datatype recvtypes[],
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Alltoallw(
-    _In_ void* sendbuf,
-    _In_ int sendcounts[],
-    _In_ int sdispls[],
-    _In_ MPI_Datatype sendtypes[],
-    _Out_ void* recvbuf,
-    _In_ int recvcounts[],
-    _In_ int rdispls[],
-    _In_ MPI_Datatype recvtypes[],
-    MPI_Comm comm
-    );
-
-
-/*---------------------------------------------*/
-/* Section 5.9: Global Reduction Operations    */
-/*---------------------------------------------*/
-
-typedef
-void
-(MPIAPI MPI_User_function)(
-    _In_count_(*len) void* invec,
-    _Inout_ void* inoutvec,
-    _In_ int* len,
-    _In_ MPI_Datatype* datatype
-    );
-
-int
-MPIAPI
-MPI_Op_create(
-    _In_ MPI_User_function* function,
-    int commute,
-    _Out_ MPI_Op* op
-    );
-int
-MPIAPI
-PMPI_Op_create(
-    _In_ MPI_User_function* function,
-    int commute,
-    _Out_ MPI_Op* op
-    );
-
-int
-MPIAPI
-MPI_Op_free(
-    _Inout_ MPI_Op* op
-    );
-int
-MPIAPI
-PMPI_Op_free(
-    _Inout_ MPI_Op* op
-    );
-
-int
-MPIAPI
-MPI_Reduce(
-    _In_ void* sendbuf,
-    _Out_opt_ void* recvbuf,
-    int count,
-    MPI_Datatype datatype,
-    MPI_Op op,
-    int root,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Reduce(
-    _In_ void* sendbuf,
-    _Out_opt_ void* recvbuf,
-    int count,
-    MPI_Datatype datatype,
-    MPI_Op op,
-    int root,
-    MPI_Comm comm
-    );
-
-int
-MPIAPI
-MPI_Allreduce(
-    _In_ void* sendbuf,
-    _Out_ void* recvbuf,
-    int count,
-    MPI_Datatype datatype,
-    MPI_Op op,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Allreduce(
-    _In_ void* sendbuf,
-    _Out_ void* recvbuf,
-    int count,
-    MPI_Datatype datatype,
-    MPI_Op op,
-    MPI_Comm comm
-    );
-
-int
-MPIAPI
-MPI_Reduce_local(
-    _In_ void *inbuf,
-    _Inout_ void *inoutbuf,
-    int count,
-    MPI_Datatype datatype,
-    MPI_Op op
-    );
-int
-MPIAPI
-PMPI_Reduce_local(
-    _In_ void *inbuf,
-    _Inout_ void *inoutbuf,
-    int count,
-    MPI_Datatype datatype,
-    MPI_Op op
-    );
-
-/*---------------------------------------------*/
-/* Section 5.10: Reduce-Scatter                */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Reduce_scatter(
-    _In_ void* sendbuf,
-    _Out_ void* recvbuf,
-    _In_ int* recvcounts,
-    MPI_Datatype datatype,
-    MPI_Op op,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Reduce_scatter(
-    _In_ void* sendbuf,
-    _Out_ void* recvbuf,
-    _In_ int* recvcounts,
-    MPI_Datatype datatype,
-    MPI_Op op,
-    MPI_Comm comm
-    );
-
-
-/*---------------------------------------------*/
-/* Section 5.11: Scan                          */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Scan(
-    _In_ void* sendbuf,
-    _Out_ void* recvbuf,
-    int count,
-    MPI_Datatype datatype,
-    MPI_Op op,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Scan(
-    _In_ void* sendbuf,
-    _Out_ void* recvbuf,
-    int count,
-    MPI_Datatype datatype,
-    MPI_Op op,
-    MPI_Comm comm
-    );
-
-int
-MPIAPI
-MPI_Exscan(
-    _In_ void* sendbuf,
-    _Out_ void* recvbuf,
-    int count,
-    MPI_Datatype datatype,
-    MPI_Op op,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Exscan(
-    _In_ void* sendbuf,
-    _Out_ void* recvbuf,
-    int count,
-    MPI_Datatype datatype,
-    MPI_Op op,
-    MPI_Comm comm
-    );
-
-
-/*---------------------------------------------------------------------------*/
-/* Chapter 6: Groups, Contexts, Communicators, and Caching                   */
-/*---------------------------------------------------------------------------*/
-
-/*---------------------------------------------*/
-/* Section 6.3: Group Management               */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Group_size(
-    MPI_Group group,
-    _Out_ int* size
-    );
-int
-MPIAPI
-PMPI_Group_size(
-    MPI_Group group,
-    _Out_ int* size
-    );
-
-int
-MPIAPI
-MPI_Group_rank(
-    MPI_Group group,
-    _Out_ int* rank
-    );
-int
-MPIAPI
-PMPI_Group_rank(
-    MPI_Group group,
-    _Out_ int* rank
-    );
-
-int
-MPIAPI
-MPI_Group_translate_ranks(
-    MPI_Group group1,
-    int n,
-    _In_count_(n) int* ranks1,
-    MPI_Group group2,
-    _Out_ int* ranks2
-    );
-
-int
-MPIAPI
-PMPI_Group_translate_ranks(
-    MPI_Group group1,
-    int n,
-    _In_count_(n) int* ranks1,
-    MPI_Group group2,
-    _Out_ int* ranks2
-    );
-
-/* Results of the compare operations */
-#define MPI_IDENT       0
-#define MPI_CONGRUENT   1
-#define MPI_SIMILAR     2
-#define MPI_UNEQUAL     3
-
-int
-MPIAPI
-MPI_Group_compare(
-    MPI_Group group1,
-    MPI_Group group2,
-    _Out_ int* result
-    );
-int
-MPIAPI
-PMPI_Group_compare(
-    MPI_Group group1,
-    MPI_Group group2,
-    _Out_ int* result
-    );
-
-int
-MPIAPI
-MPI_Comm_group(
-    MPI_Comm comm,
-    _Out_ MPI_Group* group
-    );
-int
-MPIAPI
-PMPI_Comm_group(
-    MPI_Comm comm,
-    _Out_ MPI_Group* group
-    );
-
-int
-MPIAPI
-MPI_Group_union(
-    MPI_Group group1,
-    MPI_Group group2,
-    _Out_ MPI_Group* newgroup
-    );
-int
-MPIAPI
-PMPI_Group_union(
-    MPI_Group group1,
-    MPI_Group group2,
-    _Out_ MPI_Group* newgroup
-    );
-
-int
-MPIAPI
-MPI_Group_intersection(
-    MPI_Group group1,
-    MPI_Group group2,
-    _Out_ MPI_Group* newgroup
-    );
-int
-MPIAPI
-PMPI_Group_intersection(
-    MPI_Group group1,
-    MPI_Group group2,
-    _Out_ MPI_Group* newgroup
-    );
-
-int
-MPIAPI
-MPI_Group_difference(
-    MPI_Group group1,
-    MPI_Group group2,
-    _Out_ MPI_Group* newgroup
-    );
-int
-MPIAPI
-PMPI_Group_difference(
-    MPI_Group group1,
-    MPI_Group group2,
-    _Out_ MPI_Group* newgroup
-    );
-
-int
-MPIAPI
-MPI_Group_incl(
-    MPI_Group group,
-    int n,
-    _In_count_(n) int* ranks,
-    _Out_ MPI_Group* newgroup
-    );
-int
-MPIAPI
-PMPI_Group_incl(
-    MPI_Group group,
-    int n,
-    _In_count_(n) int* ranks,
-    _Out_ MPI_Group* newgroup
-    );
-
-int
-MPIAPI
-MPI_Group_excl(
-    MPI_Group group,
-    int n,
-    _In_count_(n) int* ranks,
-    _Out_ MPI_Group* newgroup
-    );
-int
-MPIAPI
-PMPI_Group_excl(
-    MPI_Group group,
-    int n,
-    _In_count_(n) int* ranks,
-    _Out_ MPI_Group* newgroup
-    );
-
-int
-MPIAPI
-MPI_Group_range_incl(
-    MPI_Group group,
-    int n,
-    _In_count_(n) int ranges[][3],
-    _Out_ MPI_Group* newgroup
-    );
-int
-MPIAPI
-PMPI_Group_range_incl(
-    MPI_Group group,
-    int n,
-    _In_count_(n) int ranges[][3],
-    _Out_ MPI_Group* newgroup
-    );
-
-int
-MPIAPI
-MPI_Group_range_excl(
-    MPI_Group group,
-    int n,
-    _In_count_(n) int ranges[][3],
-    _Out_ MPI_Group* newgroup
-    );
-int
-MPIAPI
-PMPI_Group_range_excl(
-    MPI_Group group,
-    int n,
-    _In_count_(n) int ranges[][3],
-    _Out_ MPI_Group* newgroup
-    );
-
-int
-MPIAPI
-MPI_Group_free(
-    _Inout_ MPI_Group* group
-    );
-int
-MPIAPI
-PMPI_Group_free(
-    _Inout_ MPI_Group* group
-    );
-
-
-/*---------------------------------------------*/
-/* Section 6.4: Communicator Management        */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Comm_size(
-    MPI_Comm comm,
-    _Out_ int* size
-    );
-int
-MPIAPI
-PMPI_Comm_size(
-    MPI_Comm comm,
-    _Out_ int* size
-    );
-
-int
-MPIAPI
-MPI_Comm_rank(
-    MPI_Comm comm,
-    _Out_ int* rank
-    );
-int
-MPIAPI
-PMPI_Comm_rank(
-    MPI_Comm comm,
-    _Out_ int* rank
-    );
-
-int
-MPIAPI
-MPI_Comm_compare(
-    MPI_Comm comm1,
-    MPI_Comm comm2,
-    _Out_ int* result
-    );
-int
-MPIAPI
-PMPI_Comm_compare(
-    MPI_Comm comm1,
-    MPI_Comm comm2,
-    _Out_ int* result
-    );
-
-int
-MPIAPI
-MPI_Comm_dup(
-    MPI_Comm comm,
-    _Out_ MPI_Comm* newcomm
-    );
-int
-MPIAPI
-PMPI_Comm_dup(
-    MPI_Comm comm,
-    _Out_ MPI_Comm* newcomm
-    );
-
-int
-MPIAPI
-MPI_Comm_create(
-    MPI_Comm comm,
-    MPI_Group group,
-    _Out_ MPI_Comm* newcomm
-    );
-int
-MPIAPI
-PMPI_Comm_create(
-    MPI_Comm comm,
-    MPI_Group group,
-    _Out_ MPI_Comm* newcomm
-    );
-
-int
-MPIAPI
-MPI_Comm_split(
-    MPI_Comm comm,
-    int color,
-    int key,
-    _Out_ MPI_Comm* newcomm
-    );
-int
-MPIAPI
-PMPI_Comm_split(
-    MPI_Comm comm,
-    int color,
-    int key,
-    _Out_ MPI_Comm* newcomm
-    );
-
-int
-MPIAPI
-MPI_Comm_free(
-    _Inout_ MPI_Comm* comm
-    );
-int
-MPIAPI
-PMPI_Comm_free(
-    _Inout_ MPI_Comm* comm
-    );
-
-
-/*---------------------------------------------*/
-/* Section 6.6: Inter-Communication            */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Comm_test_inter(
-    MPI_Comm comm,
-    _Out_ int* flag
-    );
-int
-MPIAPI
-PMPI_Comm_test_inter(
-    MPI_Comm comm,
-    _Out_ int* flag
-    );
-
-int
-MPIAPI
-MPI_Comm_remote_size(
-    MPI_Comm comm,
-    _Out_ int* size
-    );
-int
-MPIAPI
-PMPI_Comm_remote_size(
-    MPI_Comm comm,
-    _Out_ int* size
-    );
-
-int
-MPIAPI
-MPI_Comm_remote_group(
-    MPI_Comm comm,
-    _Out_ MPI_Group* group
-    );
-int
-MPIAPI
-PMPI_Comm_remote_group(
-    MPI_Comm comm,
-    _Out_ MPI_Group* group
-    );
-
-int
-MPIAPI
-MPI_Intercomm_create(
-    MPI_Comm local_comm,
-    int local_leader,
-    MPI_Comm peer_comm,
-    int remote_leader,
-    int tag,
-    _Out_ MPI_Comm* newintercomm
-    );
-int
-MPIAPI
-PMPI_Intercomm_create(
-    MPI_Comm local_comm,
-    int local_leader,
-    MPI_Comm peer_comm,
-    int remote_leader,
-    int tag,
-    _Out_ MPI_Comm* newintercomm
-    );
-
-int
-MPIAPI
-MPI_Intercomm_merge(
-    MPI_Comm intercomm,
-    int high,
-    _Out_ MPI_Comm* newintracomm
-    );
-int
-MPIAPI
-PMPI_Intercomm_merge(
-    MPI_Comm intercomm,
-    int high,
-    _Out_ MPI_Comm* newintracomm
-    );
-
-
-/*---------------------------------------------*/
-/* Section 6.7: Caching                        */
-/*---------------------------------------------*/
-
-#define MPI_KEYVAL_INVALID  0x24000000
-
-typedef
-int
-(MPIAPI MPI_Comm_copy_attr_function)(
-    MPI_Comm oldcomm,
-    int comm_keyval,
-    _In_opt_ void* extra_state,
-    _In_ void* attribute_val_in,
-    _Out_ void* attribute_val_out,
-    _Out_ int* flag
-    );
-
-typedef
-int
-(MPIAPI MPI_Comm_delete_attr_function)(
-    MPI_Comm comm,
-    int comm_keyval,
-    _In_ void* attribute_val,
-    _In_opt_ void* extra_state
-    );
-
-#define MPI_COMM_NULL_COPY_FN ((MPI_Comm_copy_attr_function*)0)
-#define MPI_COMM_NULL_DELETE_FN ((MPI_Comm_delete_attr_function*)0)
-#define MPI_COMM_DUP_FN ((MPI_Comm_copy_attr_function*)MPIR_Dup_fn)
-
-int
-MPIAPI
-MPI_Comm_create_keyval(
-    _In_opt_ MPI_Comm_copy_attr_function* comm_copy_attr_fn,
-    _In_opt_ MPI_Comm_delete_attr_function* comm_delete_attr_fn,
-    _Out_ int* comm_keyval,
-    _In_opt_ void* extra_state
-    );
-int
-MPIAPI
-PMPI_Comm_create_keyval(
-    _In_opt_ MPI_Comm_copy_attr_function* comm_copy_attr_fn,
-    _In_opt_ MPI_Comm_delete_attr_function* comm_delete_attr_fn,
-    _Out_ int* comm_keyval,
-    _In_opt_ void* extra_state
-    );
-
-int
-MPIAPI
-MPI_Comm_free_keyval(
-    _Inout_ int* comm_keyval
-    );
-int
-MPIAPI
-PMPI_Comm_free_keyval(
-    _Inout_ int* comm_keyval
-    );
-
-int
-MPIAPI
-MPI_Comm_set_attr(
-    MPI_Comm comm,
-    int comm_keyval,
-    _In_ void* attribute_val
-    );
-int
-MPIAPI
-PMPI_Comm_set_attr(
-    MPI_Comm comm,
-    int comm_keyval,
-    _In_ void* attribute_val
-    );
-
-
-/* Predefined comm attribute key values */
-/* C Versions (return pointer to value),
-   Fortran Versions (return integer value).
-
-   DO NOT CHANGE THESE.  The values encode:
-   builtin kind (0x1 in bit 30-31)
-   Keyval object (0x9 in bits 26-29)
-   for communicator (0x1 in bits 22-25)
-
-   Fortran versions of the attributes are formed by adding one to
-   the C version.
- */
-#define MPI_TAG_UB          0x64400001
-#define MPI_HOST            0x64400003
-#define MPI_IO              0x64400005
-#define MPI_WTIME_IS_GLOBAL 0x64400007
-#define MPI_UNIVERSE_SIZE   0x64400009
-#define MPI_LASTUSEDCODE    0x6440000b
-#define MPI_APPNUM          0x6440000d
-
-int
-MPIAPI
-MPI_Comm_get_attr(
-    MPI_Comm comm,
-    int comm_keyval,
-    _Out_ void* attribute_val,
-    _Out_ int* flag
-    );
-int
-MPIAPI
-PMPI_Comm_get_attr(
-    MPI_Comm comm,
-    int comm_keyval,
-    _Out_ void* attribute_val,
-    _Out_ int* flag
-    );
-
-int
-MPIAPI
-MPI_Comm_delete_attr(
-    MPI_Comm comm,
-    int comm_keyval
-    );
-int
-MPIAPI
-PMPI_Comm_delete_attr(
-    MPI_Comm comm,
-    int comm_keyval
-    );
-
-
-typedef
-int
-(MPIAPI MPI_Win_copy_attr_function)(
-    MPI_Win oldwin,
-    int win_keyval,
-    _In_opt_ void* extra_state,
-    _In_ void* attribute_val_in,
-    _Out_ void* attribute_val_out,
-    _Out_ int* flag
-    );
-
-typedef
-int
-(MPIAPI MPI_Win_delete_attr_function)(
-    MPI_Win win,
-    int win_keyval,
-    _In_ void* attribute_val,
-    _In_opt_ void* extra_state
-    );
-
-#define MPI_WIN_NULL_COPY_FN ((MPI_Win_copy_attr_function*)0)
-#define MPI_WIN_NULL_DELETE_FN ((MPI_Win_delete_attr_function*)0)
-#define MPI_WIN_DUP_FN ((MPI_Win_copy_attr_function*)MPIR_Dup_fn)
-
-int
-MPIAPI
-MPI_Win_create_keyval(
-    _In_ MPI_Win_copy_attr_function* win_copy_attr_fn,
-    _In_ MPI_Win_delete_attr_function* win_delete_attr_fn,
-    _Out_ int* win_keyval,
-    _In_opt_ void* extra_state
-    );
-int
-MPIAPI
-PMPI_Win_create_keyval(
-    _In_ MPI_Win_copy_attr_function* win_copy_attr_fn,
-    _In_ MPI_Win_delete_attr_function* win_delete_attr_fn,
-    _Out_ int* win_keyval,
-    _In_opt_ void* extra_state
-    );
-
-int
-MPIAPI
-MPI_Win_free_keyval(
-    _Inout_ int* win_keyval
-    );
-int
-MPIAPI
-PMPI_Win_free_keyval(
-    _Inout_ int* win_keyval
-    );
-
-int
-MPIAPI
-MPI_Win_set_attr(
-    MPI_Win win,
-    int win_keyval,
-    _In_ void* attribute_val
-    );
-int
-MPIAPI
-PMPI_Win_set_attr(
-    MPI_Win win,
-    int win_keyval,
-    _In_ void* attribute_val
-    );
-
-
-/* Predefined window key value attributes */
-#define MPI_WIN_BASE        0x66000001
-#define MPI_WIN_SIZE        0x66000003
-#define MPI_WIN_DISP_UNIT   0x66000005
-
-int
-MPIAPI
-MPI_Win_get_attr(
-    MPI_Win win,
-    int win_keyval,
-    _Out_ void* attribute_val,
-    _Out_ int* flag
-    );
-int
-MPIAPI
-PMPI_Win_get_attr(
-    MPI_Win win,
-    int win_keyval,
-    _Out_ void* attribute_val,
-    _Out_ int* flag
-    );
-
-int
-MPIAPI
-MPI_Win_delete_attr(
-    MPI_Win win,
-    int win_keyval
-    );
-int
-MPIAPI
-PMPI_Win_delete_attr(
-    MPI_Win win,
-    int win_keyval
-    );
-
-
-typedef
-int
-(MPIAPI MPI_Type_copy_attr_function)(
-    MPI_Datatype olddatatype,
-    int datatype_keyval,
-    _In_opt_ void* extra_state,
-    _In_ void* attribute_val_in,
-    _Out_ void* attribute_val_out,
-    _Out_ int* flag
-    );
-
-typedef
-int
-(MPIAPI MPI_Type_delete_attr_function)(
-    MPI_Datatype datatype,
-    int datatype_keyval,
-    _In_ void* attribute_val,
-    _In_opt_ void* extra_state
-    );
-
-#define MPI_TYPE_NULL_COPY_FN ((MPI_Type_copy_attr_function*)0)
-#define MPI_TYPE_NULL_DELETE_FN ((MPI_Type_delete_attr_function*)0)
-#define MPI_TYPE_DUP_FN ((MPI_Type_copy_attr_function*)MPIR_Dup_fn)
-
-int
-MPIAPI
-MPI_Type_create_keyval(
-    _In_ MPI_Type_copy_attr_function* type_copy_attr_fn,
-    _In_ MPI_Type_delete_attr_function* type_delete_attr_fn,
-    _Out_ int* type_keyval,
-    _In_opt_ void* extra_state
-    );
-int
-MPIAPI
-PMPI_Type_create_keyval(
-    _In_ MPI_Type_copy_attr_function* type_copy_attr_fn,
-    _In_ MPI_Type_delete_attr_function* type_delete_attr_fn,
-    _Out_ int* type_keyval,
-    _In_opt_ void* extra_state
-    );
-
-int
-MPIAPI
-MPI_Type_free_keyval(
-    _Inout_ int* type_keyval
-    );
-int
-MPIAPI
-PMPI_Type_free_keyval(
-    _Inout_ int* type_keyval
-    );
-
-int
-MPIAPI
-MPI_Type_set_attr(
-    MPI_Datatype type,
-    int type_keyval,
-    _In_ void* attribute_val
-    );
-int
-MPIAPI
-PMPI_Type_set_attr(
-    MPI_Datatype type,
-    int type_keyval,
-    _In_ void* attribute_val
-    );
-
-int
-MPIAPI
-MPI_Type_get_attr(
-    MPI_Datatype type,
-    int type_keyval,
-    _Out_ void* attribute_val,
-    _Out_ int* flag
-    );
-int
-MPIAPI
-PMPI_Type_get_attr(
-    MPI_Datatype type,
-    int type_keyval,
-    _Out_ void* attribute_val,
-    _Out_ int* flag
-    );
-
-int
-MPIAPI
-MPI_Type_delete_attr(
-    MPI_Datatype datatype,
-    int type_keyval
-    );
-int
-MPIAPI
-PMPI_Type_delete_attr(
-    MPI_Datatype datatype,
-    int type_keyval
-    );
-
-
-/*---------------------------------------------*/
-/* Section 6.8: Naming Objects                 */
-/*---------------------------------------------*/
-
-#define MPI_MAX_OBJECT_NAME 128
-
-int
-MPIAPI
-MPI_Comm_set_name(
-    MPI_Comm comm,
-    _In_z_ char* comm_name
-    );
-int
-MPIAPI
-PMPI_Comm_set_name(
-    MPI_Comm comm,
-    _In_z_ char* comm_name
-    );
-
-int
-MPIAPI
-MPI_Comm_get_name(
-    MPI_Comm comm,
-    _Out_z_cap_post_count_(MPI_MAX_OBJECT_NAME,*resultlen) char* comm_name,
-    _Out_ int* resultlen
-    );
-int
-MPIAPI
-PMPI_Comm_get_name(
-    MPI_Comm comm,
-    _Out_z_cap_post_count_(MPI_MAX_OBJECT_NAME,*resultlen) char* comm_name,
-    _Out_ int* resultlen
-    );
-
-int
-MPIAPI
-MPI_Type_set_name(
-    MPI_Datatype type,
-    _In_z_ char* type_name
-    );
-int
-MPIAPI
-PMPI_Type_set_name(
-    MPI_Datatype type,
-    _In_z_ char* type_name
-    );
-
-int
-MPIAPI
-MPI_Type_get_name(
-    MPI_Datatype type,
-    _Out_z_cap_post_count_(MPI_MAX_OBJECT_NAME,*resultlen) char* type_name,
-    _Out_ int* resultlen
-    );
-int
-MPIAPI
-PMPI_Type_get_name(
-    MPI_Datatype type,
-    _Out_z_cap_post_count_(MPI_MAX_OBJECT_NAME,*resultlen) char* type_name,
-    _Out_ int* resultlen
-    );
-
-int
-MPIAPI
-MPI_Win_set_name(
-    MPI_Win win,
-    _In_z_ char* win_name
-    );
-int
-MPIAPI
-PMPI_Win_set_name(
-    MPI_Win win,
-    _In_z_ char* win_name
-    );
-
-int
-MPIAPI
-MPI_Win_get_name(
-    MPI_Win win,
-    _Out_z_cap_post_count_(MPI_MAX_OBJECT_NAME,*resultlen) char* win_name,
-    _Out_ int* resultlen
-    );
-int
-MPIAPI
-PMPI_Win_get_name(
-    MPI_Win win,
-    _Out_z_cap_post_count_(MPI_MAX_OBJECT_NAME,*resultlen) char* win_name,
-    _Out_ int* resultlen
-    );
-
-
-/*---------------------------------------------------------------------------*/
-/* Chapter 7: Process Topologies                                             */
-/*---------------------------------------------------------------------------*/
-
-int
-MPIAPI
-MPI_Cart_create(
-    MPI_Comm comm_old,
-    int ndims,
-    _In_count_(ndims) int* dims,
-    _In_count_(ndims) int* periods,
-    int reorder,
-    _Out_ MPI_Comm* comm_cart
-    );
-int
-MPIAPI
-PMPI_Cart_create(
-    MPI_Comm comm_old,
-    int ndims,
-    _In_count_(ndims) int* dims,
-    _In_count_(ndims) int* periods,
-    int reorder,
-    _Out_ MPI_Comm* comm_cart
-    );
-
-int
-MPIAPI
-MPI_Dims_create(
-    int nnodes,
-    int ndims,
-    _Inout_count_(ndims) int* dims
-    );
-int
-MPIAPI
-PMPI_Dims_create(
-    int nnodes,
-    int ndims,
-    _Inout_count_(ndims) int* dims
-    );
-
-int
-MPIAPI
-MPI_Graph_create(
-    MPI_Comm comm_old,
-    int nnodes,
-    _In_count_(nnodes) int* index,
-    _In_ int* edges,
-    int reorder,
-    _Out_ MPI_Comm* comm_cart
-    );
-int
-MPIAPI
-PMPI_Graph_create(
-    MPI_Comm comm_old,
-    int nnodes,
-    _In_count_(nnodes) int* index,
-    _In_ int* edges,
-    int reorder,
-    _Out_ MPI_Comm* comm_cart
-    );
-
-
-/* Topology types */
-enum
-{
-    MPI_GRAPH   = 1,
-    MPI_CART    = 2
-};
-
-int
-MPIAPI
-MPI_Topo_test(
-    MPI_Comm comm,
-    _Out_ int* status
-    );
-int
-MPIAPI
-PMPI_Topo_test(
-    MPI_Comm comm,
-    _Out_ int* status
-    );
-
-int
-MPIAPI
-MPI_Graphdims_get(
-    MPI_Comm comm,
-    _Out_ int* nnodes,
-    _Out_ int* nedges
-    );
-int
-MPIAPI
-PMPI_Graphdims_get(
-    MPI_Comm comm,
-    _Out_ int* nnodes,
-    _Out_ int* nedges
-    );
-
-int
-MPIAPI
-MPI_Graph_get(
-    MPI_Comm comm,
-    int maxindex,
-    int maxedges,
-    _Out_cap_(maxindex) int* index,
-    _Out_cap_(maxedges) int* edges
-    );
-int
-MPIAPI
-PMPI_Graph_get(
-    MPI_Comm comm,
-    int maxindex,
-    int maxedges,
-    _Out_cap_(maxindex) int* index,
-    _Out_cap_(maxedges) int* edges
-    );
-
-int
-MPIAPI
-MPI_Cartdim_get(
-    MPI_Comm comm,
-    _Out_ int* ndims
-    );
-int
-MPIAPI
-PMPI_Cartdim_get(
-    MPI_Comm comm,
-    _Out_ int* ndims
-    );
-
-int
-MPIAPI
-MPI_Cart_get(
-    MPI_Comm comm,
-    int maxdims,
-    _Out_cap_(maxdims) int* dims,
-    _Out_cap_(maxdims) int* periods,
-    _Out_cap_(maxdims) int* coords
-    );
-int
-MPIAPI
-PMPI_Cart_get(
-    MPI_Comm comm,
-    int maxdims,
-    _Out_cap_(maxdims) int* dims,
-    _Out_cap_(maxdims) int* periods,
-    _Out_cap_(maxdims) int* coords
-    );
-
-int
-MPIAPI
-MPI_Cart_rank(
-    MPI_Comm comm,
-    _In_ int* coords,
-    _Out_ int* rank
-    );
-int
-MPIAPI
-PMPI_Cart_rank(
-    MPI_Comm comm,
-    _In_ int* coords,
-    _Out_ int* rank
-    );
-
-int
-MPIAPI
-MPI_Cart_coords(
-    MPI_Comm comm,
-    int rank,
-    int maxdims,
-    _Out_cap_(maxdims) int* coords
-    );
-int
-MPIAPI
-PMPI_Cart_coords(
-    MPI_Comm comm,
-    int rank,
-    int maxdims,
-    _Out_cap_(maxdims) int* coords
-    );
-
-int
-MPIAPI
-MPI_Graph_neighbors_count(
-    MPI_Comm comm,
-    int rank,
-    _Out_ int* nneighbors
-    );
-int
-MPIAPI
-PMPI_Graph_neighbors_count(
-    MPI_Comm comm,
-    int rank,
-    _Out_ int* nneighbors
-    );
-
-int
-MPIAPI
-MPI_Graph_neighbors(
-    MPI_Comm comm,
-    int rank,
-    int maxneighbors,
-    _Out_cap_(maxneighbors) int* neighbors
-    );
-int
-MPIAPI
-PMPI_Graph_neighbors(
-    MPI_Comm comm,
-    int rank,
-    int maxneighbors,
-    _Out_cap_(maxneighbors) int* neighbors
-    );
-
-int
-MPIAPI
-MPI_Cart_shift(
-    MPI_Comm comm,
-    int direction,
-    int disp,
-    _Out_ int* rank_source,
-    _Out_ int* rank_dest
-    );
-int
-MPIAPI
-PMPI_Cart_shift(
-    MPI_Comm comm,
-    int direction,
-    int disp,
-    _Out_ int* rank_source,
-    _Out_ int* rank_dest
-    );
-
-int
-MPIAPI
-MPI_Cart_sub(
-    MPI_Comm comm,
-    _In_ int* remain_dims,
-    _Out_ MPI_Comm* newcomm
-    );
-int
-MPIAPI
-PMPI_Cart_sub(
-    MPI_Comm comm,
-    _In_ int* remain_dims,
-    _Out_ MPI_Comm* newcomm
-    );
-
-int
-MPIAPI
-MPI_Cart_map(
-    MPI_Comm comm,
-    int ndims,
-    _In_count_(ndims) int* dims,
-    _In_count_(ndims) int* periods,
-    _Out_ int* newrank
-    );
-int
-MPIAPI
-PMPI_Cart_map(
-    MPI_Comm comm,
-    int ndims,
-    _In_count_(ndims) int* dims,
-    _In_count_(ndims) int* periods,
-    _Out_ int* newrank
-    );
-
-int
-MPIAPI
-MPI_Graph_map(
-    MPI_Comm comm,
-    int nnodes,
-    _In_count_(nnodes) int* index,
-    _In_ int* edges,
-    _Out_ int* newrank
-    );
-int
-MPIAPI
-PMPI_Graph_map(
-    MPI_Comm comm,
-    int nnodes,
-    _In_count_(nnodes) int* index,
-    _In_ int* edges,
-    _Out_ int* newrank
-    );
-
-
-/*---------------------------------------------------------------------------*/
-/* Chapter 8: Environmental Management                                       */
-/*---------------------------------------------------------------------------*/
-
-/*---------------------------------------------*/
-/* Section 8.1: Implementation Information     */
-/*---------------------------------------------*/
-
-#define MPI_VERSION     2
-#define MPI_SUBVERSION  0
-
-int
-MPIAPI
-MPI_Get_version(
-    _Out_ int* version,
-    _Out_ int* subversion
-    );
-int
-MPIAPI
-PMPI_Get_version(
-    _Out_ int* version,
-    _Out_ int* subversion
-    );
-
-#define MPI_MAX_PROCESSOR_NAME  128
-
-int
-MPIAPI
-MPI_Get_processor_name(
-    _Out_z_cap_post_count_(MPI_MAX_PROCESSOR_NAME,*resultlen) char* name,
-    _Out_ int* resultlen
-    );
-int
-MPIAPI
-PMPI_Get_processor_name(
-    _Out_z_cap_post_count_(MPI_MAX_PROCESSOR_NAME,*resultlen) char* name,
-    _Out_ int* resultlen
-    );
-
-/*---------------------------------------------*/
-/* Section 8.2: Memory Allocation              */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Alloc_mem(
-    MPI_Aint size,
-    MPI_Info info,
-    _Out_ void* baseptr
-    );
-int
-MPIAPI
-PMPI_Alloc_mem(
-    MPI_Aint size,
-    MPI_Info info,
-    _Out_ void* baseptr
-    );
-
-int
-MPIAPI
-MPI_Free_mem(
-    _In_ void* base
-    );
-int
-MPIAPI
-PMPI_Free_mem(
-    _In_ void* base
-    );
-
-
-/*---------------------------------------------*/
-/* Section 8.3: Error Handling                 */
-/*---------------------------------------------*/
-
-typedef
-void
-(MPIAPI MPI_Comm_errhandler_fn)(
-    _In_ MPI_Comm* comm,
-    _Inout_ int* errcode,
-    ...
-    );
-
-int
-MPIAPI
-MPI_Comm_create_errhandler(
-    _In_ MPI_Comm_errhandler_fn* function,
-    _Out_ MPI_Errhandler* errhandler
-    );
-int
-MPIAPI
-PMPI_Comm_create_errhandler(
-    _In_ MPI_Comm_errhandler_fn* function,
-    _Out_ MPI_Errhandler* errhandler
-    );
-
-int
-MPIAPI
-MPI_Comm_set_errhandler(
-    MPI_Comm comm,
-    MPI_Errhandler errhandler
-    );
-int
-MPIAPI
-PMPI_Comm_set_errhandler(
-    MPI_Comm comm,
-    MPI_Errhandler errhandler
-    );
-
-int
-MPIAPI
-MPI_Comm_get_errhandler(
-    MPI_Comm comm,
-    _Out_ MPI_Errhandler* errhandler
-    );
-int
-MPIAPI
-PMPI_Comm_get_errhandler(
-    MPI_Comm comm,
-    _Out_ MPI_Errhandler* errhandler
-    );
-
-
-typedef
-void
-(MPIAPI MPI_Win_errhandler_fn)(
-    _In_ MPI_Win* win,
-    _Inout_ int* errcode,
-    ...
-    );
-
-int
-MPIAPI
-MPI_Win_create_errhandler(
-    _In_ MPI_Win_errhandler_fn* function,
-    _Out_ MPI_Errhandler* errhandler
-    );
-int
-MPIAPI
-PMPI_Win_create_errhandler(
-    _In_ MPI_Win_errhandler_fn* function,
-    _Out_ MPI_Errhandler* errhandler
-    );
-
-int
-MPIAPI
-MPI_Win_set_errhandler(
-    MPI_Win win,
-    MPI_Errhandler errhandler
-    );
-int
-MPIAPI
-PMPI_Win_set_errhandler(
-    MPI_Win win,
-    MPI_Errhandler errhandler
-    );
-
-int
-MPIAPI
-MPI_Win_get_errhandler(
-    MPI_Win win,
-    _Out_ MPI_Errhandler* errhandler
-    );
-int
-MPIAPI
-PMPI_Win_get_errhandler(
-    MPI_Win win,
-    _Out_ MPI_Errhandler* errhandler
-    );
-
-
-typedef
-void
-(MPIAPI MPI_File_errhandler_fn)(
-    _In_ MPI_File* file,
-    _Inout_ int* errcode,
-    ...
-    );
-
-int
-MPIAPI
-MPI_File_create_errhandler(
-    _In_ MPI_File_errhandler_fn* function,
-    _Out_ MPI_Errhandler* errhandler
-    );
-int
-MPIAPI
-PMPI_File_create_errhandler(
-    _In_ MPI_File_errhandler_fn* function,
-    _Out_ MPI_Errhandler* errhandler
-    );
-
-int
-MPIAPI
-MPI_File_set_errhandler(
-    MPI_File file,
-    MPI_Errhandler errhandler
-    );
-int
-MPIAPI
-PMPI_File_set_errhandler(
-    MPI_File file,
-    MPI_Errhandler errhandler
-    );
-
-int
-MPIAPI
-MPI_File_get_errhandler(
-    MPI_File file,
-    _Out_ MPI_Errhandler* errhandler
-    );
-int
-MPIAPI
-PMPI_File_get_errhandler(
-    MPI_File file,
-    _Out_ MPI_Errhandler* errhandler
-    );
-
-int
-MPIAPI
-MPI_Errhandler_free(
-    _Inout_ MPI_Errhandler* errhandler
-    );
-int
-MPIAPI
-PMPI_Errhandler_free(
-    _Inout_ MPI_Errhandler* errhandler
-    );
-
-#define MPI_MAX_ERROR_STRING    512
-
-int
-MPIAPI
-MPI_Error_string(
-    int errorcode,
-    _Out_z_cap_post_count_(MPI_MAX_ERROR_STRING,*resultlen) char* string,
-    _Out_ int* resultlen
-    );
-int
-MPIAPI
-PMPI_Error_string(
-    int errorcode,
-    _Out_z_cap_post_count_(MPI_MAX_ERROR_STRING,*resultlen) char* string,
-    _Out_ int* resultlen
-    );
-
-
-/*---------------------------------------------*/
-/* Section 8.4: Error Codes and Classes        */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Error_class(
-    int errorcode,
-    _Out_ int* errorclass
-    );
-int
-MPIAPI
-PMPI_Error_class(
-    int errorcode,
-    _Out_ int* errorclass
-    );
-
-int
-MPIAPI
-MPI_Add_error_class(
-    _Out_ int* errorclass
-    );
-int
-MPIAPI
-PMPI_Add_error_class(
-    _Out_ int* errorclass
-    );
-
-int
-MPIAPI
-MPI_Add_error_code(
-    int errorclass,
-    _Out_ int* errorcode
-    );
-int
-MPIAPI
-PMPI_Add_error_code(
-    int errorclass,
-    _Out_ int* errorcode
-    );
-
-int
-MPIAPI
-MPI_Add_error_string(
-    int errorcode,
-    _In_z_ char* string
-    );
-int
-MPIAPI
-PMPI_Add_error_string(
-    int errorcode,
-    _In_z_ char* string
-    );
-
-int
-MPIAPI
-MPI_Comm_call_errhandler(
-    MPI_Comm comm,
-    int errorcode
-    );
-int
-MPIAPI
-PMPI_Comm_call_errhandler(
-    MPI_Comm comm,
-    int errorcode
-    );
-
-int
-MPIAPI
-MPI_Win_call_errhandler(
-    MPI_Win win,
-    int errcode
-    );
-int
-MPIAPI
-PMPI_Win_call_errhandler(
-    MPI_Win win,
-    int errcode
-    );
-
-int
-MPIAPI
-MPI_File_call_errhandler(
-    MPI_File file,
-    int errorcode
-    );
-int
-MPIAPI
-PMPI_File_call_errhandler(
-    MPI_File file,
-    int errorcode
-    );
-
-
-/*---------------------------------------------*/
-/* Section 8.6: Timers and Synchronization     */
-/*---------------------------------------------*/
-
-double
-MPIAPI
-MPI_Wtime(
-    void
-    );
-double
-MPIAPI
-PMPI_Wtime(
-    void
-    );
-
-double
-MPIAPI
-MPI_Wtick(
-    void
-    );
-double
-MPIAPI
-PMPI_Wtick(
-    void
-    );
-
-
-/*---------------------------------------------*/
-/* Section 8.7: Startup                        */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Init(
-    _In_opt_ int* argc,
-    _In_opt_count_(*argc) char*** argv
-    );
-int
-MPIAPI
-PMPI_Init(
-    _In_opt_ int* argc,
-    _In_opt_count_(*argc) char*** argv
-    );
-
-int
-MPIAPI
-MPI_Finalize(
-    void
-    );
-int
-MPIAPI
-PMPI_Finalize(
-    void
-    );
-
-int
-MPIAPI
-MPI_Initialized(
-    _Out_ int* flag
-    );
-int
-MPIAPI
-PMPI_Initialized(
-    _Out_ int* flag
-    );
-
-int
-MPIAPI
-MPI_Abort(
-    MPI_Comm comm,
-    int errorcode
-    );
-int
-MPIAPI
-PMPI_Abort(
-    MPI_Comm comm,
-    int errorcode
-    );
-
-int
-MPIAPI
-MPI_Finalized(
-    _Out_ int* flag
-    );
-int
-MPIAPI
-PMPI_Finalized(
-    _Out_ int* flag
-    );
-
-
-/*---------------------------------------------------------------------------*/
-/* Chapter 9: The Info Object                                                */
-/*---------------------------------------------------------------------------*/
-
-#define MPI_MAX_INFO_KEY    255
-#define MPI_MAX_INFO_VAL   1024
-
-int
-MPIAPI
-MPI_Info_create(
-    _Out_ MPI_Info* info
-    );
-int
-MPIAPI
-PMPI_Info_create(
-    _Out_ MPI_Info* info
-    );
-
-int
-MPIAPI
-MPI_Info_set(
-    MPI_Info info,
-    _In_z_ char* key,
-    _In_z_ char* value
-    );
-int
-MPIAPI
-PMPI_Info_set(
-    MPI_Info info,
-    _In_z_ char* key,
-    _In_z_ char* value
-    );
-
-int
-MPIAPI
-MPI_Info_delete(
-    MPI_Info info,
-    _In_z_ char* key
-    );
-int
-MPIAPI
-PMPI_Info_delete(
-    MPI_Info info,
-    _In_z_ char* key
-    );
-
-int
-MPIAPI
-MPI_Info_get(
-    MPI_Info info,
-    _In_z_ char* key,
-    int valuelen,
-    _Out_z_cap_(valuelen) char* value,
-    _Out_ int* flag
-    );
-int
-MPIAPI
-PMPI_Info_get(
-    MPI_Info info,
-    _In_z_ char* key,
-    int valuelen,
-    _Out_z_cap_(valuelen) char* value,
-    _Out_ int* flag
-    );
-
-int
-MPIAPI
-MPI_Info_get_valuelen(
-    MPI_Info info,
-    _In_z_ char* key,
-    _Out_ int* valuelen,
-    _Out_ int* flag
-    );
-int
-MPIAPI
-PMPI_Info_get_valuelen(
-    MPI_Info info,
-    _In_z_ char* key,
-    _Out_ int* valuelen,
-    _Out_ int* flag
-    );
-
-int
-MPIAPI
-MPI_Info_get_nkeys(
-    MPI_Info info,
-    _Out_ int* nkeys
-    );
-int
-MPIAPI
-PMPI_Info_get_nkeys(
-    MPI_Info info,
-    _Out_ int* nkeys
-    );
-
-int
-MPIAPI
-MPI_Info_get_nthkey(
-    MPI_Info info,
-    int n,
-    _Out_z_cap_(MPI_MAX_INFO_KEY) char* key
-    );
-int
-MPIAPI
-PMPI_Info_get_nthkey(
-    MPI_Info info,
-    int n,
-    _Out_z_cap_(MPI_MAX_INFO_KEY) char* key
-    );
-
-int
-MPIAPI
-MPI_Info_dup(
-    MPI_Info info,
-    _Out_ MPI_Info* newinfo
-    );
-int
-MPIAPI
-PMPI_Info_dup(
-    MPI_Info info,
-    _Out_ MPI_Info* newinfo
-    );
-
-int
-MPIAPI
-MPI_Info_free(
-    _Inout_ MPI_Info* info
-    );
-int
-MPIAPI
-PMPI_Info_free(
-    _Inout_ MPI_Info* info
-    );
-
-
-/*---------------------------------------------------------------------------*/
-/* Chapter 10: Process Creation and Management                               */
-/*---------------------------------------------------------------------------*/
-
-/*---------------------------------------------*/
-/* Section 10.3: Process Manager Interface     */
-/*---------------------------------------------*/
-
-#define MPI_ARGV_NULL ((char**)0)
-#define MPI_ARGVS_NULL ((char***)0)
-
-#define MPI_ERRCODES_IGNORE ((int*)0)
-
-int
-MPIAPI
-MPI_Comm_spawn(
-    _In_z_ char* command,
-    _In_ char* argv[],
-    int maxprocs,
-    MPI_Info info,
-    int root,
-    MPI_Comm comm,
-    _Out_ MPI_Comm* intercomm,
-    _Out_opt_cap_(maxprocs) int array_of_errcodes[]
-    );
-int
-MPIAPI
-PMPI_Comm_spawn(
-    _In_z_ char* command,
-    _In_ char* argv[],
-    int maxprocs,
-    MPI_Info info,
-    int root,
-    MPI_Comm comm,
-    _Out_ MPI_Comm* intercomm,
-    _Out_opt_cap_(maxprocs) int array_of_errcodes[]
-    );
-
-int
-MPIAPI
-MPI_Comm_get_parent(
-    _Out_ MPI_Comm* parent
-    );
-int
-MPIAPI
-PMPI_Comm_get_parent(
-    _Out_ MPI_Comm* parent
-    );
-
-int
-MPIAPI
-MPI_Comm_spawn_multiple(
-    int count,
-    _In_count_(count) char* array_of_commands[],
-    _In_opt_count_(count) char** array_of_argv[],
-    _In_count_(count) int array_of_maxprocs[],
-    _In_count_(count) MPI_Info array_of_info[],
-    int root,
-    MPI_Comm comm,
-    _Out_ MPI_Comm* intercomm,
-    _Out_opt_ int array_of_errcodes[]
-    );
-int
-MPIAPI
-PMPI_Comm_spawn_multiple(
-    int count,
-    _In_count_(count) char* array_of_commands[],
-    _In_opt_count_(count) char** array_of_argv[],
-    _In_count_(count) int array_of_maxprocs[],
-    _In_count_(count) MPI_Info array_of_info[],
-    int root,
-    MPI_Comm comm,
-    _Out_ MPI_Comm* intercomm,
-    _Out_opt_ int array_of_errcodes[]
-    );
-
-
-/*---------------------------------------------*/
-/* Section 10.4: Establishing Communication    */
-/*---------------------------------------------*/
-
-#define MPI_MAX_PORT_NAME   256
-
-int
-MPIAPI
-MPI_Open_port(
-    MPI_Info info,
-    _Out_cap_(MPI_MAX_PORT_NAME) char* port_name
-    );
-int
-MPIAPI
-PMPI_Open_port(
-    MPI_Info info,
-    _Out_cap_(MPI_MAX_PORT_NAME) char* port_name
-    );
-
-int
-MPIAPI
-MPI_Close_port(
-    _In_z_ char* port_name
-    );
-int
-MPIAPI
-PMPI_Close_port(
-    _In_z_ char* port_name
-    );
-
-int
-MPIAPI
-MPI_Comm_accept(
-    _In_z_ char* port_name,
-    MPI_Info info,
-    int root,
-    MPI_Comm comm,
-    _Out_ MPI_Comm* newcomm
-    );
-int
-MPIAPI
-PMPI_Comm_accept(
-    _In_z_ char* port_name,
-    MPI_Info info,
-    int root,
-    MPI_Comm comm,
-    _Out_ MPI_Comm* newcomm
-    );
-
-int
-MPIAPI
-MPI_Comm_connect(
-    _In_z_ char* port_name,
-    MPI_Info info,
-    int root,
-    MPI_Comm comm,
-    _Out_ MPI_Comm* newcomm
-    );
-int
-MPIAPI
-PMPI_Comm_connect(
-    _In_z_ char* port_name,
-    MPI_Info info,
-    int root,
-    MPI_Comm comm,
-    _Out_ MPI_Comm* newcomm
-    );
-
-
-/*---------------------------------------------*/
-/* Section 10.4.4: Name Publishing             */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Publish_name(
-    _In_z_ char* service_name,
-    MPI_Info info,
-    _In_z_ char* port_name
-    );
-int
-MPIAPI
-PMPI_Publish_name(
-    _In_z_ char* service_name,
-    MPI_Info info,
-    _In_z_ char* port_name
-    );
-
-int
-MPIAPI
-MPI_Unpublish_name(
-    _In_z_ char* service_name,
-    MPI_Info info,
-    _In_z_ char* port_name
-    );
-int
-MPIAPI
-PMPI_Unpublish_name(
-    _In_z_ char* service_name,
-    MPI_Info info,
-    _In_z_ char* port_name
-    );
-
-int
-MPIAPI
-MPI_Lookup_name(
-    _In_z_ char* service_name,
-    MPI_Info info,
-    _Out_cap_(MPI_MAX_PORT_NAME) char* port_name
-    );
-int
-MPIAPI
-PMPI_Lookup_name(
-    _In_z_ char* service_name,
-    MPI_Info info,
-    _Out_cap_(MPI_MAX_PORT_NAME) char* port_name
-    );
-
-
-/*---------------------------------------------*/
-/* Section 10.5: Other Functionality           */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Comm_disconnect(
-    _In_ MPI_Comm* comm
-    );
-int
-MPIAPI
-PMPI_Comm_disconnect(
-    _In_ MPI_Comm* comm
-    );
-
-int
-MPIAPI
-MPI_Comm_join(
-    int fd,
-    _Out_ MPI_Comm* intercomm
-    );
-int
-MPIAPI
-PMPI_Comm_join(
-    int fd,
-    _Out_ MPI_Comm* intercomm
-    );
-
-
-/*---------------------------------------------------------------------------*/
-/* Chapter 11: One-Sided Communications                                      */
-/*---------------------------------------------------------------------------*/
-
-int
-MPIAPI
-MPI_Win_create(
-    _In_ void* base,
-    MPI_Aint size,
-    int disp_unit,
-    MPI_Info info,
-    MPI_Comm comm,
-    _Out_ MPI_Win* win
-    );
-int
-MPIAPI
-PMPI_Win_create(
-    _In_ void* base,
-    MPI_Aint size,
-    int disp_unit,
-    MPI_Info info,
-    MPI_Comm comm,
-    _Out_ MPI_Win* win
-    );
-
-int
-MPIAPI
-MPI_Win_free(
-    _Inout_ MPI_Win* win
-    );
-int
-MPIAPI
-PMPI_Win_free(
-    _Inout_ MPI_Win* win
-    );
-
-int
-MPIAPI
-MPI_Win_get_group(
-    MPI_Win win,
-    _Out_ MPI_Group* group
-    );
-int
-MPIAPI
-PMPI_Win_get_group(
-    MPI_Win win,
-    _Out_ MPI_Group* group
-    );
-
-int
-MPIAPI
-MPI_Put(
-    _In_ void* origin_addr,
-    int origin_count,
-    MPI_Datatype origin_datatype,
-    int target_rank,
-    MPI_Aint target_disp,
-    int target_count,
-    MPI_Datatype datatype,
-    MPI_Win win
-    );
-int
-MPIAPI
-PMPI_Put(
-    _In_ void* origin_addr,
-    int origin_count,
-    MPI_Datatype origin_datatype,
-    int target_rank,
-    MPI_Aint target_disp,
-    int target_count,
-    MPI_Datatype datatype,
-    MPI_Win win
-    );
-
-int
-MPIAPI
-MPI_Get(
-    _Out_ void* origin_addr,
-    int origin_count,
-    MPI_Datatype origin_datatype,
-    int target_rank,
-    MPI_Aint target_disp,
-    int target_count,
-    MPI_Datatype datatype,
-    MPI_Win win
-    );
-int
-MPIAPI
-PMPI_Get(
-    _Out_ void* origin_addr,
-    int origin_count,
-    MPI_Datatype origin_datatype,
-    int target_rank,
-    MPI_Aint target_disp,
-    int target_count,
-    MPI_Datatype datatype,
-    MPI_Win win
-    );
-
-int
-MPIAPI
-MPI_Accumulate(
-    _In_ void* origin_addr,
-    int origin_count,
-    MPI_Datatype origin_datatype,
-    int target_rank,
-    MPI_Aint target_disp,
-    int target_count,
-    MPI_Datatype datatype,
-    MPI_Op op,
-    MPI_Win win
-    );
-int
-MPIAPI
-PMPI_Accumulate(
-    _In_ void* origin_addr,
-    int origin_count,
-    MPI_Datatype origin_datatype,
-    int target_rank,
-    MPI_Aint target_disp,
-    int target_count,
-    MPI_Datatype datatype,
-    MPI_Op op,
-    MPI_Win win
-    );
-
-/* Asserts for one-sided communication */
-#define MPI_MODE_NOCHECK    1024
-#define MPI_MODE_NOSTORE    2048
-#define MPI_MODE_NOPUT      4096
-#define MPI_MODE_NOPRECEDE  8192
-#define MPI_MODE_NOSUCCEED 16384
-
-int
-MPIAPI
-MPI_Win_fence(
-    int assert,
-    MPI_Win win
-    );
-int
-MPIAPI
-PMPI_Win_fence(
-    int assert,
-    MPI_Win win
-    );
-
-int
-MPIAPI
-MPI_Win_start(
-    MPI_Group group,
-    int assert,
-    MPI_Win win
-    );
-int
-MPIAPI
-PMPI_Win_start(
-    MPI_Group group,
-    int assert,
-    MPI_Win win
-    );
-
-int
-MPIAPI
-MPI_Win_complete(
-    MPI_Win win
-    );
-int
-MPIAPI
-PMPI_Win_complete(
-    MPI_Win win
-    );
-
-int
-MPIAPI
-MPI_Win_post(
-    MPI_Group group,
-    int assert,
-    MPI_Win win
-    );
-int
-MPIAPI
-PMPI_Win_post(
-    MPI_Group group,
-    int assert,
-    MPI_Win win
-    );
-
-int
-MPIAPI
-MPI_Win_wait(
-    MPI_Win win
-    );
-int
-MPIAPI
-PMPI_Win_wait(
-    MPI_Win win
-    );
-
-int
-MPIAPI
-MPI_Win_test(
-    MPI_Win win,
-    _Out_ int* flag
-    );
-int
-MPIAPI
-PMPI_Win_test(
-    MPI_Win win,
-    _Out_ int* flag
-    );
-
-#define MPI_LOCK_EXCLUSIVE  234
-#define MPI_LOCK_SHARED     235
-
-int
-MPIAPI
-MPI_Win_lock(
-    int lock_type,
-    int rank,
-    int assert,
-    MPI_Win win
-    );
-int
-MPIAPI
-PMPI_Win_lock(
-    int lock_type,
-    int rank,
-    int assert,
-    MPI_Win win
-    );
-
-int
-MPIAPI
-MPI_Win_unlock(
-    int rank,
-    MPI_Win win
-    );
-int
-MPIAPI
-PMPI_Win_unlock(
-    int rank,
-    MPI_Win win
-    );
-
-
-/*---------------------------------------------------------------------------*/
-/* Chapter 12: External Interfaces                                           */
-/*---------------------------------------------------------------------------*/
-
-/*---------------------------------------------*/
-/* Section 12.2: Generalized Requests          */
-/*---------------------------------------------*/
-
-typedef
-int
-(MPIAPI MPI_Grequest_query_function)(
-    _In_opt_ void* extra_state,
-    _Out_ MPI_Status* status
-    );
-
-typedef
-int
-(MPIAPI MPI_Grequest_free_function)(
-    _In_opt_ void* extra_state
-    );
-
-typedef
-int
-(MPIAPI MPI_Grequest_cancel_function)(
-    _In_opt_ void* extra_state,
-    int complete
-    );
-
-int
-MPIAPI
-MPI_Grequest_start(
-    _In_ MPI_Grequest_query_function* query_fn,
-    _In_ MPI_Grequest_free_function* free_fn,
-    _In_ MPI_Grequest_cancel_function* cancel_fn,
-    _In_opt_ void* extra_state,
-    _Out_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_Grequest_start(
-    _In_ MPI_Grequest_query_function* query_fn,
-    _In_ MPI_Grequest_free_function* free_fn,
-    _In_ MPI_Grequest_cancel_function* cancel_fn,
-    _In_opt_ void* extra_state,
-    _Out_ MPI_Request* request
-    );
-
-int
-MPIAPI
-MPI_Grequest_complete(
-    MPI_Request request
-    );
-int
-MPIAPI
-PMPI_Grequest_complete(
-    MPI_Request request
-    );
-
-
-/*---------------------------------------------*/
-/* Section 12.3: Information with Status       */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Status_set_elements(
-    _In_ MPI_Status* status,
-    MPI_Datatype datatype,
-    int count
-    );
-int
-MPIAPI
-PMPI_Status_set_elements(
-    _In_ MPI_Status* status,
-    MPI_Datatype datatype,
-    int count
-    );
-
-int
-MPIAPI
-MPI_Status_set_cancelled(
-    _In_ MPI_Status* status,
-    int flag
-    );
-int
-MPIAPI
-PMPI_Status_set_cancelled(
-    _In_ MPI_Status* status,
-    int flag
-    );
-
-
-/*---------------------------------------------*/
-/* Section 12.4: Threads                       */
-/*---------------------------------------------*/
-
-#define MPI_THREAD_SINGLE       0
-#define MPI_THREAD_FUNNELED     1
-#define MPI_THREAD_SERIALIZED   2
-#define MPI_THREAD_MULTIPLE     3
-
-int
-MPIAPI
-MPI_Init_thread(
-    _In_opt_ int* argc,
-    _In_opt_count_(*argc) char*** argv,
-    int required,
-    _Out_ int* provided
-    );
-int
-MPIAPI
-PMPI_Init_thread(
-    _In_opt_ int* argc,
-    _In_opt_count_(*argc) char*** argv,
-    int required,
-    _Out_ int* provided
-    );
-
-int
-MPIAPI
-MPI_Query_thread(
-    _Out_ int* provided
-    );
-int
-MPIAPI
-PMPI_Query_thread(
-    _Out_ int* provided
-    );
-
-int
-MPIAPI
-MPI_Is_thread_main(
-    _Out_ int* flag
-    );
-int
-MPIAPI
-PMPI_Is_thread_main(
-    _Out_ int* flag
-    );
-
-
-/*---------------------------------------------------------------------------*/
-/* Chapter 13: I/O                                                           */
-/*---------------------------------------------------------------------------*/
-
-/*---------------------------------------------*/
-/* Section 13.2: File Manipulation             */
-/*---------------------------------------------*/
-
-#define MPI_MODE_CREATE             0x00000001
-#define MPI_MODE_RDONLY             0x00000002
-#define MPI_MODE_WRONLY             0x00000004
-#define MPI_MODE_RDWR               0x00000008
-#define MPI_MODE_DELETE_ON_CLOSE    0x00000010
-#define MPI_MODE_UNIQUE_OPEN        0x00000020
-#define MPI_MODE_EXCL               0x00000040
-#define MPI_MODE_APPEND             0x00000080
-#define MPI_MODE_SEQUENTIAL         0x00000100
-#define MSMPI_MODE_HIDDEN           0x00000200
-
-int
-MPIAPI
-MPI_File_open(
-    MPI_Comm comm,
-    _In_z_ char* filename,
-    int amode,
-    MPI_Info info,
-    _Out_ MPI_File* newfile
-    );
-int
-MPIAPI
-PMPI_File_open(
-    MPI_Comm comm,
-    _In_z_ char* filename,
-    int amode,
-    MPI_Info info,
-    _Out_ MPI_File* newfile
-    );
-
-int
-MPIAPI
-MPI_File_close(
-    _In_ MPI_File* file
-    );
-int
-MPIAPI
-PMPI_File_close(
-    _In_ MPI_File* file
-    );
-
-int
-MPIAPI
-MPI_File_delete(
-    _In_z_ char* filename,
-    MPI_Info info
-    );
-int
-MPIAPI
-PMPI_File_delete(
-    _In_z_ char* filename,
-    MPI_Info info
-    );
-
-int
-MPIAPI
-MPI_File_set_size(
-    MPI_File file,
-    MPI_Offset size
-    );
-int
-MPIAPI
-PMPI_File_set_size(
-    MPI_File file,
-    MPI_Offset size
-    );
-
-int
-MPIAPI
-MPI_File_preallocate(
-    MPI_File file,
-    MPI_Offset size
-    );
-int
-MPIAPI
-PMPI_File_preallocate(
-    MPI_File file,
-    MPI_Offset size
-    );
-
-int
-MPIAPI
-MPI_File_get_size(
-    MPI_File file,
-    _Out_ MPI_Offset* size
-    );
-int
-MPIAPI
-PMPI_File_get_size(
-    MPI_File file,
-    _Out_ MPI_Offset* size
-    );
-
-int
-MPIAPI
-MPI_File_get_group(
-    MPI_File file,
-    _Out_ MPI_Group* group
-    );
-int
-MPIAPI
-PMPI_File_get_group(
-    MPI_File file,
-    _Out_ MPI_Group* group
-    );
-
-int
-MPIAPI
-MPI_File_get_amode(
-    MPI_File file,
-    _Out_ int* amode
-    );
-int
-MPIAPI
-PMPI_File_get_amode(
-    MPI_File file,
-    _Out_ int* amode
-    );
-
-int
-MPIAPI
-MPI_File_set_info(
-    MPI_File file,
-    MPI_Info info
-    );
-int
-MPIAPI
-PMPI_File_set_info(
-    MPI_File file,
-    MPI_Info info
-    );
-
-int
-MPIAPI
-MPI_File_get_info(
-    MPI_File file,
-    _Out_ MPI_Info* info
-    );
-int
-MPIAPI
-PMPI_File_get_info(
-    MPI_File file,
-    _Out_ MPI_Info* info
-    );
-
-
-/*---------------------------------------------*/
-/* Section 13.3: File Views                    */
-/*---------------------------------------------*/
-
-#define MPI_DISPLACEMENT_CURRENT (-54278278)
-
-int
-MPIAPI
-MPI_File_set_view(
-    MPI_File file,
-    MPI_Offset disp,
-    MPI_Datatype etype,
-    MPI_Datatype filetype,
-    _In_z_ char* datarep,
-    MPI_Info info
-    );
-int
-MPIAPI
-PMPI_File_set_view(
-    MPI_File file,
-    MPI_Offset disp,
-    MPI_Datatype etype,
-    MPI_Datatype filetype,
-    _In_z_ char* datarep,
-    MPI_Info info
-    );
-
-#define MPI_MAX_DATAREP_STRING  128
-
-int
-MPIAPI
-MPI_File_get_view(
-    MPI_File file,
-    _Out_ MPI_Offset* disp,
-    _Out_ MPI_Datatype* etype,
-    _Out_ MPI_Datatype* filetype,
-    _Out_z_cap_(MPI_MAX_DATAREP_STRING) char* datarep
-    );
-int
-MPIAPI
-PMPI_File_get_view(
-    MPI_File file,
-    _Out_ MPI_Offset* disp,
-    _Out_ MPI_Datatype* etype,
-    _Out_ MPI_Datatype* filetype,
-    _Out_z_cap_(MPI_MAX_DATAREP_STRING) char* datarep
-    );
-
-
-/*---------------------------------------------*/
-/* Section 13.4: Data Access                   */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_File_read_at(
-    MPI_File file,
-    MPI_Offset offset,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_File_read_at(
-    MPI_File file,
-    MPI_Offset offset,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_File_read_at_all(
-    MPI_File file,
-    MPI_Offset offset,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_File_read_at_all(
-    MPI_File file,
-    MPI_Offset offset,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_File_write_at(
-    MPI_File file,
-    MPI_Offset offset,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_File_write_at(
-    MPI_File file,
-    MPI_Offset offset,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_File_write_at_all(
-    MPI_File file,
-    MPI_Offset offset,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_File_write_at_all(
-    MPI_File file,
-    MPI_Offset offset,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_File_iread_at(
-    MPI_File file,
-    MPI_Offset offset,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_File_iread_at(
-    MPI_File file,
-    MPI_Offset offset,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Request* request
-    );
-
-int
-MPIAPI
-MPI_File_iwrite_at(
-    MPI_File file,
-    MPI_Offset offset,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_File_iwrite_at(
-    MPI_File file,
-    MPI_Offset offset,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Request* request
-    );
-
-int
-MPIAPI
-MPI_File_read(
-    MPI_File file,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_File_read(
-    MPI_File file,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_File_read_all(
-    MPI_File file,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_File_read_all(
-    MPI_File file,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_File_write(
-    MPI_File file,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_File_write(
-    MPI_File file,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_File_write_all(
-    MPI_File file,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_File_write_all(
-    MPI_File file,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-
-
-int
-MPIAPI
-MPI_File_iread(
-    MPI_File file,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_File_iread(
-    _In_ MPI_File file,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Request* request
-    );
-
-int
-MPIAPI
-MPI_File_iwrite(
-    MPI_File file,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_File_iwrite(
-    MPI_File file,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Request* request
-    );
-
-
-/* File seek whence */
-#define MPI_SEEK_SET    600
-#define MPI_SEEK_CUR    602
-#define MPI_SEEK_END    604
-
-int
-MPIAPI
-MPI_File_seek(
-    MPI_File file,
-    MPI_Offset offset,
-    int whence
-    );
-int
-MPIAPI
-PMPI_File_seek(
-    MPI_File file,
-    MPI_Offset offset,
-    int whence
-    );
-
-int
-MPIAPI
-MPI_File_get_position(
-    MPI_File file,
-    _Out_ MPI_Offset* offset
-    );
-int
-MPIAPI
-PMPI_File_get_position(
-    MPI_File file,
-    _Out_ MPI_Offset* offset
-    );
-
-int
-MPIAPI
-MPI_File_get_byte_offset(
-    MPI_File file,
-    MPI_Offset offset,
-    _Out_ MPI_Offset* disp
-    );
-int
-MPIAPI
-PMPI_File_get_byte_offset(
-    MPI_File file,
-    MPI_Offset offset,
-    _Out_ MPI_Offset* disp
-    );
-
-int
-MPIAPI
-MPI_File_read_shared(
-    MPI_File file,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-     );
-int
-MPIAPI
-PMPI_File_read_shared(
-    MPI_File file,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-     );
-
-int
-MPIAPI
-MPI_File_write_shared(
-    MPI_File file,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_File_write_shared(
-    MPI_File file,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_File_iread_shared(
-    MPI_File file,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_File_iread_shared(
-    MPI_File file,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Request* request
-    );
-
-int
-MPIAPI
-MPI_File_iwrite_shared(
-    MPI_File file,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_File_iwrite_shared(
-    MPI_File file,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Request* request
-    );
-
-int
-MPIAPI
-MPI_File_read_ordered(
-    MPI_File file,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_File_read_ordered(
-    MPI_File file,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_File_write_ordered(
-    _In_ MPI_File file,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_File_write_ordered(
-    MPI_File file,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_File_seek_shared(
-    MPI_File file,
-    MPI_Offset offset,
-    int whence
-    );
-int
-MPIAPI
-PMPI_File_seek_shared(
-    MPI_File file,
-    MPI_Offset offset,
-    int whence
-    );
-
-int
-MPIAPI
-MPI_File_get_position_shared(
-    MPI_File file,
-    _Out_ MPI_Offset* offset
-    );
-int
-MPIAPI
-PMPI_File_get_position_shared(
-    MPI_File file,
-    _Out_ MPI_Offset* offset
-    );
-
-int
-MPIAPI
-MPI_File_read_at_all_begin(
-    MPI_File file,
-    MPI_Offset offset,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype
-    );
-int
-MPIAPI
-PMPI_File_read_at_all_begin(
-    MPI_File file,
-    MPI_Offset offset,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype
-    );
-
-int
-MPIAPI
-MPI_File_read_at_all_end(
-    MPI_File file,
-    _Out_ void* buf,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_File_read_at_all_end(
-    MPI_File file,
-    _Out_ void* buf,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_File_write_at_all_begin(
-    MPI_File file,
-    MPI_Offset offset,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype
-    );
-int
-MPIAPI
-PMPI_File_write_at_all_begin(
-    MPI_File file,
-    MPI_Offset offset,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype
-    );
-
-int
-MPIAPI
-MPI_File_write_at_all_end(
-    MPI_File file,
-    _In_ void* buf,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_File_write_at_all_end(
-    MPI_File file,
-    _In_ void* buf,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_File_read_all_begin(
-    MPI_File file,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype
-    );
-int
-MPIAPI
-PMPI_File_read_all_begin(
-    MPI_File file,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype
-    );
-
-int
-MPIAPI
-MPI_File_read_all_end(
-    MPI_File file,
-    _Out_ void* buf,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_File_read_all_end(
-    MPI_File file,
-    _Out_ void* buf,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_File_write_all_begin(
-    MPI_File file,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype
-    );
-int
-MPIAPI
-PMPI_File_write_all_begin(
-    MPI_File file,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype
-    );
-
-int
-MPIAPI
-MPI_File_write_all_end(
-    MPI_File file,
-    _In_ void* buf,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_File_write_all_end(
-    MPI_File file,
-    _In_ void* buf,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_File_read_ordered_begin(
-    MPI_File file,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype
-    );
-int
-MPIAPI
-PMPI_File_read_ordered_begin(
-    MPI_File file,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype
-    );
-
-int
-MPIAPI
-MPI_File_read_ordered_end(
-    MPI_File file,
-    _Out_ void* buf,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_File_read_ordered_end(
-    MPI_File file,
-    _Out_ void* buf,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_File_write_ordered_begin(
-    MPI_File file,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype
-    );
-int
-MPIAPI
-PMPI_File_write_ordered_begin(
-    MPI_File file,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype
-    );
-
-int
-MPIAPI
-MPI_File_write_ordered_end(
-    MPI_File file,
-    _In_ void* buf,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_File_write_ordered_end(
-    MPI_File file,
-    _In_ void* buf,
-    _Out_ MPI_Status* status
-    );
-
-
-/*---------------------------------------------*/
-/* Section 13.5: File Interoperability         */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_File_get_type_extent(
-    MPI_File file,
-    MPI_Datatype datatype,
-    _Out_ MPI_Aint* extent
-    );
-int
-MPIAPI
-PMPI_File_get_type_extent(
-    MPI_File file,
-    MPI_Datatype datatype,
-    _Out_ MPI_Aint* extent
-    );
-
-
-typedef
-int
-(MPIAPI MPI_Datarep_conversion_function)(
-    _Inout_ void* userbuf,
-    MPI_Datatype datatype,
-    int count,
-    _Inout_ void* filebuf,
-    MPI_Offset position,
-    _In_ void* extra_state
-    );
-
-typedef
-int
-(MPIAPI MPI_Datarep_extent_function)(
-    MPI_Datatype datatype,
-    _Out_ MPI_Aint* file_extent,
-    _In_ void* extra_state
-    );
-
-#define MPI_CONVERSION_FN_NULL ((MPI_Datarep_conversion_function*)0)
-
-int
-MPIAPI
-MPI_Register_datarep(
-    _In_z_ char* datarep,
-    _In_opt_ MPI_Datarep_conversion_function* read_conversion_fn,
-    _In_opt_ MPI_Datarep_conversion_function* write_conversion_fn,
-    _In_ MPI_Datarep_extent_function* dtype_file_extent_fn,
-    _In_opt_ void* extra_state
-    );
-int
-MPIAPI
-PMPI_Register_datarep(
-    _In_z_ char* datarep,
-    _In_opt_ MPI_Datarep_conversion_function* read_conversion_fn,
-    _In_opt_ MPI_Datarep_conversion_function* write_conversion_fn,
-    _In_ MPI_Datarep_extent_function* dtype_file_extent_fn,
-    _In_opt_ void* extra_state
-    );
-
-
-/*---------------------------------------------*/
-/* Section 13.6: Consistency and Semantics     */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_File_set_atomicity(
-    MPI_File file,
-    int flag
-    );
-int
-MPIAPI
-PMPI_File_set_atomicity(
-    MPI_File file,
-    int flag
-    );
-
-int
-MPIAPI
-MPI_File_get_atomicity(
-    MPI_File file,
-    _Out_ int* flag
-    );
-int
-MPIAPI
-PMPI_File_get_atomicity(
-    MPI_File file,
-    _Out_ int* flag
-    );
-
-int
-MPIAPI
-MPI_File_sync(
-    MPI_File file
-    );
-int
-MPIAPI
-PMPI_File_sync(
-    MPI_File file
-    );
-
-
-/*---------------------------------------------------------------------------*/
-/* Chapter 14: Profiling Interface                                           */
-/*---------------------------------------------------------------------------*/
-
-int
-MPIAPI
-MPI_Pcontrol(
-    const int level,
-    ...);
-int
-MPIAPI
-PMPI_Pcontrol(
-    const int level,
-    ...);
-
-
-/*---------------------------------------------------------------------------*/
-/* Chapter 15: Depricated Functions                                          */
-/*---------------------------------------------------------------------------*/
-
-#ifdef MSMPI_NO_DEPRECATE_20
-#define MSMPI_DEPRECATE_20( x )
-#else
-#define MSMPI_DEPRECATE_20( x ) __declspec(deprecated( \
-    "Deprecated in MPI 2.0, use '" #x "'.  " \
-    "To disable deprecation, define MSMPI_NO_DEPRECATE_20." ))
-#endif
-
-MSMPI_DEPRECATE_20( MPI_Type_create_hvector )
-int
-MPIAPI
-MPI_Type_hvector(
-    int count,
-    int blocklength,
-    MPI_Aint stride,
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-MSMPI_DEPRECATE_20( PMPI_Type_create_hvector )
-int
-MPIAPI
-PMPI_Type_hvector(
-    int count,
-    int blocklength,
-    MPI_Aint stride,
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-
-MSMPI_DEPRECATE_20( MPI_Type_create_hindexed )
-int
-MPIAPI
-MPI_Type_hindexed(
-    int count,
-    _In_count_(count) int array_of_blocklengths[],
-    _In_count_(count) MPI_Aint array_of_displacements[],
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-MSMPI_DEPRECATE_20( PMPI_Type_create_hindexed )
-int
-MPIAPI
-PMPI_Type_hindexed(
-    int count,
-    _In_count_(count) int array_of_blocklengths[],
-    _In_count_(count) MPI_Aint array_of_displacements[],
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-
-MSMPI_DEPRECATE_20( MPI_Type_create_struct )
-int
-MPIAPI
-MPI_Type_struct(
-    int count,
-    _In_count_(count) int array_of_blocklengths[],
-    _In_count_(count) MPI_Aint array_of_displacements[],
-    _In_count_(count) MPI_Datatype array_of_types[],
-    _In_ MPI_Datatype* newtype
-    );
-MSMPI_DEPRECATE_20( PMPI_Type_create_struct )
-int
-MPIAPI
-PMPI_Type_struct(
-    int count,
-    _In_count_(count) int array_of_blocklengths[],
-    _In_count_(count) MPI_Aint array_of_displacements[],
-    _In_count_(count) MPI_Datatype array_of_types[],
-    _In_ MPI_Datatype* newtype
-    );
-
-MSMPI_DEPRECATE_20( MPI_Get_address )
-int
-MPIAPI
-MPI_Address(
-    _In_ void* location,
-    _Out_ MPI_Aint* address
-    );
-MSMPI_DEPRECATE_20( PMPI_Get_address )
-int
-MPIAPI
-PMPI_Address(
-    _In_ void* location,
-    _Out_ MPI_Aint* address
-    );
-
-MSMPI_DEPRECATE_20( MPI_Type_get_extent )
-int
-MPIAPI
-MPI_Type_extent(
-    MPI_Datatype datatype,
-    _Out_ MPI_Aint* extent
-    );
-MSMPI_DEPRECATE_20( PMPI_Type_get_extent )
-int
-MPIAPI
-PMPI_Type_extent(
-    MPI_Datatype datatype,
-    _Out_ MPI_Aint* extent
-    );
-
-MSMPI_DEPRECATE_20( MPI_Type_get_extent )
-int
-MPIAPI
-MPI_Type_lb(
-    MPI_Datatype datatype,
-    _Out_ MPI_Aint* displacement
-    );
-MSMPI_DEPRECATE_20( PMPI_Type_get_extent )
-int
-MPIAPI
-PMPI_Type_lb(
-    MPI_Datatype datatype,
-    _Out_ MPI_Aint* displacement
-    );
-
-MSMPI_DEPRECATE_20( MPI_Type_get_extent )
-int
-MPIAPI
-MPI_Type_ub(
-    MPI_Datatype datatype,
-    _Out_ MPI_Aint* displacement
-    );
-MSMPI_DEPRECATE_20( PMPI_Type_get_extent )
-int
-MPIAPI
-PMPI_Type_ub(
-    MPI_Datatype datatype,
-    _Out_ MPI_Aint* displacement
-    );
-
-
-typedef MPI_Comm_copy_attr_function MPI_Copy_function;
-typedef MPI_Comm_delete_attr_function MPI_Delete_function;
-
-#define MPI_NULL_COPY_FN ((MPI_Copy_function*)0)
-#define MPI_NULL_DELETE_FN ((MPI_Delete_function*)0)
-#define MPI_DUP_FN MPIR_Dup_fn
-
-
-MSMPI_DEPRECATE_20( MPI_Comm_create_keyval )
-int
-MPIAPI
-MPI_Keyval_create(
-    _In_ MPI_Copy_function* copy_fn,
-    _In_ MPI_Delete_function* delete_fn,
-    _Out_ int* keyval,
-    _In_opt_ void* extra_state
-    );
-MSMPI_DEPRECATE_20( PMPI_Comm_create_keyval )
-int
-MPIAPI
-PMPI_Keyval_create(
-    _In_ MPI_Copy_function* copy_fn,
-    _In_ MPI_Delete_function* delete_fn,
-    _Out_ int* keyval,
-    _In_opt_ void* extra_state
-    );
-
-MSMPI_DEPRECATE_20( MPI_Comm_free_keyval )
-int
-MPIAPI
-MPI_Keyval_free(
-    _Inout_ int* keyval
-    );
-MSMPI_DEPRECATE_20( PMPI_Comm_free_keyval )
-int
-MPIAPI
-PMPI_Keyval_free(
-    _Inout_ int* keyval
-    );
-
-MSMPI_DEPRECATE_20( MPI_Comm_set_attr )
-int
-MPIAPI
-MPI_Attr_put(
-    MPI_Comm comm,
-    int keyval,
-    _In_ void* attribute_val
-    );
-MSMPI_DEPRECATE_20( PMPI_Comm_set_attr )
-int
-MPIAPI
-PMPI_Attr_put(
-    MPI_Comm comm,
-    int keyval,
-    _In_ void* attribute_val
-    );
-
-MSMPI_DEPRECATE_20( MPI_Comm_get_attr )
-int
-MPIAPI
-MPI_Attr_get(
-    MPI_Comm comm,
-    int keyval,
-    _Out_ void* attribute_val,
-    _Out_ int* flag
-    );
-MSMPI_DEPRECATE_20( PMPI_Comm_get_attr )
-int
-MPIAPI
-PMPI_Attr_get(
-    MPI_Comm comm,
-    int keyval,
-    _Out_ void* attribute_val,
-    _Out_ int* flag
-    );
-
-MSMPI_DEPRECATE_20( MPI_Comm_delete_attr )
-int
-MPIAPI
-MPI_Attr_delete(
-    MPI_Comm comm,
-    int keyval
-    );
-MSMPI_DEPRECATE_20( PMPI_Comm_delete_attr )
-int
-MPIAPI
-PMPI_Attr_delete(
-    MPI_Comm comm,
-    int keyval
-    );
-
-
-typedef MPI_Comm_errhandler_fn MPI_Handler_function;
-
-MSMPI_DEPRECATE_20( MPI_Comm_create_errhandler )
-int
-MPIAPI
-MPI_Errhandler_create(
-    _In_ MPI_Handler_function* function,
-    _Out_ MPI_Errhandler* errhandler
-    );
-MSMPI_DEPRECATE_20( PMPI_Comm_create_errhandler )
-int
-MPIAPI
-PMPI_Errhandler_create(
-    _In_ MPI_Handler_function* function,
-    _Out_ MPI_Errhandler* errhandler
-    );
-
-MSMPI_DEPRECATE_20( MPI_Comm_set_errhandler )
-int
-MPIAPI
-MPI_Errhandler_set(
-    MPI_Comm comm,
-    MPI_Errhandler errhandler
-    );
-MSMPI_DEPRECATE_20( PMPI_Comm_set_errhandler )
-int
-MPIAPI
-PMPI_Errhandler_set(
-    MPI_Comm comm,
-    MPI_Errhandler errhandler
-    );
-
-MSMPI_DEPRECATE_20( MPI_Comm_get_errhandler )
-int
-MPIAPI
-MPI_Errhandler_get(
-    MPI_Comm comm,
-    _Out_ MPI_Errhandler* errhandler
-    );
-MSMPI_DEPRECATE_20( PMPI_Comm_get_errhandler )
-int
-MPIAPI
-PMPI_Errhandler_get(
-    MPI_Comm comm,
-    _Out_ MPI_Errhandler* errhandler
-    );
-
-
-/*---------------------------------------------------------------------------*/
-/* Chapter 16: Language Bindings                                             */
-/*---------------------------------------------------------------------------*/
-
-/*---------------------------------------------*/
-/* Section 16.2: Fortran Support               */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Type_create_f90_real(
-    int p,
-    int r,
-    _Out_ MPI_Datatype* newtype
-    );
-int
-MPIAPI
-PMPI_Type_create_f90_real(
-    int p,
-    int r,
-    _Out_ MPI_Datatype* newtype
-    );
-
-int
-MPIAPI
-MPI_Type_create_f90_complex(
-    int p,
-    int r,
-    _Out_ MPI_Datatype* newtype
-    );
-int
-MPIAPI
-PMPI_Type_create_f90_complex(
-    int p,
-    int r,
-    _Out_ MPI_Datatype* newtype
-    );
-
-int
-MPIAPI
-MPI_Type_create_f90_integer(
-    int r,
-    _Out_ MPI_Datatype* newtype
-    );
-int
-MPIAPI
-PMPI_Type_create_f90_integer(
-    int r,
-    _Out_ MPI_Datatype* newtype
-    );
-
-/* typeclasses */
-#define MPI_TYPECLASS_REAL      1
-#define MPI_TYPECLASS_INTEGER   2
-#define MPI_TYPECLASS_COMPLEX   3
-
-int
-MPIAPI
-MPI_Type_match_size(
-    int typeclass,
-    int size,
-    _Out_ MPI_Datatype* type
-    );
-int
-MPIAPI
-PMPI_Type_match_size(
-    int typeclass,
-    int size,
-    _Out_ MPI_Datatype* type
-    );
-
-
-/*---------------------------------------------*/
-/* Section 16.3: Language Interoperability     */
-/*---------------------------------------------*/
-
-#define MPI_Comm_c2f(comm)  (MPI_Fint)(comm)
-#define PMPI_Comm_c2f(comm) (MPI_Fint)(comm)
-
-#define MPI_Comm_f2c(comm)  (MPI_Comm)(comm)
-#define PMPI_Comm_f2c(comm) (MPI_Comm)(comm)
-
-
-#define MPI_Type_f2c(datatype)  (MPI_Datatype)(datatype)
-#define PMPI_Type_f2c(datatype) (MPI_Datatype)(datatype)
-
-#define MPI_Type_c2f(datatype)  (MPI_Fint)(datatype)
-#define PMPI_Type_c2f(datatype) (MPI_Fint)(datatype)
-
-
-#define MPI_Group_f2c(group)  (MPI_Group)(group)
-#define PMPI_Group_f2c(group) (MPI_Group)(group)
-
-#define MPI_Group_c2f(group)  (MPI_Fint)(group)
-#define PMPI_Group_c2f(group) (MPI_Fint)(group)
-
-
-#define MPI_Request_f2c(request)  (MPI_Request)(request)
-#define PMPI_Request_f2c(request) (MPI_Request)(request)
-
-#define MPI_Request_c2f(request)  (MPI_Fint)(request)
-#define PMPI_Request_c2f(request) (MPI_Fint)(request)
-
-
-#define MPI_Win_f2c(win)  (MPI_Win)(win)
-#define PMPI_Win_f2c(win) (MPI_Win)(win)
-
-#define MPI_Win_c2f(win)  (MPI_Fint)(win)
-#define PMPI_Win_c2f(win) (MPI_Fint)(win)
-
-
-#define MPI_Op_c2f(op)  (MPI_Fint)(op)
-#define PMPI_Op_c2f(op) (MPI_Fint)(op)
-
-#define MPI_Op_f2c(op)  (MPI_Op)(op)
-#define PMPI_Op_f2c(op) (MPI_Op)(op)
-
-
-#define MPI_Info_c2f(info)  (MPI_Fint)(info)
-#define PMPI_Info_c2f(info) (MPI_Fint)(info)
-
-#define MPI_Info_f2c(info)  (MPI_Info)(info)
-#define PMPI_Info_f2c(info) (MPI_Info)(info)
-
-
-#define MPI_Errhandler_c2f(errhandler)  (MPI_Fint)(errhandler)
-#define PMPI_Errhandler_c2f(errhandler) (MPI_Fint)(errhandler)
-
-#define MPI_Errhandler_f2c(errhandler)  (MPI_Errhandler)(errhandler)
-#define PMPI_Errhandler_f2c(errhandler) (MPI_Errhandler)(errhandler)
-
-
-MPI_File
-MPIAPI
-MPI_File_f2c(
-    MPI_Fint file
-    );
-MPI_File
-MPIAPI
-PMPI_File_f2c(
-    MPI_Fint file
-    );
-
-MPI_Fint
-MPIAPI
-MPI_File_c2f(
-    MPI_File file
-    );
-MPI_Fint
-MPIAPI
-PMPI_File_c2f(
-    MPI_File file
-    );
-
-int
-MPIAPI
-MPI_Status_f2c(
-    _In_ MPI_Fint* f_status,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_Status_f2c(
-    _In_ MPI_Fint* f_status,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_Status_c2f(
-    _In_ MPI_Status* status,
-    _Out_ MPI_Fint* f_status
-    );
-int
-MPIAPI
-PMPI_Status_c2f(
-    _In_ MPI_Status* status,
-    _Out_ MPI_Fint* f_status
-    );
-
-
-#if !defined(_MPICH_DLL_)
-#define MPIU_DLL_SPEC __declspec(dllimport)
-#else
-#define MPIU_DLL_SPEC
-#endif
-
-extern MPIU_DLL_SPEC MPI_Fint* MPI_F_STATUS_IGNORE;
-extern MPIU_DLL_SPEC MPI_Fint* MPI_F_STATUSES_IGNORE;
-
-
-/*---------------------------------------------------------------------------*/
-/* Implementation Specific                                                   */
-/*---------------------------------------------------------------------------*/
-
-int
-MPIAPI
-MPIR_Dup_fn(
-    MPI_Comm oldcomm,
-    int keyval,
-    _In_opt_ void* extra_state,
-    _In_ void* attribute_val_in,
-    _Out_ void* attribute_val_out,
-    _Out_ int* flag
-    );
-
-
-#if MSMPI_VER >= 0x300
-
-int
-MPIAPI
-MSMPI_Get_bsend_overhead();
-
-#endif
-
-
-#if MSMPI_VER >= 0x300
-
-int
-MPIAPI
-MSMPI_Get_version();
-
-#else
-#  define MSMPI_Get_version() (MSMPI_VER)
-#endif
-
-typedef void
-(MPIAPI MSMPI_Request_callback)(
-    _In_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MSMPI_Request_set_apc(
-    MPI_Request request,
-    _In_ MSMPI_Request_callback* callback_fn,
-    _In_ MPI_Status* callback_status
-    );
-
-typedef struct _MSMPI_LOCK_QUEUE
-{
-    struct _MSMPI_LOCK_QUEUE* volatile next;
-    volatile MPI_Aint flags;
-
-} MSMPI_Lock_queue;
-
-void
-MPIAPI
-MSMPI_Queuelock_acquire(
-    _Out_ MSMPI_Lock_queue* queue
-    );
-
-void
-MPIAPI
-MSMPI_Queuelock_release(
-    _In_ MSMPI_Lock_queue* queue
-    );
-
-int
-MPIAPI
-MSMPI_Waitsome_interruptible(
-    int incount,
-    _Inout_count_(incount) MPI_Request array_of_requests[],
-    _Out_ int* outcount,
-    _Out_cap_post_count_(incount,*outcount) int array_of_indices[],
-    _Out_cap_post_count_(incount,*outcount) MPI_Status array_of_statuses[]
-    );
-
-
-/*---------------------------------------------------------------------------*/
-/* SAL ANNOTATIONS                                                           */
-/*---------------------------------------------------------------------------*/
-
-//OACR_WARNING_POP
-
-#ifdef MSMPI_DEFINED_SAL
-#undef MSMPI_DEFINED_SAL
-#undef _In_
-#undef _In_z_
-#undef _In_opt_
-#undef _In_count_
-#undef _In_bytecount_
-#undef _In_opt_count_
-#undef _Out_
-#undef _Out_cap_
-#undef _Out_cap_post_count_
-#undef _Out_bytecap_
-#undef _Out_z_cap_
-#undef _Out_z_cap_post_count_
-#undef _Out_cap_post_part_
-#undef _Out_opt_
-#undef _Out_opt_cap_
-#undef _Post_z_
-#undef _Inout_
-#undef _Inout_count_
-#endif
-
-#if defined(__cplusplus)
-}
-#endif
-
-#endif /* MPI_INCLUDED */
diff --git a/MachineLearning/CNTKEval/CNTKEval.vcxproj b/MachineLearning/CNTKEval/CNTKEval.vcxproj
index 8ef6b57bc..679eb72cd 100644
--- a/MachineLearning/CNTKEval/CNTKEval.vcxproj
+++ b/MachineLearning/CNTKEval/CNTKEval.vcxproj
@@ -30,7 +30,6 @@
     <UseDebugLibraries>true</UseDebugLibraries>
     <PlatformToolset>v120</PlatformToolset>
     <CharacterSet>Unicode</CharacterSet>
-    <UseIntelMKL>Parallel</UseIntelMKL>
   </PropertyGroup>
   <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'" Label="Configuration">
     <ConfigurationType>DynamicLibrary</ConfigurationType>
@@ -38,7 +37,6 @@
     <PlatformToolset>v120</PlatformToolset>
     <WholeProgramOptimization>true</WholeProgramOptimization>
     <CharacterSet>Unicode</CharacterSet>
-    <UseIntelMKL>Parallel</UseIntelMKL>
   </PropertyGroup>
   <Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
   <ImportGroup Label="ExtensionSettings">
@@ -76,7 +74,7 @@
       <SubSystem>Windows</SubSystem>
       <GenerateDebugInformation>true</GenerateDebugInformation>
       <AdditionalDependencies>CNTKMath.lib; nvml.lib; kernel32.lib; user32.lib; shell32.lib; %(AdditionalDependencies)</AdditionalDependencies>
-      <AdditionalLibraryDirectories>..\..\math\$(Platform)\$(Configuration);$(SolutionDir)$(Platform)\$(Configuration)\; "c:\Program Files\NVIDIA Corporation\GDK\gdk_win7_amd64_release\nvml\lib"</AdditionalLibraryDirectories>
+      <AdditionalLibraryDirectories>$(SolutionDir)$(Platform)\$(Configuration)\; "c:\Program Files\NVIDIA Corporation\GDK\gdk_win7_amd64_release\nvml\lib"</AdditionalLibraryDirectories>
       <DelayLoadDLLs>CNTKMath.dll; nvml.dll; cudart64_70.dll</DelayLoadDLLs>
     </Link>
     <PostBuildEvent>
@@ -105,7 +103,7 @@
       <EnableCOMDATFolding>true</EnableCOMDATFolding>
       <OptimizeReferences>true</OptimizeReferences>
       <AdditionalDependencies>CNTKMath.lib; nvml.lib; kernel32.lib; user32.lib; shell32.lib; %(AdditionalDependencies)</AdditionalDependencies>
-      <AdditionalLibraryDirectories>..\..\math\$(Platform)\$(Configuration);$(SolutionDir)$(Platform)\$(Configuration)\; "c:\Program Files\NVIDIA Corporation\GDK\gdk_win7_amd64_release\nvml\lib"</AdditionalLibraryDirectories>
+      <AdditionalLibraryDirectories>$(SolutionDir)$(Platform)\$(Configuration)\; "c:\Program Files\NVIDIA Corporation\GDK\gdk_win7_amd64_release\nvml\lib"</AdditionalLibraryDirectories>
       <Profile>true</Profile>
       <DelayLoadDLLs>CNTKMath.dll; nvml.dll; cudart64_70.dll</DelayLoadDLLs>
     </Link>
@@ -158,4 +156,4 @@
   <Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
   <ImportGroup Label="ExtensionTargets">
   </ImportGroup>
-</Project>
+</Project>
\ No newline at end of file
diff --git a/MachineLearning/cn/mpi/mpi.h b/MachineLearning/cn/mpi/mpi.h
deleted file mode 100644
index bd61200e7..000000000
--- a/MachineLearning/cn/mpi/mpi.h
+++ /dev/null
@@ -1,5937 +0,0 @@
-/*
- *  (C) 2001 by Argonne National Laboratory.
- *  (C) 2009 by Microsoft Corporation.
- *      See COPYRIGHT in the SDK directory.
- */
-
-#ifndef MPI_INCLUDED
-#define MPI_INCLUDED
-
-#if defined(__cplusplus)
-extern "C" {
-#endif
-
-
-#ifndef MSMPI_VER
-#define MSMPI_VER 0x100
-#endif
-
-
-/*---------------------------------------------------------------------------*/
-/* SAL ANNOTATIONS                                                           */
-/*---------------------------------------------------------------------------*/
-/*
- * Define SAL annotations if they aren't defined yet.  Note that if we define
- * them, we undefine them at the end of this file so that future inclusion of
- * sal.h doesn't cause errors.
- */
-#ifndef _In_
-#define MSMPI_DEFINED_SAL
-#define _In_
-#define _In_z_
-#define _In_opt_
-#define _In_count_( x )
-#define _In_bytecount_( x )
-#define _In_opt_count_( x )
-#define _Out_
-#define _Out_cap_( x )
-#define _Out_cap_post_count_( x, y )
-#define _Out_bytecap_( x )
-#define _Out_z_cap_( x )
-#define _Out_z_cap_post_count_( x, y )
-#define _Out_cap_post_part_( x, y )
-#define _Out_opt_
-#define _Out_opt_cap_( x )
-#define _Post_z_
-#define _Inout_
-#define _Inout_count_( x )
-#endif
-
-/*---------------------------------------------------------------------------*/
-/* MSMPI Calling convention                                                  */
-/*---------------------------------------------------------------------------*/
-
-#define MPIAPI __stdcall
-
-
-/*---------------------------------------------------------------------------*/
-/* MPI ERROR CLASS                                                           */
-/*---------------------------------------------------------------------------*/
-
-#define MPI_SUCCESS          0      /* Successful return code */
-
-#define MPI_ERR_BUFFER       1      /* Invalid buffer pointer */
-#define MPI_ERR_COUNT        2      /* Invalid count argument */
-#define MPI_ERR_TYPE         3      /* Invalid datatype argument */
-#define MPI_ERR_TAG          4      /* Invalid tag argument */
-#define MPI_ERR_COMM         5      /* Invalid communicator */
-#define MPI_ERR_RANK         6      /* Invalid rank */
-#define MPI_ERR_ROOT         7      /* Invalid root */
-#define MPI_ERR_GROUP        8      /* Invalid group */
-#define MPI_ERR_OP           9      /* Invalid operation */
-#define MPI_ERR_TOPOLOGY    10      /* Invalid topology */
-#define MPI_ERR_DIMS        11      /* Invalid dimension argument */
-#define MPI_ERR_ARG         12      /* Invalid argument */
-#define MPI_ERR_UNKNOWN     13      /* Unknown error */
-#define MPI_ERR_TRUNCATE    14      /* Message truncated on receive */
-#define MPI_ERR_OTHER       15      /* Other error; use Error_string */
-#define MPI_ERR_INTERN      16      /* Internal error code */
-#define MPI_ERR_IN_STATUS   17      /* Error code is in status */
-#define MPI_ERR_PENDING     18      /* Pending request */
-#define MPI_ERR_REQUEST     19      /* Invalid request (handle) */
-#define MPI_ERR_ACCESS      20      /* Premission denied */
-#define MPI_ERR_AMODE       21      /* Error related to amode passed to MPI_File_open */
-#define MPI_ERR_BAD_FILE    22      /* Invalid file name (e.g., path name too long) */
-#define MPI_ERR_CONVERSION  23      /* Error in user data conversion function */
-#define MPI_ERR_DUP_DATAREP 24      /* Data representation identifier already registered */
-#define MPI_ERR_FILE_EXISTS 25      /* File exists */
-#define MPI_ERR_FILE_IN_USE 26      /* File operation could not be completed, file in use */
-#define MPI_ERR_FILE        27      /* Invalid file handle */
-#define MPI_ERR_INFO        28      /* Invalid info argument */
-#define MPI_ERR_INFO_KEY    29      /* Key longer than MPI_MAX_INFO_KEY */
-#define MPI_ERR_INFO_VALUE  30      /* Value longer than MPI_MAX_INFO_VAL */
-#define MPI_ERR_INFO_NOKEY  31      /* Invalid key passed to MPI_Info_delete */
-#define MPI_ERR_IO          32      /* Other I/O error */
-#define MPI_ERR_NAME        33      /* Invalid service name in MPI_Lookup_name */
-#define MPI_ERR_NO_MEM      34      /* Alloc_mem could not allocate memory */
-#define MPI_ERR_NOT_SAME    35      /* Collective argument/sequence not the same on all processes */
-#define MPI_ERR_NO_SPACE    36      /* Not enough space */
-#define MPI_ERR_NO_SUCH_FILE 37     /* File does not exist */
-#define MPI_ERR_PORT        38      /* Invalid port name in MPI_comm_connect*/
-#define MPI_ERR_QUOTA       39      /* Quota exceeded */
-#define MPI_ERR_READ_ONLY   40      /* Read-only file or file system */
-#define MPI_ERR_SERVICE     41      /* Invalid service name in MPI_Unpublish_name */
-#define MPI_ERR_SPAWN       42      /* Error in spawning processes */
-#define MPI_ERR_UNSUPPORTED_DATAREP   43  /* Unsupported dararep in MPI_File_set_view */
-#define MPI_ERR_UNSUPPORTED_OPERATION 44  /* Unsupported operation on file */
-#define MPI_ERR_WIN         45      /* Invalid win argument */
-#define MPI_ERR_BASE        46      /* Invalid base passed to MPI_Free_mem */
-#define MPI_ERR_LOCKTYPE    47      /* Invalid locktype argument */
-#define MPI_ERR_KEYVAL      48      /* Invalid keyval  */
-#define MPI_ERR_RMA_CONFLICT 49     /* Conflicting accesses to window */
-#define MPI_ERR_RMA_SYNC    50      /* Wrong synchronization of RMA calls */
-#define MPI_ERR_SIZE        51      /* Invalid size argument */
-#define MPI_ERR_DISP        52      /* Invalid disp argument */
-#define MPI_ERR_ASSERT      53      /* Invalid assert argument */
-
-#define MPI_ERR_LASTCODE    0x3fffffff    /* Last valid error code for a predefined error class */
-
-#define MPICH_ERR_LAST_CLASS 53
-
-
-/*---------------------------------------------------------------------------*/
-/* MPI Basic integer types                                                   */
-/*---------------------------------------------------------------------------*/
-
-/* Address size integer */
-#ifdef _WIN64
-typedef __int64 MPI_Aint;
-#else
-typedef int MPI_Aint;
-#endif
-
-/* Fortran INTEGER */
-typedef int MPI_Fint;
-
-/* File offset */
-typedef __int64 MPI_Offset;
-
-
-/*---------------------------------------------------------------------------*/
-/* MPI_Datatype                                                              */
-/*---------------------------------------------------------------------------*/
-
-typedef int MPI_Datatype;
-#define MPI_DATATYPE_NULL           ((MPI_Datatype)0x0c000000)
-
-#define MPI_CHAR                    ((MPI_Datatype)0x4c000101)
-#define MPI_UNSIGNED_CHAR           ((MPI_Datatype)0x4c000102)
-#define MPI_SHORT                   ((MPI_Datatype)0x4c000203)
-#define MPI_UNSIGNED_SHORT          ((MPI_Datatype)0x4c000204)
-#define MPI_INT                     ((MPI_Datatype)0x4c000405)
-#define MPI_UNSIGNED                ((MPI_Datatype)0x4c000406)
-#define MPI_LONG                    ((MPI_Datatype)0x4c000407)
-#define MPI_UNSIGNED_LONG           ((MPI_Datatype)0x4c000408)
-#define MPI_LONG_LONG_INT           ((MPI_Datatype)0x4c000809)
-#define MPI_LONG_LONG               MPI_LONG_LONG_INT
-#define MPI_FLOAT                   ((MPI_Datatype)0x4c00040a)
-#define MPI_DOUBLE                  ((MPI_Datatype)0x4c00080b)
-#define MPI_LONG_DOUBLE             ((MPI_Datatype)0x4c00080c)
-#define MPI_BYTE                    ((MPI_Datatype)0x4c00010d)
-#define MPI_WCHAR                   ((MPI_Datatype)0x4c00020e)
-
-#define MPI_PACKED                  ((MPI_Datatype)0x4c00010f)
-#define MPI_LB                      ((MPI_Datatype)0x4c000010)
-#define MPI_UB                      ((MPI_Datatype)0x4c000011)
-
-#define MPI_C_COMPLEX               ((MPI_Datatype)0x4c000812)
-#define MPI_C_FLOAT_COMPLEX         ((MPI_Datatype)0x4c000813)
-#define MPI_C_DOUBLE_COMPLEX        ((MPI_Datatype)0x4c001614)
-#define MPI_C_LONG_DOUBLE_COMPLEX   ((MPI_Datatype)0x4c001615)
-
-#define MPI_2INT                    ((MPI_Datatype)0x4c000816)
-#define MPI_C_BOOL                  ((MPI_Datatype)0x4c000117)
-#define MPI_SIGNED_CHAR             ((MPI_Datatype)0x4c000118)
-#define MPI_UNSIGNED_LONG_LONG      ((MPI_Datatype)0x4c000819)
-
-/* Fortran types */
-#define MPI_CHARACTER               ((MPI_Datatype)0x4c00011a)
-#define MPI_INTEGER                 ((MPI_Datatype)0x4c00041b)
-#define MPI_REAL                    ((MPI_Datatype)0x4c00041c)
-#define MPI_LOGICAL                 ((MPI_Datatype)0x4c00041d)
-#define MPI_COMPLEX                 ((MPI_Datatype)0x4c00081e)
-#define MPI_DOUBLE_PRECISION        ((MPI_Datatype)0x4c00081f)
-#define MPI_2INTEGER                ((MPI_Datatype)0x4c000820)
-#define MPI_2REAL                   ((MPI_Datatype)0x4c000821)
-#define MPI_DOUBLE_COMPLEX          ((MPI_Datatype)0x4c001022)
-#define MPI_2DOUBLE_PRECISION       ((MPI_Datatype)0x4c001023)
-#define MPI_2COMPLEX                ((MPI_Datatype)0x4c001024)
-#define MPI_2DOUBLE_COMPLEX         ((MPI_Datatype)0x4c002025)
-
-/* Size-specific types (see MPI 2.2, 16.2.5) */
-#define MPI_REAL2                   MPI_DATATYPE_NULL
-#define MPI_REAL4                   ((MPI_Datatype)0x4c000427)
-#define MPI_COMPLEX8                ((MPI_Datatype)0x4c000828)
-#define MPI_REAL8                   ((MPI_Datatype)0x4c000829)
-#define MPI_COMPLEX16               ((MPI_Datatype)0x4c00102a)
-#define MPI_REAL16                  MPI_DATATYPE_NULL
-#define MPI_COMPLEX32               MPI_DATATYPE_NULL
-#define MPI_INTEGER1                ((MPI_Datatype)0x4c00012d)
-#define MPI_COMPLEX4                MPI_DATATYPE_NULL
-#define MPI_INTEGER2                ((MPI_Datatype)0x4c00022f)
-#define MPI_INTEGER4                ((MPI_Datatype)0x4c000430)
-#define MPI_INTEGER8                ((MPI_Datatype)0x4c000831)
-#define MPI_INTEGER16               MPI_DATATYPE_NULL
-#define MPI_INT8_T                  ((MPI_Datatype)0x4c000133)
-#define MPI_INT16_T                 ((MPI_Datatype)0x4c000234)
-#define MPI_INT32_T                 ((MPI_Datatype)0x4c000435)
-#define MPI_INT64_T                 ((MPI_Datatype)0x4c000836)
-#define MPI_UINT8_T                 ((MPI_Datatype)0x4c000137)
-#define MPI_UINT16_T                ((MPI_Datatype)0x4c000238)
-#define MPI_UINT32_T                ((MPI_Datatype)0x4c000439)
-#define MPI_UINT64_T                ((MPI_Datatype)0x4c00083a)
-
-#ifdef _WIN64
-#define MPI_AINT                    ((MPI_Datatype)0x4c00083b)
-#else
-#define MPI_AINT                    ((MPI_Datatype)0x4c00043b)
-#endif
-#define MPI_OFFSET                  ((MPI_Datatype)0x4c00083c)
-
-/*
- * The layouts for the types MPI_DOUBLE_INT etc. are
- *
- *      struct { double a; int b; }
- */
-#define MPI_FLOAT_INT               ((MPI_Datatype)0x8c000000)
-#define MPI_DOUBLE_INT              ((MPI_Datatype)0x8c000001)
-#define MPI_LONG_INT                ((MPI_Datatype)0x8c000002)
-#define MPI_SHORT_INT               ((MPI_Datatype)0x8c000003)
-#define MPI_LONG_DOUBLE_INT         ((MPI_Datatype)0x8c000004)
-
-
-/*---------------------------------------------------------------------------*/
-/* MPI_Comm                                                                  */
-/*---------------------------------------------------------------------------*/
-
-typedef int MPI_Comm;
-#define MPI_COMM_NULL  ((MPI_Comm)0x04000000)
-
-#define MPI_COMM_WORLD ((MPI_Comm)0x44000000)
-#define MPI_COMM_SELF  ((MPI_Comm)0x44000001)
-
-
-/*---------------------------------------------------------------------------*/
-/* MPI_Win                                                                   */
-/*---------------------------------------------------------------------------*/
-
-typedef int MPI_Win;
-#define MPI_WIN_NULL ((MPI_Win)0x20000000)
-
-
-/*---------------------------------------------------------------------------*/
-/* MPI_File                                                                  */
-/*---------------------------------------------------------------------------*/
-
-typedef struct ADIOI_FileD* MPI_File;
-#define MPI_FILE_NULL ((MPI_File)0)
-
-
-/*---------------------------------------------------------------------------*/
-/* MPI_Op                                                                    */
-/*---------------------------------------------------------------------------*/
-
-typedef int MPI_Op;
-#define MPI_OP_NULL ((MPI_Op)0x18000000)
-
-#define MPI_MAX     ((MPI_Op)0x58000001)
-#define MPI_MIN     ((MPI_Op)0x58000002)
-#define MPI_SUM     ((MPI_Op)0x58000003)
-#define MPI_PROD    ((MPI_Op)0x58000004)
-#define MPI_LAND    ((MPI_Op)0x58000005)
-#define MPI_BAND    ((MPI_Op)0x58000006)
-#define MPI_LOR     ((MPI_Op)0x58000007)
-#define MPI_BOR     ((MPI_Op)0x58000008)
-#define MPI_LXOR    ((MPI_Op)0x58000009)
-#define MPI_BXOR    ((MPI_Op)0x5800000a)
-#define MPI_MINLOC  ((MPI_Op)0x5800000b)
-#define MPI_MAXLOC  ((MPI_Op)0x5800000c)
-#define MPI_REPLACE ((MPI_Op)0x5800000d)
-
-
-/*---------------------------------------------------------------------------*/
-/* MPI_Info                                                                  */
-/*---------------------------------------------------------------------------*/
-
-typedef int MPI_Info;
-#define MPI_INFO_NULL         ((MPI_Info)0x1c000000)
-
-
-/*---------------------------------------------------------------------------*/
-/* MPI_Request                                                               */
-/*---------------------------------------------------------------------------*/
-
-typedef int MPI_Request;
-#define MPI_REQUEST_NULL ((MPI_Request)0x2c000000)
-
-
-/*---------------------------------------------------------------------------*/
-/* MPI_Group                                                                 */
-/*---------------------------------------------------------------------------*/
-
-typedef int MPI_Group;
-#define MPI_GROUP_NULL  ((MPI_Group)0x08000000)
-
-#define MPI_GROUP_EMPTY ((MPI_Group)0x48000000)
-
-
-/*---------------------------------------------------------------------------*/
-/* MPI_Errhandler                                                            */
-/*---------------------------------------------------------------------------*/
-
-typedef int MPI_Errhandler;
-#define MPI_ERRHANDLER_NULL  ((MPI_Errhandler)0x14000000)
-
-#define MPI_ERRORS_ARE_FATAL ((MPI_Errhandler)0x54000000)
-#define MPI_ERRORS_RETURN    ((MPI_Errhandler)0x54000001)
-
-/*---------------------------------------------------------------------------*/
-/* MPI_Status                                                                */
-/*---------------------------------------------------------------------------*/
-
-typedef struct MPI_Status
-{
-    int count;
-    int cancelled;
-    int MPI_SOURCE;
-    int MPI_TAG;
-    int MPI_ERROR;
-
-} MPI_Status;
-
-#define MPI_STATUS_IGNORE ((MPI_Status*)(MPI_Aint)1)
-#define MPI_STATUSES_IGNORE ((MPI_Status*)(MPI_Aint)1)
-
-
-/*---------------------------------------------------------------------------*/
-/* MISC CONSTANTS                                                            */
-/*---------------------------------------------------------------------------*/
-
-/* Used in: Count, Index, Rank, Color, Toplogy, Precision, Exponent range  */
-#define MPI_UNDEFINED   (-32766)
-
-/* Used in: Rank */
-#define MPI_PROC_NULL   (-1)
-#define MPI_ANY_SOURCE  (-2)
-#define MPI_ROOT        (-3)
-
-/* Used in: Tag */
-#define MPI_ANY_TAG     (-1)
-
-/* Used for: Buffer address */
-#define MPI_BOTTOM      ((void*)0)
-
-
-/*---------------------------------------------------------------------------*/
-/* Chapter 3: Point-to-Point Communication                                   */
-/*---------------------------------------------------------------------------*/
-
-/*---------------------------------------------*/
-/* Section 3.2: Blocking Communication         */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Send(
-    _In_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Send(
-    _In_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm
-    );
-
-int
-MPIAPI
-MPI_Recv(
-    _Out_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int source,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_Recv(
-    _Out_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int source,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_Get_count(
-    _In_ MPI_Status* status,
-    MPI_Datatype datatype,
-    _Out_ int* count
-    );
-int
-MPIAPI
-PMPI_Get_count(
-    _In_ MPI_Status* status,
-    MPI_Datatype datatype,
-    _Out_ int* count
-    );
-
-
-/*---------------------------------------------*/
-/* Section 3.4: Communication Modes            */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Bsend(
-    _In_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Bsend(
-    _In_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm
-    );
-
-int
-MPIAPI
-MPI_Ssend(
-    _In_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Ssend(
-    _In_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm
-    );
-
-int
-MPIAPI
-MPI_Rsend(
-    _In_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Rsend(
-    _In_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm
-    );
-
-
-/*---------------------------------------------*/
-/* Section 3.6: Buffer Allocation              */
-/*---------------------------------------------*/
-
-/* Upper bound on bsend overhead for each message */
-#define MSMPI_BSEND_OVERHEAD_V1   95
-#define MSMPI_BSEND_OVERHEAD_V2   MSMPI_BSEND_OVERHEAD_V1
-
-#if MSMPI_VER > 0x300
-#  define MPI_BSEND_OVERHEAD  MSMPI_Get_bsend_overhead()
-#else
-#  define MPI_BSEND_OVERHEAD  MSMPI_BSEND_OVERHEAD_V1
-#endif
-
-int
-MPIAPI
-MPI_Buffer_attach(
-    _In_ void* buffer,
-    int size
-    );
-int
-MPIAPI
-PMPI_Buffer_attach(
-    _In_ void* buffer,
-    int size
-    );
-
-int
-MPIAPI
-MPI_Buffer_detach(
-    _Out_ void* buffer_addr,
-    _Out_ int* size
-    );
-int
-MPIAPI
-PMPI_Buffer_detach(
-    _Out_ void* buffer_addr,
-    _Out_ int* size
-    );
-
-
-/*---------------------------------------------*/
-/* Section 3.7: Nonblocking Communication      */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Isend(
-    _In_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_Isend(
-    _In_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-
-int
-MPIAPI
-MPI_Ibsend(
-    _In_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_Ibsend(
-    _In_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-
-int
-MPIAPI
-MPI_Issend(
-    _In_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_Issend(
-    _In_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-
-int
-MPIAPI
-MPI_Irsend(
-    _In_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_Irsend(
-    _In_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-
-int
-MPIAPI
-MPI_Irecv(
-    _Out_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int source,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_Irecv(
-    _Out_opt_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int source,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-
-
-/*---------------------------------------------*/
-/* Section 3.7.3: Communication Completion     */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Wait(
-    _Inout_ MPI_Request* request,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_Wait(
-    _Inout_ MPI_Request* request,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_Test(
-    _Inout_ MPI_Request* request,
-    _Out_ int* flag,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_Test(
-    _Inout_ MPI_Request* request,
-    _Out_ int* flag,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_Request_free(
-    _Inout_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_Request_free(
-    _Inout_ MPI_Request* request
-    );
-
-
-/*---------------------------------------------*/
-/* Section 3.7.5: Multiple Completions         */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Waitany(
-    int count,
-    _Inout_count_(count) MPI_Request* array_of_requests,
-    _Out_ int* index,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_Waitany(
-    int count,
-    _Inout_count_(count) MPI_Request* array_of_requests,
-    _Out_ int* index,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_Testany(
-    int count,
-    _Inout_count_(count) MPI_Request* array_of_requests,
-    _Out_ int* index,
-    _Out_ int* flag,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_Testany(
-    int count,
-    _Inout_count_(count) MPI_Request* array_of_requests,
-    _Out_ int* index,
-    _Out_ int* flag,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_Waitall(
-    int count,
-    _Inout_count_(count) MPI_Request* array_of_requests,
-    _Out_cap_(count) MPI_Status* array_of_statuses
-    );
-int
-MPIAPI
-PMPI_Waitall(
-    int count,
-    _Inout_count_(count) MPI_Request* array_of_requests,
-    _Out_cap_(count) MPI_Status* array_of_statuses
-    );
-
-int
-MPIAPI
-MPI_Testall(
-    int count,
-    _Inout_count_(count) MPI_Request* array_of_requests,
-    _Out_ int* flag,
-    _Out_cap_(count) MPI_Status* array_of_statuses
-    );
-int
-MPIAPI
-PMPI_Testall(
-    int count,
-    _Inout_count_(count) MPI_Request* array_of_requests,
-    _Out_ int* flag,
-    _Out_cap_(count) MPI_Status* array_of_statuses
-    );
-
-int
-MPIAPI
-MPI_Waitsome(
-    int incount,
-    _Inout_count_(incount) MPI_Request* array_of_requests,
-    _Out_ int* outcount,
-    _Out_cap_post_count_(incount,*outcount) int* array_of_indices,
-    _Out_cap_post_count_(incount,*outcount) MPI_Status* array_of_statuses
-    );
-int
-MPIAPI
-PMPI_Waitsome(
-    int incount,
-    _Inout_count_(incount) MPI_Request* array_of_requests,
-    _Out_ int* outcount,
-    _Out_cap_post_count_(incount,*outcount) int* array_of_indices,
-    _Out_cap_post_count_(incount,*outcount) MPI_Status* array_of_statuses
-    );
-
-int
-MPIAPI
-MPI_Testsome(
-    int incount,
-    _Inout_count_(incount) MPI_Request* array_of_requests,
-    _Out_ int* outcount,
-    _Out_cap_post_count_(incount,*outcount) int* array_of_indices,
-    _Out_cap_post_count_(incount,*outcount) MPI_Status* array_of_statuses
-    );
-int
-MPIAPI
-PMPI_Testsome(
-    int incount,
-    _Inout_count_(incount) MPI_Request* array_of_requests,
-    _Out_ int* outcount,
-    _Out_cap_post_count_(incount,*outcount) int* array_of_indices,
-    _Out_cap_post_count_(incount,*outcount) MPI_Status* array_of_statuses
-    );
-
-
-/*---------------------------------------------*/
-/* Section 3.7.6: Test of status               */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Request_get_status(
-    MPI_Request request,
-    _Out_ int* flag,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_Request_get_status(
-    MPI_Request request,
-    _Out_ int* flag,
-    _Out_ MPI_Status* status
-    );
-
-
-/*---------------------------------------------*/
-/* Section 3.8: Probe and Cancel               */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Iprobe(
-    int source,
-    int tag,
-    MPI_Comm comm,
-    _Out_ int* flag,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_Iprobe(
-    int source,
-    int tag,
-    MPI_Comm comm,
-    _Out_ int* flag,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_Probe(
-    int source,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_Probe(
-    int source,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_Cancel(
-    _In_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_Cancel(
-    _In_ MPI_Request* request
-    );
-
-int
-MPIAPI
-MPI_Test_cancelled(
-    _In_ MPI_Status* status,
-    _Out_ int* flag
-    );
-int
-MPIAPI
-PMPI_Test_cancelled(
-    _In_ MPI_Status* request,
-    _Out_ int* flag
-    );
-
-
-/*---------------------------------------------*/
-/* Section 3.9: Persistent Communication       */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Send_init(
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_Send_init(
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-
-int
-MPIAPI
-MPI_Bsend_init(
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_Bsend_init(
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-
-int
-MPIAPI
-MPI_Ssend_init(
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_Ssend_init(
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-
-int
-MPIAPI
-MPI_Rsend_init(
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_Rsend_init(
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-
-int
-MPIAPI
-MPI_Recv_init(
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int source,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_Recv_init(
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int source,
-    int tag,
-    MPI_Comm comm,
-    _Out_ MPI_Request* request
-    );
-
-int
-MPIAPI
-MPI_Start(
-    _Inout_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_Start(
-    _Inout_ MPI_Request* request
-    );
-
-int
-MPIAPI
-MPI_Startall(
-    int count,
-    _Inout_count_(count) MPI_Request* array_of_requests
-    );
-int
-MPIAPI
-PMPI_Startall(
-    int count,
-    _Inout_count_(count) MPI_Request* array_of_requests
-    );
-
-
-/*---------------------------------------------*/
-/* Section 3.10: Send-Recv                     */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Sendrecv(
-    _In_ void* sendbuf,
-    int sendcount,
-    MPI_Datatype sendtype,
-    int dest,
-    int sendtag,
-    _Out_ void* recvbuf,
-    int recvcount,
-    MPI_Datatype recvtype,
-    int source,
-    int recvtag,
-    MPI_Comm comm,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_Sendrecv(
-    _In_ void* sendbuf,
-    int sendcount,
-    MPI_Datatype sendtype,
-    int dest,
-    int sendtag,
-    _Out_ void* recvbuf,
-    int recvcount,
-    MPI_Datatype recvtype,
-    int source,
-    int recvtag,
-    MPI_Comm comm,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_Sendrecv_replace(
-    _Inout_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int sendtag,
-    int source,
-    int recvtag,
-    MPI_Comm comm,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_Sendrecv_replace(
-    _Inout_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    int dest,
-    int sendtag,
-    int source,
-    int recvtag,
-    MPI_Comm comm,
-    _Out_ MPI_Status* status
-    );
-
-
-/*---------------------------------------------------------------------------*/
-/* Chapter 4: Datatypes                                                      */
-/*---------------------------------------------------------------------------*/
-
-/*---------------------------------------------*/
-/* Section 4.1: Derived Datatypes              */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Type_contiguous(
-    int count,
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-int
-MPIAPI
-PMPI_Type_contiguous(
-    int count,
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-
-int
-MPIAPI
-MPI_Type_vector(
-    int count,
-    int blocklength,
-    int stride,
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-int
-MPIAPI
-PMPI_Type_vector(
-    int count,
-    int blocklength,
-    int stride,
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-
-int
-MPIAPI
-MPI_Type_create_hvector(
-    int count,
-    int blocklength,
-    MPI_Aint stride,
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-int
-MPIAPI
-PMPI_Type_create_hvector(
-    int count,
-    int blocklength,
-    MPI_Aint stride,
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-
-int
-MPIAPI
-MPI_Type_indexed(
-    int count,
-    _In_count_(count) int* array_of_blocklengths,
-    _In_count_(count) int* array_of_displacements,
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-int
-MPIAPI
-PMPI_Type_indexed(
-    int count,
-    _In_count_(count) int* array_of_blocklengths,
-    _In_count_(count) int* array_of_displacements,
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-
-int
-MPIAPI
-MPI_Type_create_hindexed(
-    int count,
-    _In_count_(count) int array_of_blocklengths[],
-    _In_count_(count) MPI_Aint array_of_displacements[],
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-int
-MPIAPI
-PMPI_Type_create_hindexed(
-    int count,
-    _In_count_(count) int array_of_blocklengths[],
-    _In_opt_count_(count) MPI_Aint array_of_displacements[],
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-
-int
-MPIAPI
-MPI_Type_create_indexed_block(
-    int count,
-    int blocklength,
-    _In_count_(count) int array_of_displacements[],
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-int
-MPIAPI
-PMPI_Type_create_indexed_block(
-    int count,
-    int blocklength,
-    _In_count_(count) int array_of_displacements[],
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-
-int
-MPIAPI
-MPI_Type_create_struct(
-    int count,
-    _In_count_(count) int array_of_blocklengths[],
-    _In_count_(count) MPI_Aint array_of_displacements[],
-    _In_count_(count) MPI_Datatype array_of_types[],
-    _Out_ MPI_Datatype* newtype
-    );
-int
-MPIAPI
-PMPI_Type_create_struct(
-    int count,
-    _In_count_(count) int array_of_blocklengths[],
-    _In_opt_count_(count) MPI_Aint array_of_displacements[],
-    _In_count_(count) MPI_Datatype array_of_types[],
-    _Out_ MPI_Datatype* newtype
-    );
-
-
-#define MPI_ORDER_C         56
-#define MPI_ORDER_FORTRAN   57
-
-int
-MPIAPI
-MPI_Type_create_subarray(
-    int ndims,
-    _In_count_(ndims) int array_of_sizes[],
-    _In_count_(ndims) int array_of_subsizes[],
-    _In_count_(ndims) int array_of_starts[],
-    int order,
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-int
-MPIAPI
-PMPI_Type_create_subarray(
-    int ndims,
-    _In_count_(ndims) int array_of_sizes[],
-    _In_count_(ndims) int array_of_subsizes[],
-    _In_count_(ndims) int array_of_starts[],
-    int order,
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-
-
-#define MPI_DISTRIBUTE_BLOCK         121
-#define MPI_DISTRIBUTE_CYCLIC        122
-#define MPI_DISTRIBUTE_NONE          123
-#define MPI_DISTRIBUTE_DFLT_DARG (-49767)
-
-int
-MPIAPI
-MPI_Type_create_darray(
-    int size,
-    int rank,
-    int ndims,
-    _In_count_(ndims) int array_of_gszies[],
-    _In_count_(ndims) int array_of_distribs[],
-    _In_count_(ndims) int array_of_dargs[],
-    _In_count_(ndims) int array_of_psizes[],
-    int order,
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-int
-MPIAPI
-PMPI_Type_create_darray(
-    int size,
-    int rank,
-    int ndims,
-    _In_count_(ndims) int array_of_gszies[],
-    _In_count_(ndims) int array_of_distribs[],
-    _In_count_(ndims) int array_of_dargs[],
-    _In_count_(ndims) int array_of_psizes[],
-    int order,
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-
-
-/*---------------------------------------------*/
-/* Section 4.1.5: Datatype Address and Size    */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Get_address(
-    _In_ void* location,
-    _Out_ MPI_Aint* address
-    );
-int
-MPIAPI
-PMPI_Get_address(
-    _In_ void* location,
-    _Out_ MPI_Aint* address
-    );
-
-int
-MPIAPI
-MPI_Type_size(
-    MPI_Datatype datatype,
-    _Out_ int* size
-    );
-int
-MPIAPI
-PMPI_Type_size(
-    MPI_Datatype datatype,
-    _Out_ int* size
-    );
-
-
-/*---------------------------------------------*/
-/* Section 4.1.7: Datatype Extent and Bounds   */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Type_get_extent(
-    MPI_Datatype datatype,
-    _Out_ MPI_Aint* lb,
-    _Out_ MPI_Aint* extent
-    );
-int
-MPIAPI
-PMPI_Type_get_extent(
-    MPI_Datatype datatype,
-    _Out_ MPI_Aint* lb,
-    _Out_ MPI_Aint* extent
-    );
-
-int
-MPIAPI
-MPI_Type_create_resized(
-    MPI_Datatype oldtype,
-    MPI_Aint lb,
-    MPI_Aint extent,
-    _Out_ MPI_Datatype* newtype
-    );
-int
-MPIAPI
-PMPI_Type_create_resized(
-    MPI_Datatype oldtype,
-    MPI_Aint lb,
-    MPI_Aint extent,
-    _Out_ MPI_Datatype* newtype
-    );
-
-
-/*---------------------------------------------*/
-/* Section 4.1.8: Datatype True Extent         */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Type_get_true_extent(
-    MPI_Datatype datatype,
-    _Out_ MPI_Aint* true_lb,
-    _Out_ MPI_Aint* true_extent
-    );
-int
-MPIAPI
-PMPI_Type_get_true_extent(
-    MPI_Datatype datatype,
-    _Out_ MPI_Aint* true_lb,
-    _Out_ MPI_Aint* true_extent
-    );
-
-
-/*---------------------------------------------*/
-/* Section 4.1.9: Datatype Commit and Free     */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Type_commit(
-    _In_ MPI_Datatype* datatype
-    );
-int
-MPIAPI
-PMPI_Type_commit(
-    _In_ MPI_Datatype* datatype
-    );
-
-int
-MPIAPI
-MPI_Type_free(
-    _Inout_ MPI_Datatype* datatype
-    );
-int
-MPIAPI
-PMPI_Type_free(
-    _Inout_ MPI_Datatype* datatype
-    );
-
-
-/*---------------------------------------------*/
-/* Section 4.1.10: Datatype Duplication        */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Type_dup(
-    MPI_Datatype type,
-    _Out_ MPI_Datatype* newtype
-    );
-int
-MPIAPI
-PMPI_Type_dup(
-    MPI_Datatype type,
-    _Out_ MPI_Datatype* newtype
-    );
-
-
-/*---------------------------------------------*/
-/* Section 4.1.11: Datatype and Communication  */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Get_elements(
-    _In_ MPI_Status* status,
-    MPI_Datatype datatype,
-    _Out_ int* count
-    );
-int
-MPIAPI
-PMPI_Get_elements(
-    _In_ MPI_Status* status,
-    MPI_Datatype datatype,
-    _Out_ int* count
-    );
-
-
-/*---------------------------------------------*/
-/* Section 4.1.13: Decoding a Datatype         */
-/*---------------------------------------------*/
-
-/* Datatype combiners result */
-enum
-{
-    MPI_COMBINER_NAMED            = 1,
-    MPI_COMBINER_DUP              = 2,
-    MPI_COMBINER_CONTIGUOUS       = 3,
-    MPI_COMBINER_VECTOR           = 4,
-    MPI_COMBINER_HVECTOR_INTEGER  = 5,
-    MPI_COMBINER_HVECTOR          = 6,
-    MPI_COMBINER_INDEXED          = 7,
-    MPI_COMBINER_HINDEXED_INTEGER = 8,
-    MPI_COMBINER_HINDEXED         = 9,
-    MPI_COMBINER_INDEXED_BLOCK    = 10,
-    MPI_COMBINER_STRUCT_INTEGER   = 11,
-    MPI_COMBINER_STRUCT           = 12,
-    MPI_COMBINER_SUBARRAY         = 13,
-    MPI_COMBINER_DARRAY           = 14,
-    MPI_COMBINER_F90_REAL         = 15,
-    MPI_COMBINER_F90_COMPLEX      = 16,
-    MPI_COMBINER_F90_INTEGER      = 17,
-    MPI_COMBINER_RESIZED          = 18
-};
-
-int
-MPIAPI
-MPI_Type_get_envelope(
-    MPI_Datatype datatype,
-    _Out_ int* num_integers,
-    _Out_ int* num_addresses,
-    _Out_ int* num_datatypes,
-    _Out_ int* combiner
-    );
-int
-MPIAPI
-PMPI_Type_get_envelope(
-    MPI_Datatype datatype,
-    _Out_ int* num_integers,
-    _Out_ int* num_addresses,
-    _Out_ int* num_datatypes,
-    _Out_ int* combiner
-    );
-
-int
-MPIAPI
-MPI_Type_get_contents(
-    MPI_Datatype datatype,
-    int max_integers,
-    int max_addresses,
-    int max_datatypes,
-    _Out_cap_(max_integers) int array_of_integers[],
-    _Out_cap_(max_addresses) MPI_Aint array_of_addresses[],
-    _Out_cap_(max_datatypes) MPI_Datatype array_of_datatypes[]
-    );
-int
-MPIAPI
-PMPI_Type_get_contents(
-    MPI_Datatype datatype,
-    int max_integers,
-    int max_addresses,
-    int max_datatypes,
-    _Out_cap_(max_integers) int array_of_integers[],
-    _Out_cap_(max_addresses) MPI_Aint array_of_addresses[],
-    _Out_cap_(max_datatypes) MPI_Datatype array_of_datatypes[]
-    );
-
-
-/*---------------------------------------------*/
-/* Section 4.2: Datatype Pack and Unpack       */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Pack(
-    _In_ void* inbuf,
-    int incount,
-    MPI_Datatype datatype,
-    _Out_bytecap_(outsize) void* outbuf,
-    int outsize,
-    _Inout_ int* position,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Pack(
-    _In_ void* inbuf,
-    int incount,
-    MPI_Datatype datatype,
-    _Out_bytecap_(outsize) void* outbuf,
-    int outsize,
-    _Inout_ int* position,
-    MPI_Comm comm
-    );
-
-int
-MPIAPI
-MPI_Unpack(
-    _In_bytecount_(insize) void* inbuf,
-    int insize,
-    _Inout_ int* position,
-    _Out_ void* outbuf,
-    int outcount,
-    MPI_Datatype datatype,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Unpack(
-    _In_bytecount_(insize) void* inbuf,
-    int insize,
-    _Inout_ int* position,
-    _Out_ void* outbuf,
-    int outcount,
-    MPI_Datatype datatype,
-    MPI_Comm comm
-    );
-
-int
-MPIAPI
-MPI_Pack_size(
-    int incount,
-    MPI_Datatype datatype,
-    MPI_Comm comm,
-    _Out_ int* size
-    );
-int
-MPIAPI
-PMPI_Pack_size(
-    int incount,
-    MPI_Datatype datatype,
-    MPI_Comm comm,
-    _Out_ int* size
-    );
-
-
-/*---------------------------------------------*/
-/* Section 4.3: Canonical Pack and Unpack      */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Pack_external(
-    _In_z_ char* datarep,
-    _In_ void* inbuf,
-    int incount,
-    MPI_Datatype datatype,
-    _Out_bytecap_(outsize) void* outbuf,
-    MPI_Aint outsize,
-    _Inout_ MPI_Aint* position
-    );
-int
-MPIAPI
-PMPI_Pack_external(
-    _In_z_ char* datarep,
-    _In_ void* inbuf,
-    int incount,
-    MPI_Datatype datatype,
-    _Out_bytecap_(outsize) void* outbuf,
-    MPI_Aint outsize,
-    _Inout_ MPI_Aint* position
-    );
-
-int
-MPIAPI
-MPI_Unpack_external(
-    _In_z_ char* datarep,
-    _In_bytecount_(insize) void* inbuf,
-    MPI_Aint insize,
-    _Inout_ MPI_Aint* position,
-    _Out_ void* outbuf,
-    int outcount,
-    MPI_Datatype datatype
-    );
-int
-MPIAPI
-PMPI_Unpack_external(
-    _In_z_ char* datarep,
-    _In_bytecount_(insize) void* inbuf,
-    MPI_Aint insize,
-    _Inout_ MPI_Aint* position,
-    _Out_ void* outbuf,
-    int outcount,
-    MPI_Datatype datatype
-    );
-
-int
-MPIAPI
-MPI_Pack_external_size(
-    _In_z_ char* datarep,
-    int incount,
-    MPI_Datatype datatype,
-    _Out_ MPI_Aint* size
-    );
-int
-MPIAPI
-PMPI_Pack_external_size(
-    _In_z_ char* datarep,
-    int incount,
-    MPI_Datatype datatype,
-    _Out_ MPI_Aint* size
-    );
-
-
-/*---------------------------------------------------------------------------*/
-/* Chapter 5: Collective Communication                                       */
-/*---------------------------------------------------------------------------*/
-
-#define MPI_IN_PLACE ((void*)(MPI_Aint)-1)
-
-/*---------------------------------------------*/
-/* Section 5.3: Barrier Synchronization        */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Barrier(
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Barrier(
-    MPI_Comm comm
-    );
-
-
-/*---------------------------------------------*/
-/* Section 5.4: Broadcast                      */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Bcast(
-    _Inout_ void* buffer,
-    int count,
-    MPI_Datatype datatype,
-    int root,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Bcast(
-    _Inout_ void* buffer,
-    int count,
-    MPI_Datatype datatype,
-    int root,
-    MPI_Comm comm
-    );
-
-
-/*---------------------------------------------*/
-/* Section 5.5: Gather                         */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Gather(
-    _In_ void* sendbuf,
-    int sendcount,
-    MPI_Datatype sendtype,
-    _Out_opt_ void* recvbuf,
-    int recvcount,
-    MPI_Datatype recvtype,
-    int root,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Gather(
-    _In_ void* sendbuf,
-    int sendcount,
-    MPI_Datatype sendtype,
-    _Out_opt_ void* recvbuf,
-    int recvcount,
-    MPI_Datatype recvtype,
-    int root,
-    MPI_Comm comm
-    );
-
-int
-MPIAPI
-MPI_Gatherv(
-    _In_ void* sendbuf,
-    int sendcount,
-    MPI_Datatype sendtype,
-    _Out_opt_ void* recvbuf,
-    _In_opt_ int* recvcounts,
-    _In_opt_ int* displs,
-    MPI_Datatype recvtype,
-    int root,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Gatherv(
-    _In_ void* sendbuf,
-    int sendcount,
-    MPI_Datatype sendtype,
-    _Out_opt_ void* recvbuf,
-    _In_opt_ int* recvcounts,
-    _In_opt_ int* displs,
-    MPI_Datatype recvtype,
-    int root,
-    MPI_Comm comm
-    );
-
-
-/*---------------------------------------------*/
-/* Section 5.6: Scatter                        */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Scatter(
-    _In_ void* sendbuf,
-    int sendcount,
-    MPI_Datatype sendtype,
-    _Out_ void* recvbuf,
-    int recvcount,
-    MPI_Datatype recvtype,
-    int root,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Scatter(
-    _In_ void* sendbuf,
-    int sendcount,
-    MPI_Datatype sendtype,
-    _Out_ void* recvbuf,
-    int recvcount,
-    MPI_Datatype recvtype,
-    int root,
-    MPI_Comm comm
-    );
-
-int
-MPIAPI
-MPI_Scatterv(
-    _In_ void* sendbuf,
-    _In_ int* sendcounts,
-    _In_ int* displs,
-    MPI_Datatype sendtype,
-    _Out_ void* recvbuf,
-    int recvcount,
-    MPI_Datatype recvtype,
-    int root,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Scatterv(
-    _In_ void* sendbuf,
-    _In_ int* sendcounts,
-    _In_ int* displs,
-    MPI_Datatype sendtype,
-    _Out_ void* recvbuf,
-    int recvcount,
-    MPI_Datatype recvtype,
-    int root,
-    MPI_Comm comm
-    );
-
-
-/*---------------------------------------------*/
-/* Section 5.6: Gather-to-all                  */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Allgather(
-    _In_ void* sendbuf,
-    int sendcount,
-    MPI_Datatype sendtype,
-    _Out_ void* recvbuf,
-    int recvcount,
-    MPI_Datatype recvtype,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Allgather(
-    _In_ void* sendbuf,
-    int sendcount,
-    MPI_Datatype sendtype,
-    _Out_ void* recvbuf,
-    int recvcount,
-    MPI_Datatype recvtype,
-    MPI_Comm comm
-    );
-
-int
-MPIAPI
-MPI_Allgatherv(
-    _In_ void* sendbuf,
-    int sendcount,
-    MPI_Datatype sendtype,
-    _Out_ void* recvbuf,
-    _In_ int* recvcounts,
-    _In_ int* displs,
-    MPI_Datatype recvtype,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Allgatherv(
-    _In_ void* sendbuf,
-    int sendcount,
-    MPI_Datatype sendtype,
-    _Out_ void* recvbuf,
-    _In_ int* recvcounts,
-    _In_ int* displs,
-    MPI_Datatype recvtype,
-    MPI_Comm comm
-    );
-
-
-/*---------------------------------------------*/
-/* Section 5.6: All-to-All Scatter/Gather      */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Alltoall(
-    _In_ void* sendbuf,
-    int sendcount,
-    MPI_Datatype sendtype,
-    _Out_ void* recvbuf,
-    int recvcount,
-    MPI_Datatype recvtype,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Alltoall(
-    _In_ void* sendbuf,
-    int sendcount,
-    MPI_Datatype sendtype,
-    _Out_ void* recvbuf,
-    int recvcount,
-    MPI_Datatype recvtype,
-    MPI_Comm comm
-    );
-
-int
-MPIAPI
-MPI_Alltoallv(
-    _In_ void* sendbuf,
-    _In_ int* sendcounts,
-    _In_ int* sdispls,
-    MPI_Datatype sendtype,
-    _Out_ void* recvbuf,
-    _In_ int* recvcounts,
-    _In_ int* rdispls,
-    MPI_Datatype recvtype,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Alltoallv(
-    _In_ void* sendbuf,
-    _In_ int* sendcounts,
-    _In_ int* sdispls,
-    MPI_Datatype sendtype,
-    _Out_ void* recvbuf,
-    _In_ int* recvcounts,
-    _In_ int* rdispls,
-    MPI_Datatype recvtype,
-    MPI_Comm comm
-    );
-
-int
-MPIAPI
-MPI_Alltoallw(
-    _In_ void* sendbuf,
-    _In_ int sendcounts[],
-    _In_ int sdispls[],
-    _In_ MPI_Datatype sendtypes[],
-    _Out_ void* recvbuf,
-    _In_ int recvcounts[],
-    _In_ int rdispls[],
-    _In_ MPI_Datatype recvtypes[],
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Alltoallw(
-    _In_ void* sendbuf,
-    _In_ int sendcounts[],
-    _In_ int sdispls[],
-    _In_ MPI_Datatype sendtypes[],
-    _Out_ void* recvbuf,
-    _In_ int recvcounts[],
-    _In_ int rdispls[],
-    _In_ MPI_Datatype recvtypes[],
-    MPI_Comm comm
-    );
-
-
-/*---------------------------------------------*/
-/* Section 5.9: Global Reduction Operations    */
-/*---------------------------------------------*/
-
-typedef
-void
-(MPIAPI MPI_User_function)(
-    _In_count_(*len) void* invec,
-    _Inout_ void* inoutvec,
-    _In_ int* len,
-    _In_ MPI_Datatype* datatype
-    );
-
-int
-MPIAPI
-MPI_Op_create(
-    _In_ MPI_User_function* function,
-    int commute,
-    _Out_ MPI_Op* op
-    );
-int
-MPIAPI
-PMPI_Op_create(
-    _In_ MPI_User_function* function,
-    int commute,
-    _Out_ MPI_Op* op
-    );
-
-int
-MPIAPI
-MPI_Op_free(
-    _Inout_ MPI_Op* op
-    );
-int
-MPIAPI
-PMPI_Op_free(
-    _Inout_ MPI_Op* op
-    );
-
-int
-MPIAPI
-MPI_Reduce(
-    _In_ void* sendbuf,
-    _Out_opt_ void* recvbuf,
-    int count,
-    MPI_Datatype datatype,
-    MPI_Op op,
-    int root,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Reduce(
-    _In_ void* sendbuf,
-    _Out_opt_ void* recvbuf,
-    int count,
-    MPI_Datatype datatype,
-    MPI_Op op,
-    int root,
-    MPI_Comm comm
-    );
-
-int
-MPIAPI
-MPI_Allreduce(
-    _In_ void* sendbuf,
-    _Out_ void* recvbuf,
-    int count,
-    MPI_Datatype datatype,
-    MPI_Op op,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Allreduce(
-    _In_ void* sendbuf,
-    _Out_ void* recvbuf,
-    int count,
-    MPI_Datatype datatype,
-    MPI_Op op,
-    MPI_Comm comm
-    );
-
-int
-MPIAPI
-MPI_Reduce_local(
-    _In_ void *inbuf,
-    _Inout_ void *inoutbuf,
-    int count,
-    MPI_Datatype datatype,
-    MPI_Op op
-    );
-int
-MPIAPI
-PMPI_Reduce_local(
-    _In_ void *inbuf,
-    _Inout_ void *inoutbuf,
-    int count,
-    MPI_Datatype datatype,
-    MPI_Op op
-    );
-
-/*---------------------------------------------*/
-/* Section 5.10: Reduce-Scatter                */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Reduce_scatter(
-    _In_ void* sendbuf,
-    _Out_ void* recvbuf,
-    _In_ int* recvcounts,
-    MPI_Datatype datatype,
-    MPI_Op op,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Reduce_scatter(
-    _In_ void* sendbuf,
-    _Out_ void* recvbuf,
-    _In_ int* recvcounts,
-    MPI_Datatype datatype,
-    MPI_Op op,
-    MPI_Comm comm
-    );
-
-
-/*---------------------------------------------*/
-/* Section 5.11: Scan                          */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Scan(
-    _In_ void* sendbuf,
-    _Out_ void* recvbuf,
-    int count,
-    MPI_Datatype datatype,
-    MPI_Op op,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Scan(
-    _In_ void* sendbuf,
-    _Out_ void* recvbuf,
-    int count,
-    MPI_Datatype datatype,
-    MPI_Op op,
-    MPI_Comm comm
-    );
-
-int
-MPIAPI
-MPI_Exscan(
-    _In_ void* sendbuf,
-    _Out_ void* recvbuf,
-    int count,
-    MPI_Datatype datatype,
-    MPI_Op op,
-    MPI_Comm comm
-    );
-int
-MPIAPI
-PMPI_Exscan(
-    _In_ void* sendbuf,
-    _Out_ void* recvbuf,
-    int count,
-    MPI_Datatype datatype,
-    MPI_Op op,
-    MPI_Comm comm
-    );
-
-
-/*---------------------------------------------------------------------------*/
-/* Chapter 6: Groups, Contexts, Communicators, and Caching                   */
-/*---------------------------------------------------------------------------*/
-
-/*---------------------------------------------*/
-/* Section 6.3: Group Management               */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Group_size(
-    MPI_Group group,
-    _Out_ int* size
-    );
-int
-MPIAPI
-PMPI_Group_size(
-    MPI_Group group,
-    _Out_ int* size
-    );
-
-int
-MPIAPI
-MPI_Group_rank(
-    MPI_Group group,
-    _Out_ int* rank
-    );
-int
-MPIAPI
-PMPI_Group_rank(
-    MPI_Group group,
-    _Out_ int* rank
-    );
-
-int
-MPIAPI
-MPI_Group_translate_ranks(
-    MPI_Group group1,
-    int n,
-    _In_count_(n) int* ranks1,
-    MPI_Group group2,
-    _Out_ int* ranks2
-    );
-
-int
-MPIAPI
-PMPI_Group_translate_ranks(
-    MPI_Group group1,
-    int n,
-    _In_count_(n) int* ranks1,
-    MPI_Group group2,
-    _Out_ int* ranks2
-    );
-
-/* Results of the compare operations */
-#define MPI_IDENT       0
-#define MPI_CONGRUENT   1
-#define MPI_SIMILAR     2
-#define MPI_UNEQUAL     3
-
-int
-MPIAPI
-MPI_Group_compare(
-    MPI_Group group1,
-    MPI_Group group2,
-    _Out_ int* result
-    );
-int
-MPIAPI
-PMPI_Group_compare(
-    MPI_Group group1,
-    MPI_Group group2,
-    _Out_ int* result
-    );
-
-int
-MPIAPI
-MPI_Comm_group(
-    MPI_Comm comm,
-    _Out_ MPI_Group* group
-    );
-int
-MPIAPI
-PMPI_Comm_group(
-    MPI_Comm comm,
-    _Out_ MPI_Group* group
-    );
-
-int
-MPIAPI
-MPI_Group_union(
-    MPI_Group group1,
-    MPI_Group group2,
-    _Out_ MPI_Group* newgroup
-    );
-int
-MPIAPI
-PMPI_Group_union(
-    MPI_Group group1,
-    MPI_Group group2,
-    _Out_ MPI_Group* newgroup
-    );
-
-int
-MPIAPI
-MPI_Group_intersection(
-    MPI_Group group1,
-    MPI_Group group2,
-    _Out_ MPI_Group* newgroup
-    );
-int
-MPIAPI
-PMPI_Group_intersection(
-    MPI_Group group1,
-    MPI_Group group2,
-    _Out_ MPI_Group* newgroup
-    );
-
-int
-MPIAPI
-MPI_Group_difference(
-    MPI_Group group1,
-    MPI_Group group2,
-    _Out_ MPI_Group* newgroup
-    );
-int
-MPIAPI
-PMPI_Group_difference(
-    MPI_Group group1,
-    MPI_Group group2,
-    _Out_ MPI_Group* newgroup
-    );
-
-int
-MPIAPI
-MPI_Group_incl(
-    MPI_Group group,
-    int n,
-    _In_count_(n) int* ranks,
-    _Out_ MPI_Group* newgroup
-    );
-int
-MPIAPI
-PMPI_Group_incl(
-    MPI_Group group,
-    int n,
-    _In_count_(n) int* ranks,
-    _Out_ MPI_Group* newgroup
-    );
-
-int
-MPIAPI
-MPI_Group_excl(
-    MPI_Group group,
-    int n,
-    _In_count_(n) int* ranks,
-    _Out_ MPI_Group* newgroup
-    );
-int
-MPIAPI
-PMPI_Group_excl(
-    MPI_Group group,
-    int n,
-    _In_count_(n) int* ranks,
-    _Out_ MPI_Group* newgroup
-    );
-
-int
-MPIAPI
-MPI_Group_range_incl(
-    MPI_Group group,
-    int n,
-    _In_count_(n) int ranges[][3],
-    _Out_ MPI_Group* newgroup
-    );
-int
-MPIAPI
-PMPI_Group_range_incl(
-    MPI_Group group,
-    int n,
-    _In_count_(n) int ranges[][3],
-    _Out_ MPI_Group* newgroup
-    );
-
-int
-MPIAPI
-MPI_Group_range_excl(
-    MPI_Group group,
-    int n,
-    _In_count_(n) int ranges[][3],
-    _Out_ MPI_Group* newgroup
-    );
-int
-MPIAPI
-PMPI_Group_range_excl(
-    MPI_Group group,
-    int n,
-    _In_count_(n) int ranges[][3],
-    _Out_ MPI_Group* newgroup
-    );
-
-int
-MPIAPI
-MPI_Group_free(
-    _Inout_ MPI_Group* group
-    );
-int
-MPIAPI
-PMPI_Group_free(
-    _Inout_ MPI_Group* group
-    );
-
-
-/*---------------------------------------------*/
-/* Section 6.4: Communicator Management        */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Comm_size(
-    MPI_Comm comm,
-    _Out_ int* size
-    );
-int
-MPIAPI
-PMPI_Comm_size(
-    MPI_Comm comm,
-    _Out_ int* size
-    );
-
-int
-MPIAPI
-MPI_Comm_rank(
-    MPI_Comm comm,
-    _Out_ int* rank
-    );
-int
-MPIAPI
-PMPI_Comm_rank(
-    MPI_Comm comm,
-    _Out_ int* rank
-    );
-
-int
-MPIAPI
-MPI_Comm_compare(
-    MPI_Comm comm1,
-    MPI_Comm comm2,
-    _Out_ int* result
-    );
-int
-MPIAPI
-PMPI_Comm_compare(
-    MPI_Comm comm1,
-    MPI_Comm comm2,
-    _Out_ int* result
-    );
-
-int
-MPIAPI
-MPI_Comm_dup(
-    MPI_Comm comm,
-    _Out_ MPI_Comm* newcomm
-    );
-int
-MPIAPI
-PMPI_Comm_dup(
-    MPI_Comm comm,
-    _Out_ MPI_Comm* newcomm
-    );
-
-int
-MPIAPI
-MPI_Comm_create(
-    MPI_Comm comm,
-    MPI_Group group,
-    _Out_ MPI_Comm* newcomm
-    );
-int
-MPIAPI
-PMPI_Comm_create(
-    MPI_Comm comm,
-    MPI_Group group,
-    _Out_ MPI_Comm* newcomm
-    );
-
-int
-MPIAPI
-MPI_Comm_split(
-    MPI_Comm comm,
-    int color,
-    int key,
-    _Out_ MPI_Comm* newcomm
-    );
-int
-MPIAPI
-PMPI_Comm_split(
-    MPI_Comm comm,
-    int color,
-    int key,
-    _Out_ MPI_Comm* newcomm
-    );
-
-int
-MPIAPI
-MPI_Comm_free(
-    _Inout_ MPI_Comm* comm
-    );
-int
-MPIAPI
-PMPI_Comm_free(
-    _Inout_ MPI_Comm* comm
-    );
-
-
-/*---------------------------------------------*/
-/* Section 6.6: Inter-Communication            */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Comm_test_inter(
-    MPI_Comm comm,
-    _Out_ int* flag
-    );
-int
-MPIAPI
-PMPI_Comm_test_inter(
-    MPI_Comm comm,
-    _Out_ int* flag
-    );
-
-int
-MPIAPI
-MPI_Comm_remote_size(
-    MPI_Comm comm,
-    _Out_ int* size
-    );
-int
-MPIAPI
-PMPI_Comm_remote_size(
-    MPI_Comm comm,
-    _Out_ int* size
-    );
-
-int
-MPIAPI
-MPI_Comm_remote_group(
-    MPI_Comm comm,
-    _Out_ MPI_Group* group
-    );
-int
-MPIAPI
-PMPI_Comm_remote_group(
-    MPI_Comm comm,
-    _Out_ MPI_Group* group
-    );
-
-int
-MPIAPI
-MPI_Intercomm_create(
-    MPI_Comm local_comm,
-    int local_leader,
-    MPI_Comm peer_comm,
-    int remote_leader,
-    int tag,
-    _Out_ MPI_Comm* newintercomm
-    );
-int
-MPIAPI
-PMPI_Intercomm_create(
-    MPI_Comm local_comm,
-    int local_leader,
-    MPI_Comm peer_comm,
-    int remote_leader,
-    int tag,
-    _Out_ MPI_Comm* newintercomm
-    );
-
-int
-MPIAPI
-MPI_Intercomm_merge(
-    MPI_Comm intercomm,
-    int high,
-    _Out_ MPI_Comm* newintracomm
-    );
-int
-MPIAPI
-PMPI_Intercomm_merge(
-    MPI_Comm intercomm,
-    int high,
-    _Out_ MPI_Comm* newintracomm
-    );
-
-
-/*---------------------------------------------*/
-/* Section 6.7: Caching                        */
-/*---------------------------------------------*/
-
-#define MPI_KEYVAL_INVALID  0x24000000
-
-typedef
-int
-(MPIAPI MPI_Comm_copy_attr_function)(
-    MPI_Comm oldcomm,
-    int comm_keyval,
-    _In_opt_ void* extra_state,
-    _In_ void* attribute_val_in,
-    _Out_ void* attribute_val_out,
-    _Out_ int* flag
-    );
-
-typedef
-int
-(MPIAPI MPI_Comm_delete_attr_function)(
-    MPI_Comm comm,
-    int comm_keyval,
-    _In_ void* attribute_val,
-    _In_opt_ void* extra_state
-    );
-
-#define MPI_COMM_NULL_COPY_FN ((MPI_Comm_copy_attr_function*)0)
-#define MPI_COMM_NULL_DELETE_FN ((MPI_Comm_delete_attr_function*)0)
-#define MPI_COMM_DUP_FN ((MPI_Comm_copy_attr_function*)MPIR_Dup_fn)
-
-int
-MPIAPI
-MPI_Comm_create_keyval(
-    _In_opt_ MPI_Comm_copy_attr_function* comm_copy_attr_fn,
-    _In_opt_ MPI_Comm_delete_attr_function* comm_delete_attr_fn,
-    _Out_ int* comm_keyval,
-    _In_opt_ void* extra_state
-    );
-int
-MPIAPI
-PMPI_Comm_create_keyval(
-    _In_opt_ MPI_Comm_copy_attr_function* comm_copy_attr_fn,
-    _In_opt_ MPI_Comm_delete_attr_function* comm_delete_attr_fn,
-    _Out_ int* comm_keyval,
-    _In_opt_ void* extra_state
-    );
-
-int
-MPIAPI
-MPI_Comm_free_keyval(
-    _Inout_ int* comm_keyval
-    );
-int
-MPIAPI
-PMPI_Comm_free_keyval(
-    _Inout_ int* comm_keyval
-    );
-
-int
-MPIAPI
-MPI_Comm_set_attr(
-    MPI_Comm comm,
-    int comm_keyval,
-    _In_ void* attribute_val
-    );
-int
-MPIAPI
-PMPI_Comm_set_attr(
-    MPI_Comm comm,
-    int comm_keyval,
-    _In_ void* attribute_val
-    );
-
-
-/* Predefined comm attribute key values */
-/* C Versions (return pointer to value),
-   Fortran Versions (return integer value).
-
-   DO NOT CHANGE THESE.  The values encode:
-   builtin kind (0x1 in bit 30-31)
-   Keyval object (0x9 in bits 26-29)
-   for communicator (0x1 in bits 22-25)
-
-   Fortran versions of the attributes are formed by adding one to
-   the C version.
- */
-#define MPI_TAG_UB          0x64400001
-#define MPI_HOST            0x64400003
-#define MPI_IO              0x64400005
-#define MPI_WTIME_IS_GLOBAL 0x64400007
-#define MPI_UNIVERSE_SIZE   0x64400009
-#define MPI_LASTUSEDCODE    0x6440000b
-#define MPI_APPNUM          0x6440000d
-
-int
-MPIAPI
-MPI_Comm_get_attr(
-    MPI_Comm comm,
-    int comm_keyval,
-    _Out_ void* attribute_val,
-    _Out_ int* flag
-    );
-int
-MPIAPI
-PMPI_Comm_get_attr(
-    MPI_Comm comm,
-    int comm_keyval,
-    _Out_ void* attribute_val,
-    _Out_ int* flag
-    );
-
-int
-MPIAPI
-MPI_Comm_delete_attr(
-    MPI_Comm comm,
-    int comm_keyval
-    );
-int
-MPIAPI
-PMPI_Comm_delete_attr(
-    MPI_Comm comm,
-    int comm_keyval
-    );
-
-
-typedef
-int
-(MPIAPI MPI_Win_copy_attr_function)(
-    MPI_Win oldwin,
-    int win_keyval,
-    _In_opt_ void* extra_state,
-    _In_ void* attribute_val_in,
-    _Out_ void* attribute_val_out,
-    _Out_ int* flag
-    );
-
-typedef
-int
-(MPIAPI MPI_Win_delete_attr_function)(
-    MPI_Win win,
-    int win_keyval,
-    _In_ void* attribute_val,
-    _In_opt_ void* extra_state
-    );
-
-#define MPI_WIN_NULL_COPY_FN ((MPI_Win_copy_attr_function*)0)
-#define MPI_WIN_NULL_DELETE_FN ((MPI_Win_delete_attr_function*)0)
-#define MPI_WIN_DUP_FN ((MPI_Win_copy_attr_function*)MPIR_Dup_fn)
-
-int
-MPIAPI
-MPI_Win_create_keyval(
-    _In_ MPI_Win_copy_attr_function* win_copy_attr_fn,
-    _In_ MPI_Win_delete_attr_function* win_delete_attr_fn,
-    _Out_ int* win_keyval,
-    _In_opt_ void* extra_state
-    );
-int
-MPIAPI
-PMPI_Win_create_keyval(
-    _In_ MPI_Win_copy_attr_function* win_copy_attr_fn,
-    _In_ MPI_Win_delete_attr_function* win_delete_attr_fn,
-    _Out_ int* win_keyval,
-    _In_opt_ void* extra_state
-    );
-
-int
-MPIAPI
-MPI_Win_free_keyval(
-    _Inout_ int* win_keyval
-    );
-int
-MPIAPI
-PMPI_Win_free_keyval(
-    _Inout_ int* win_keyval
-    );
-
-int
-MPIAPI
-MPI_Win_set_attr(
-    MPI_Win win,
-    int win_keyval,
-    _In_ void* attribute_val
-    );
-int
-MPIAPI
-PMPI_Win_set_attr(
-    MPI_Win win,
-    int win_keyval,
-    _In_ void* attribute_val
-    );
-
-
-/* Predefined window key value attributes */
-#define MPI_WIN_BASE        0x66000001
-#define MPI_WIN_SIZE        0x66000003
-#define MPI_WIN_DISP_UNIT   0x66000005
-
-int
-MPIAPI
-MPI_Win_get_attr(
-    MPI_Win win,
-    int win_keyval,
-    _Out_ void* attribute_val,
-    _Out_ int* flag
-    );
-int
-MPIAPI
-PMPI_Win_get_attr(
-    MPI_Win win,
-    int win_keyval,
-    _Out_ void* attribute_val,
-    _Out_ int* flag
-    );
-
-int
-MPIAPI
-MPI_Win_delete_attr(
-    MPI_Win win,
-    int win_keyval
-    );
-int
-MPIAPI
-PMPI_Win_delete_attr(
-    MPI_Win win,
-    int win_keyval
-    );
-
-
-typedef
-int
-(MPIAPI MPI_Type_copy_attr_function)(
-    MPI_Datatype olddatatype,
-    int datatype_keyval,
-    _In_opt_ void* extra_state,
-    _In_ void* attribute_val_in,
-    _Out_ void* attribute_val_out,
-    _Out_ int* flag
-    );
-
-typedef
-int
-(MPIAPI MPI_Type_delete_attr_function)(
-    MPI_Datatype datatype,
-    int datatype_keyval,
-    _In_ void* attribute_val,
-    _In_opt_ void* extra_state
-    );
-
-#define MPI_TYPE_NULL_COPY_FN ((MPI_Type_copy_attr_function*)0)
-#define MPI_TYPE_NULL_DELETE_FN ((MPI_Type_delete_attr_function*)0)
-#define MPI_TYPE_DUP_FN ((MPI_Type_copy_attr_function*)MPIR_Dup_fn)
-
-int
-MPIAPI
-MPI_Type_create_keyval(
-    _In_ MPI_Type_copy_attr_function* type_copy_attr_fn,
-    _In_ MPI_Type_delete_attr_function* type_delete_attr_fn,
-    _Out_ int* type_keyval,
-    _In_opt_ void* extra_state
-    );
-int
-MPIAPI
-PMPI_Type_create_keyval(
-    _In_ MPI_Type_copy_attr_function* type_copy_attr_fn,
-    _In_ MPI_Type_delete_attr_function* type_delete_attr_fn,
-    _Out_ int* type_keyval,
-    _In_opt_ void* extra_state
-    );
-
-int
-MPIAPI
-MPI_Type_free_keyval(
-    _Inout_ int* type_keyval
-    );
-int
-MPIAPI
-PMPI_Type_free_keyval(
-    _Inout_ int* type_keyval
-    );
-
-int
-MPIAPI
-MPI_Type_set_attr(
-    MPI_Datatype type,
-    int type_keyval,
-    _In_ void* attribute_val
-    );
-int
-MPIAPI
-PMPI_Type_set_attr(
-    MPI_Datatype type,
-    int type_keyval,
-    _In_ void* attribute_val
-    );
-
-int
-MPIAPI
-MPI_Type_get_attr(
-    MPI_Datatype type,
-    int type_keyval,
-    _Out_ void* attribute_val,
-    _Out_ int* flag
-    );
-int
-MPIAPI
-PMPI_Type_get_attr(
-    MPI_Datatype type,
-    int type_keyval,
-    _Out_ void* attribute_val,
-    _Out_ int* flag
-    );
-
-int
-MPIAPI
-MPI_Type_delete_attr(
-    MPI_Datatype datatype,
-    int type_keyval
-    );
-int
-MPIAPI
-PMPI_Type_delete_attr(
-    MPI_Datatype datatype,
-    int type_keyval
-    );
-
-
-/*---------------------------------------------*/
-/* Section 6.8: Naming Objects                 */
-/*---------------------------------------------*/
-
-#define MPI_MAX_OBJECT_NAME 128
-
-int
-MPIAPI
-MPI_Comm_set_name(
-    MPI_Comm comm,
-    _In_z_ char* comm_name
-    );
-int
-MPIAPI
-PMPI_Comm_set_name(
-    MPI_Comm comm,
-    _In_z_ char* comm_name
-    );
-
-int
-MPIAPI
-MPI_Comm_get_name(
-    MPI_Comm comm,
-    _Out_z_cap_post_count_(MPI_MAX_OBJECT_NAME,*resultlen) char* comm_name,
-    _Out_ int* resultlen
-    );
-int
-MPIAPI
-PMPI_Comm_get_name(
-    MPI_Comm comm,
-    _Out_z_cap_post_count_(MPI_MAX_OBJECT_NAME,*resultlen) char* comm_name,
-    _Out_ int* resultlen
-    );
-
-int
-MPIAPI
-MPI_Type_set_name(
-    MPI_Datatype type,
-    _In_z_ char* type_name
-    );
-int
-MPIAPI
-PMPI_Type_set_name(
-    MPI_Datatype type,
-    _In_z_ char* type_name
-    );
-
-int
-MPIAPI
-MPI_Type_get_name(
-    MPI_Datatype type,
-    _Out_z_cap_post_count_(MPI_MAX_OBJECT_NAME,*resultlen) char* type_name,
-    _Out_ int* resultlen
-    );
-int
-MPIAPI
-PMPI_Type_get_name(
-    MPI_Datatype type,
-    _Out_z_cap_post_count_(MPI_MAX_OBJECT_NAME,*resultlen) char* type_name,
-    _Out_ int* resultlen
-    );
-
-int
-MPIAPI
-MPI_Win_set_name(
-    MPI_Win win,
-    _In_z_ char* win_name
-    );
-int
-MPIAPI
-PMPI_Win_set_name(
-    MPI_Win win,
-    _In_z_ char* win_name
-    );
-
-int
-MPIAPI
-MPI_Win_get_name(
-    MPI_Win win,
-    _Out_z_cap_post_count_(MPI_MAX_OBJECT_NAME,*resultlen) char* win_name,
-    _Out_ int* resultlen
-    );
-int
-MPIAPI
-PMPI_Win_get_name(
-    MPI_Win win,
-    _Out_z_cap_post_count_(MPI_MAX_OBJECT_NAME,*resultlen) char* win_name,
-    _Out_ int* resultlen
-    );
-
-
-/*---------------------------------------------------------------------------*/
-/* Chapter 7: Process Topologies                                             */
-/*---------------------------------------------------------------------------*/
-
-int
-MPIAPI
-MPI_Cart_create(
-    MPI_Comm comm_old,
-    int ndims,
-    _In_count_(ndims) int* dims,
-    _In_count_(ndims) int* periods,
-    int reorder,
-    _Out_ MPI_Comm* comm_cart
-    );
-int
-MPIAPI
-PMPI_Cart_create(
-    MPI_Comm comm_old,
-    int ndims,
-    _In_count_(ndims) int* dims,
-    _In_count_(ndims) int* periods,
-    int reorder,
-    _Out_ MPI_Comm* comm_cart
-    );
-
-int
-MPIAPI
-MPI_Dims_create(
-    int nnodes,
-    int ndims,
-    _Inout_count_(ndims) int* dims
-    );
-int
-MPIAPI
-PMPI_Dims_create(
-    int nnodes,
-    int ndims,
-    _Inout_count_(ndims) int* dims
-    );
-
-int
-MPIAPI
-MPI_Graph_create(
-    MPI_Comm comm_old,
-    int nnodes,
-    _In_count_(nnodes) int* index,
-    _In_ int* edges,
-    int reorder,
-    _Out_ MPI_Comm* comm_cart
-    );
-int
-MPIAPI
-PMPI_Graph_create(
-    MPI_Comm comm_old,
-    int nnodes,
-    _In_count_(nnodes) int* index,
-    _In_ int* edges,
-    int reorder,
-    _Out_ MPI_Comm* comm_cart
-    );
-
-
-/* Topology types */
-enum
-{
-    MPI_GRAPH   = 1,
-    MPI_CART    = 2
-};
-
-int
-MPIAPI
-MPI_Topo_test(
-    MPI_Comm comm,
-    _Out_ int* status
-    );
-int
-MPIAPI
-PMPI_Topo_test(
-    MPI_Comm comm,
-    _Out_ int* status
-    );
-
-int
-MPIAPI
-MPI_Graphdims_get(
-    MPI_Comm comm,
-    _Out_ int* nnodes,
-    _Out_ int* nedges
-    );
-int
-MPIAPI
-PMPI_Graphdims_get(
-    MPI_Comm comm,
-    _Out_ int* nnodes,
-    _Out_ int* nedges
-    );
-
-int
-MPIAPI
-MPI_Graph_get(
-    MPI_Comm comm,
-    int maxindex,
-    int maxedges,
-    _Out_cap_(maxindex) int* index,
-    _Out_cap_(maxedges) int* edges
-    );
-int
-MPIAPI
-PMPI_Graph_get(
-    MPI_Comm comm,
-    int maxindex,
-    int maxedges,
-    _Out_cap_(maxindex) int* index,
-    _Out_cap_(maxedges) int* edges
-    );
-
-int
-MPIAPI
-MPI_Cartdim_get(
-    MPI_Comm comm,
-    _Out_ int* ndims
-    );
-int
-MPIAPI
-PMPI_Cartdim_get(
-    MPI_Comm comm,
-    _Out_ int* ndims
-    );
-
-int
-MPIAPI
-MPI_Cart_get(
-    MPI_Comm comm,
-    int maxdims,
-    _Out_cap_(maxdims) int* dims,
-    _Out_cap_(maxdims) int* periods,
-    _Out_cap_(maxdims) int* coords
-    );
-int
-MPIAPI
-PMPI_Cart_get(
-    MPI_Comm comm,
-    int maxdims,
-    _Out_cap_(maxdims) int* dims,
-    _Out_cap_(maxdims) int* periods,
-    _Out_cap_(maxdims) int* coords
-    );
-
-int
-MPIAPI
-MPI_Cart_rank(
-    MPI_Comm comm,
-    _In_ int* coords,
-    _Out_ int* rank
-    );
-int
-MPIAPI
-PMPI_Cart_rank(
-    MPI_Comm comm,
-    _In_ int* coords,
-    _Out_ int* rank
-    );
-
-int
-MPIAPI
-MPI_Cart_coords(
-    MPI_Comm comm,
-    int rank,
-    int maxdims,
-    _Out_cap_(maxdims) int* coords
-    );
-int
-MPIAPI
-PMPI_Cart_coords(
-    MPI_Comm comm,
-    int rank,
-    int maxdims,
-    _Out_cap_(maxdims) int* coords
-    );
-
-int
-MPIAPI
-MPI_Graph_neighbors_count(
-    MPI_Comm comm,
-    int rank,
-    _Out_ int* nneighbors
-    );
-int
-MPIAPI
-PMPI_Graph_neighbors_count(
-    MPI_Comm comm,
-    int rank,
-    _Out_ int* nneighbors
-    );
-
-int
-MPIAPI
-MPI_Graph_neighbors(
-    MPI_Comm comm,
-    int rank,
-    int maxneighbors,
-    _Out_cap_(maxneighbors) int* neighbors
-    );
-int
-MPIAPI
-PMPI_Graph_neighbors(
-    MPI_Comm comm,
-    int rank,
-    int maxneighbors,
-    _Out_cap_(maxneighbors) int* neighbors
-    );
-
-int
-MPIAPI
-MPI_Cart_shift(
-    MPI_Comm comm,
-    int direction,
-    int disp,
-    _Out_ int* rank_source,
-    _Out_ int* rank_dest
-    );
-int
-MPIAPI
-PMPI_Cart_shift(
-    MPI_Comm comm,
-    int direction,
-    int disp,
-    _Out_ int* rank_source,
-    _Out_ int* rank_dest
-    );
-
-int
-MPIAPI
-MPI_Cart_sub(
-    MPI_Comm comm,
-    _In_ int* remain_dims,
-    _Out_ MPI_Comm* newcomm
-    );
-int
-MPIAPI
-PMPI_Cart_sub(
-    MPI_Comm comm,
-    _In_ int* remain_dims,
-    _Out_ MPI_Comm* newcomm
-    );
-
-int
-MPIAPI
-MPI_Cart_map(
-    MPI_Comm comm,
-    int ndims,
-    _In_count_(ndims) int* dims,
-    _In_count_(ndims) int* periods,
-    _Out_ int* newrank
-    );
-int
-MPIAPI
-PMPI_Cart_map(
-    MPI_Comm comm,
-    int ndims,
-    _In_count_(ndims) int* dims,
-    _In_count_(ndims) int* periods,
-    _Out_ int* newrank
-    );
-
-int
-MPIAPI
-MPI_Graph_map(
-    MPI_Comm comm,
-    int nnodes,
-    _In_count_(nnodes) int* index,
-    _In_ int* edges,
-    _Out_ int* newrank
-    );
-int
-MPIAPI
-PMPI_Graph_map(
-    MPI_Comm comm,
-    int nnodes,
-    _In_count_(nnodes) int* index,
-    _In_ int* edges,
-    _Out_ int* newrank
-    );
-
-
-/*---------------------------------------------------------------------------*/
-/* Chapter 8: Environmental Management                                       */
-/*---------------------------------------------------------------------------*/
-
-/*---------------------------------------------*/
-/* Section 8.1: Implementation Information     */
-/*---------------------------------------------*/
-
-#define MPI_VERSION     2
-#define MPI_SUBVERSION  0
-
-int
-MPIAPI
-MPI_Get_version(
-    _Out_ int* version,
-    _Out_ int* subversion
-    );
-int
-MPIAPI
-PMPI_Get_version(
-    _Out_ int* version,
-    _Out_ int* subversion
-    );
-
-#define MPI_MAX_PROCESSOR_NAME  128
-
-int
-MPIAPI
-MPI_Get_processor_name(
-    _Out_z_cap_post_count_(MPI_MAX_PROCESSOR_NAME,*resultlen) char* name,
-    _Out_ int* resultlen
-    );
-int
-MPIAPI
-PMPI_Get_processor_name(
-    _Out_z_cap_post_count_(MPI_MAX_PROCESSOR_NAME,*resultlen) char* name,
-    _Out_ int* resultlen
-    );
-
-/*---------------------------------------------*/
-/* Section 8.2: Memory Allocation              */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Alloc_mem(
-    MPI_Aint size,
-    MPI_Info info,
-    _Out_ void* baseptr
-    );
-int
-MPIAPI
-PMPI_Alloc_mem(
-    MPI_Aint size,
-    MPI_Info info,
-    _Out_ void* baseptr
-    );
-
-int
-MPIAPI
-MPI_Free_mem(
-    _In_ void* base
-    );
-int
-MPIAPI
-PMPI_Free_mem(
-    _In_ void* base
-    );
-
-
-/*---------------------------------------------*/
-/* Section 8.3: Error Handling                 */
-/*---------------------------------------------*/
-
-typedef
-void
-(MPIAPI MPI_Comm_errhandler_fn)(
-    _In_ MPI_Comm* comm,
-    _Inout_ int* errcode,
-    ...
-    );
-
-int
-MPIAPI
-MPI_Comm_create_errhandler(
-    _In_ MPI_Comm_errhandler_fn* function,
-    _Out_ MPI_Errhandler* errhandler
-    );
-int
-MPIAPI
-PMPI_Comm_create_errhandler(
-    _In_ MPI_Comm_errhandler_fn* function,
-    _Out_ MPI_Errhandler* errhandler
-    );
-
-int
-MPIAPI
-MPI_Comm_set_errhandler(
-    MPI_Comm comm,
-    MPI_Errhandler errhandler
-    );
-int
-MPIAPI
-PMPI_Comm_set_errhandler(
-    MPI_Comm comm,
-    MPI_Errhandler errhandler
-    );
-
-int
-MPIAPI
-MPI_Comm_get_errhandler(
-    MPI_Comm comm,
-    _Out_ MPI_Errhandler* errhandler
-    );
-int
-MPIAPI
-PMPI_Comm_get_errhandler(
-    MPI_Comm comm,
-    _Out_ MPI_Errhandler* errhandler
-    );
-
-
-typedef
-void
-(MPIAPI MPI_Win_errhandler_fn)(
-    _In_ MPI_Win* win,
-    _Inout_ int* errcode,
-    ...
-    );
-
-int
-MPIAPI
-MPI_Win_create_errhandler(
-    _In_ MPI_Win_errhandler_fn* function,
-    _Out_ MPI_Errhandler* errhandler
-    );
-int
-MPIAPI
-PMPI_Win_create_errhandler(
-    _In_ MPI_Win_errhandler_fn* function,
-    _Out_ MPI_Errhandler* errhandler
-    );
-
-int
-MPIAPI
-MPI_Win_set_errhandler(
-    MPI_Win win,
-    MPI_Errhandler errhandler
-    );
-int
-MPIAPI
-PMPI_Win_set_errhandler(
-    MPI_Win win,
-    MPI_Errhandler errhandler
-    );
-
-int
-MPIAPI
-MPI_Win_get_errhandler(
-    MPI_Win win,
-    _Out_ MPI_Errhandler* errhandler
-    );
-int
-MPIAPI
-PMPI_Win_get_errhandler(
-    MPI_Win win,
-    _Out_ MPI_Errhandler* errhandler
-    );
-
-
-typedef
-void
-(MPIAPI MPI_File_errhandler_fn)(
-    _In_ MPI_File* file,
-    _Inout_ int* errcode,
-    ...
-    );
-
-int
-MPIAPI
-MPI_File_create_errhandler(
-    _In_ MPI_File_errhandler_fn* function,
-    _Out_ MPI_Errhandler* errhandler
-    );
-int
-MPIAPI
-PMPI_File_create_errhandler(
-    _In_ MPI_File_errhandler_fn* function,
-    _Out_ MPI_Errhandler* errhandler
-    );
-
-int
-MPIAPI
-MPI_File_set_errhandler(
-    MPI_File file,
-    MPI_Errhandler errhandler
-    );
-int
-MPIAPI
-PMPI_File_set_errhandler(
-    MPI_File file,
-    MPI_Errhandler errhandler
-    );
-
-int
-MPIAPI
-MPI_File_get_errhandler(
-    MPI_File file,
-    _Out_ MPI_Errhandler* errhandler
-    );
-int
-MPIAPI
-PMPI_File_get_errhandler(
-    MPI_File file,
-    _Out_ MPI_Errhandler* errhandler
-    );
-
-int
-MPIAPI
-MPI_Errhandler_free(
-    _Inout_ MPI_Errhandler* errhandler
-    );
-int
-MPIAPI
-PMPI_Errhandler_free(
-    _Inout_ MPI_Errhandler* errhandler
-    );
-
-#define MPI_MAX_ERROR_STRING    512
-
-int
-MPIAPI
-MPI_Error_string(
-    int errorcode,
-    _Out_z_cap_post_count_(MPI_MAX_ERROR_STRING,*resultlen) char* string,
-    _Out_ int* resultlen
-    );
-int
-MPIAPI
-PMPI_Error_string(
-    int errorcode,
-    _Out_z_cap_post_count_(MPI_MAX_ERROR_STRING,*resultlen) char* string,
-    _Out_ int* resultlen
-    );
-
-
-/*---------------------------------------------*/
-/* Section 8.4: Error Codes and Classes        */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Error_class(
-    int errorcode,
-    _Out_ int* errorclass
-    );
-int
-MPIAPI
-PMPI_Error_class(
-    int errorcode,
-    _Out_ int* errorclass
-    );
-
-int
-MPIAPI
-MPI_Add_error_class(
-    _Out_ int* errorclass
-    );
-int
-MPIAPI
-PMPI_Add_error_class(
-    _Out_ int* errorclass
-    );
-
-int
-MPIAPI
-MPI_Add_error_code(
-    int errorclass,
-    _Out_ int* errorcode
-    );
-int
-MPIAPI
-PMPI_Add_error_code(
-    int errorclass,
-    _Out_ int* errorcode
-    );
-
-int
-MPIAPI
-MPI_Add_error_string(
-    int errorcode,
-    _In_z_ char* string
-    );
-int
-MPIAPI
-PMPI_Add_error_string(
-    int errorcode,
-    _In_z_ char* string
-    );
-
-int
-MPIAPI
-MPI_Comm_call_errhandler(
-    MPI_Comm comm,
-    int errorcode
-    );
-int
-MPIAPI
-PMPI_Comm_call_errhandler(
-    MPI_Comm comm,
-    int errorcode
-    );
-
-int
-MPIAPI
-MPI_Win_call_errhandler(
-    MPI_Win win,
-    int errcode
-    );
-int
-MPIAPI
-PMPI_Win_call_errhandler(
-    MPI_Win win,
-    int errcode
-    );
-
-int
-MPIAPI
-MPI_File_call_errhandler(
-    MPI_File file,
-    int errorcode
-    );
-int
-MPIAPI
-PMPI_File_call_errhandler(
-    MPI_File file,
-    int errorcode
-    );
-
-
-/*---------------------------------------------*/
-/* Section 8.6: Timers and Synchronization     */
-/*---------------------------------------------*/
-
-double
-MPIAPI
-MPI_Wtime(
-    void
-    );
-double
-MPIAPI
-PMPI_Wtime(
-    void
-    );
-
-double
-MPIAPI
-MPI_Wtick(
-    void
-    );
-double
-MPIAPI
-PMPI_Wtick(
-    void
-    );
-
-
-/*---------------------------------------------*/
-/* Section 8.7: Startup                        */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Init(
-    _In_opt_ int* argc,
-    _In_opt_count_(*argc) char*** argv
-    );
-int
-MPIAPI
-PMPI_Init(
-    _In_opt_ int* argc,
-    _In_opt_count_(*argc) char*** argv
-    );
-
-int
-MPIAPI
-MPI_Finalize(
-    void
-    );
-int
-MPIAPI
-PMPI_Finalize(
-    void
-    );
-
-int
-MPIAPI
-MPI_Initialized(
-    _Out_ int* flag
-    );
-int
-MPIAPI
-PMPI_Initialized(
-    _Out_ int* flag
-    );
-
-int
-MPIAPI
-MPI_Abort(
-    MPI_Comm comm,
-    int errorcode
-    );
-int
-MPIAPI
-PMPI_Abort(
-    MPI_Comm comm,
-    int errorcode
-    );
-
-int
-MPIAPI
-MPI_Finalized(
-    _Out_ int* flag
-    );
-int
-MPIAPI
-PMPI_Finalized(
-    _Out_ int* flag
-    );
-
-
-/*---------------------------------------------------------------------------*/
-/* Chapter 9: The Info Object                                                */
-/*---------------------------------------------------------------------------*/
-
-#define MPI_MAX_INFO_KEY    255
-#define MPI_MAX_INFO_VAL   1024
-
-int
-MPIAPI
-MPI_Info_create(
-    _Out_ MPI_Info* info
-    );
-int
-MPIAPI
-PMPI_Info_create(
-    _Out_ MPI_Info* info
-    );
-
-int
-MPIAPI
-MPI_Info_set(
-    MPI_Info info,
-    _In_z_ char* key,
-    _In_z_ char* value
-    );
-int
-MPIAPI
-PMPI_Info_set(
-    MPI_Info info,
-    _In_z_ char* key,
-    _In_z_ char* value
-    );
-
-int
-MPIAPI
-MPI_Info_delete(
-    MPI_Info info,
-    _In_z_ char* key
-    );
-int
-MPIAPI
-PMPI_Info_delete(
-    MPI_Info info,
-    _In_z_ char* key
-    );
-
-int
-MPIAPI
-MPI_Info_get(
-    MPI_Info info,
-    _In_z_ char* key,
-    int valuelen,
-    _Out_z_cap_(valuelen) char* value,
-    _Out_ int* flag
-    );
-int
-MPIAPI
-PMPI_Info_get(
-    MPI_Info info,
-    _In_z_ char* key,
-    int valuelen,
-    _Out_z_cap_(valuelen) char* value,
-    _Out_ int* flag
-    );
-
-int
-MPIAPI
-MPI_Info_get_valuelen(
-    MPI_Info info,
-    _In_z_ char* key,
-    _Out_ int* valuelen,
-    _Out_ int* flag
-    );
-int
-MPIAPI
-PMPI_Info_get_valuelen(
-    MPI_Info info,
-    _In_z_ char* key,
-    _Out_ int* valuelen,
-    _Out_ int* flag
-    );
-
-int
-MPIAPI
-MPI_Info_get_nkeys(
-    MPI_Info info,
-    _Out_ int* nkeys
-    );
-int
-MPIAPI
-PMPI_Info_get_nkeys(
-    MPI_Info info,
-    _Out_ int* nkeys
-    );
-
-int
-MPIAPI
-MPI_Info_get_nthkey(
-    MPI_Info info,
-    int n,
-    _Out_z_cap_(MPI_MAX_INFO_KEY) char* key
-    );
-int
-MPIAPI
-PMPI_Info_get_nthkey(
-    MPI_Info info,
-    int n,
-    _Out_z_cap_(MPI_MAX_INFO_KEY) char* key
-    );
-
-int
-MPIAPI
-MPI_Info_dup(
-    MPI_Info info,
-    _Out_ MPI_Info* newinfo
-    );
-int
-MPIAPI
-PMPI_Info_dup(
-    MPI_Info info,
-    _Out_ MPI_Info* newinfo
-    );
-
-int
-MPIAPI
-MPI_Info_free(
-    _Inout_ MPI_Info* info
-    );
-int
-MPIAPI
-PMPI_Info_free(
-    _Inout_ MPI_Info* info
-    );
-
-
-/*---------------------------------------------------------------------------*/
-/* Chapter 10: Process Creation and Management                               */
-/*---------------------------------------------------------------------------*/
-
-/*---------------------------------------------*/
-/* Section 10.3: Process Manager Interface     */
-/*---------------------------------------------*/
-
-#define MPI_ARGV_NULL ((char**)0)
-#define MPI_ARGVS_NULL ((char***)0)
-
-#define MPI_ERRCODES_IGNORE ((int*)0)
-
-int
-MPIAPI
-MPI_Comm_spawn(
-    _In_z_ char* command,
-    _In_ char* argv[],
-    int maxprocs,
-    MPI_Info info,
-    int root,
-    MPI_Comm comm,
-    _Out_ MPI_Comm* intercomm,
-    _Out_opt_cap_(maxprocs) int array_of_errcodes[]
-    );
-int
-MPIAPI
-PMPI_Comm_spawn(
-    _In_z_ char* command,
-    _In_ char* argv[],
-    int maxprocs,
-    MPI_Info info,
-    int root,
-    MPI_Comm comm,
-    _Out_ MPI_Comm* intercomm,
-    _Out_opt_cap_(maxprocs) int array_of_errcodes[]
-    );
-
-int
-MPIAPI
-MPI_Comm_get_parent(
-    _Out_ MPI_Comm* parent
-    );
-int
-MPIAPI
-PMPI_Comm_get_parent(
-    _Out_ MPI_Comm* parent
-    );
-
-int
-MPIAPI
-MPI_Comm_spawn_multiple(
-    int count,
-    _In_count_(count) char* array_of_commands[],
-    _In_opt_count_(count) char** array_of_argv[],
-    _In_count_(count) int array_of_maxprocs[],
-    _In_count_(count) MPI_Info array_of_info[],
-    int root,
-    MPI_Comm comm,
-    _Out_ MPI_Comm* intercomm,
-    _Out_opt_ int array_of_errcodes[]
-    );
-int
-MPIAPI
-PMPI_Comm_spawn_multiple(
-    int count,
-    _In_count_(count) char* array_of_commands[],
-    _In_opt_count_(count) char** array_of_argv[],
-    _In_count_(count) int array_of_maxprocs[],
-    _In_count_(count) MPI_Info array_of_info[],
-    int root,
-    MPI_Comm comm,
-    _Out_ MPI_Comm* intercomm,
-    _Out_opt_ int array_of_errcodes[]
-    );
-
-
-/*---------------------------------------------*/
-/* Section 10.4: Establishing Communication    */
-/*---------------------------------------------*/
-
-#define MPI_MAX_PORT_NAME   256
-
-int
-MPIAPI
-MPI_Open_port(
-    MPI_Info info,
-    _Out_cap_(MPI_MAX_PORT_NAME) char* port_name
-    );
-int
-MPIAPI
-PMPI_Open_port(
-    MPI_Info info,
-    _Out_cap_(MPI_MAX_PORT_NAME) char* port_name
-    );
-
-int
-MPIAPI
-MPI_Close_port(
-    _In_z_ char* port_name
-    );
-int
-MPIAPI
-PMPI_Close_port(
-    _In_z_ char* port_name
-    );
-
-int
-MPIAPI
-MPI_Comm_accept(
-    _In_z_ char* port_name,
-    MPI_Info info,
-    int root,
-    MPI_Comm comm,
-    _Out_ MPI_Comm* newcomm
-    );
-int
-MPIAPI
-PMPI_Comm_accept(
-    _In_z_ char* port_name,
-    MPI_Info info,
-    int root,
-    MPI_Comm comm,
-    _Out_ MPI_Comm* newcomm
-    );
-
-int
-MPIAPI
-MPI_Comm_connect(
-    _In_z_ char* port_name,
-    MPI_Info info,
-    int root,
-    MPI_Comm comm,
-    _Out_ MPI_Comm* newcomm
-    );
-int
-MPIAPI
-PMPI_Comm_connect(
-    _In_z_ char* port_name,
-    MPI_Info info,
-    int root,
-    MPI_Comm comm,
-    _Out_ MPI_Comm* newcomm
-    );
-
-
-/*---------------------------------------------*/
-/* Section 10.4.4: Name Publishing             */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Publish_name(
-    _In_z_ char* service_name,
-    MPI_Info info,
-    _In_z_ char* port_name
-    );
-int
-MPIAPI
-PMPI_Publish_name(
-    _In_z_ char* service_name,
-    MPI_Info info,
-    _In_z_ char* port_name
-    );
-
-int
-MPIAPI
-MPI_Unpublish_name(
-    _In_z_ char* service_name,
-    MPI_Info info,
-    _In_z_ char* port_name
-    );
-int
-MPIAPI
-PMPI_Unpublish_name(
-    _In_z_ char* service_name,
-    MPI_Info info,
-    _In_z_ char* port_name
-    );
-
-int
-MPIAPI
-MPI_Lookup_name(
-    _In_z_ char* service_name,
-    MPI_Info info,
-    _Out_cap_(MPI_MAX_PORT_NAME) char* port_name
-    );
-int
-MPIAPI
-PMPI_Lookup_name(
-    _In_z_ char* service_name,
-    MPI_Info info,
-    _Out_cap_(MPI_MAX_PORT_NAME) char* port_name
-    );
-
-
-/*---------------------------------------------*/
-/* Section 10.5: Other Functionality           */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Comm_disconnect(
-    _In_ MPI_Comm* comm
-    );
-int
-MPIAPI
-PMPI_Comm_disconnect(
-    _In_ MPI_Comm* comm
-    );
-
-int
-MPIAPI
-MPI_Comm_join(
-    int fd,
-    _Out_ MPI_Comm* intercomm
-    );
-int
-MPIAPI
-PMPI_Comm_join(
-    int fd,
-    _Out_ MPI_Comm* intercomm
-    );
-
-
-/*---------------------------------------------------------------------------*/
-/* Chapter 11: One-Sided Communications                                      */
-/*---------------------------------------------------------------------------*/
-
-int
-MPIAPI
-MPI_Win_create(
-    _In_ void* base,
-    MPI_Aint size,
-    int disp_unit,
-    MPI_Info info,
-    MPI_Comm comm,
-    _Out_ MPI_Win* win
-    );
-int
-MPIAPI
-PMPI_Win_create(
-    _In_ void* base,
-    MPI_Aint size,
-    int disp_unit,
-    MPI_Info info,
-    MPI_Comm comm,
-    _Out_ MPI_Win* win
-    );
-
-int
-MPIAPI
-MPI_Win_free(
-    _Inout_ MPI_Win* win
-    );
-int
-MPIAPI
-PMPI_Win_free(
-    _Inout_ MPI_Win* win
-    );
-
-int
-MPIAPI
-MPI_Win_get_group(
-    MPI_Win win,
-    _Out_ MPI_Group* group
-    );
-int
-MPIAPI
-PMPI_Win_get_group(
-    MPI_Win win,
-    _Out_ MPI_Group* group
-    );
-
-int
-MPIAPI
-MPI_Put(
-    _In_ void* origin_addr,
-    int origin_count,
-    MPI_Datatype origin_datatype,
-    int target_rank,
-    MPI_Aint target_disp,
-    int target_count,
-    MPI_Datatype datatype,
-    MPI_Win win
-    );
-int
-MPIAPI
-PMPI_Put(
-    _In_ void* origin_addr,
-    int origin_count,
-    MPI_Datatype origin_datatype,
-    int target_rank,
-    MPI_Aint target_disp,
-    int target_count,
-    MPI_Datatype datatype,
-    MPI_Win win
-    );
-
-int
-MPIAPI
-MPI_Get(
-    _Out_ void* origin_addr,
-    int origin_count,
-    MPI_Datatype origin_datatype,
-    int target_rank,
-    MPI_Aint target_disp,
-    int target_count,
-    MPI_Datatype datatype,
-    MPI_Win win
-    );
-int
-MPIAPI
-PMPI_Get(
-    _Out_ void* origin_addr,
-    int origin_count,
-    MPI_Datatype origin_datatype,
-    int target_rank,
-    MPI_Aint target_disp,
-    int target_count,
-    MPI_Datatype datatype,
-    MPI_Win win
-    );
-
-int
-MPIAPI
-MPI_Accumulate(
-    _In_ void* origin_addr,
-    int origin_count,
-    MPI_Datatype origin_datatype,
-    int target_rank,
-    MPI_Aint target_disp,
-    int target_count,
-    MPI_Datatype datatype,
-    MPI_Op op,
-    MPI_Win win
-    );
-int
-MPIAPI
-PMPI_Accumulate(
-    _In_ void* origin_addr,
-    int origin_count,
-    MPI_Datatype origin_datatype,
-    int target_rank,
-    MPI_Aint target_disp,
-    int target_count,
-    MPI_Datatype datatype,
-    MPI_Op op,
-    MPI_Win win
-    );
-
-/* Asserts for one-sided communication */
-#define MPI_MODE_NOCHECK    1024
-#define MPI_MODE_NOSTORE    2048
-#define MPI_MODE_NOPUT      4096
-#define MPI_MODE_NOPRECEDE  8192
-#define MPI_MODE_NOSUCCEED 16384
-
-int
-MPIAPI
-MPI_Win_fence(
-    int assert,
-    MPI_Win win
-    );
-int
-MPIAPI
-PMPI_Win_fence(
-    int assert,
-    MPI_Win win
-    );
-
-int
-MPIAPI
-MPI_Win_start(
-    MPI_Group group,
-    int assert,
-    MPI_Win win
-    );
-int
-MPIAPI
-PMPI_Win_start(
-    MPI_Group group,
-    int assert,
-    MPI_Win win
-    );
-
-int
-MPIAPI
-MPI_Win_complete(
-    MPI_Win win
-    );
-int
-MPIAPI
-PMPI_Win_complete(
-    MPI_Win win
-    );
-
-int
-MPIAPI
-MPI_Win_post(
-    MPI_Group group,
-    int assert,
-    MPI_Win win
-    );
-int
-MPIAPI
-PMPI_Win_post(
-    MPI_Group group,
-    int assert,
-    MPI_Win win
-    );
-
-int
-MPIAPI
-MPI_Win_wait(
-    MPI_Win win
-    );
-int
-MPIAPI
-PMPI_Win_wait(
-    MPI_Win win
-    );
-
-int
-MPIAPI
-MPI_Win_test(
-    MPI_Win win,
-    _Out_ int* flag
-    );
-int
-MPIAPI
-PMPI_Win_test(
-    MPI_Win win,
-    _Out_ int* flag
-    );
-
-#define MPI_LOCK_EXCLUSIVE  234
-#define MPI_LOCK_SHARED     235
-
-int
-MPIAPI
-MPI_Win_lock(
-    int lock_type,
-    int rank,
-    int assert,
-    MPI_Win win
-    );
-int
-MPIAPI
-PMPI_Win_lock(
-    int lock_type,
-    int rank,
-    int assert,
-    MPI_Win win
-    );
-
-int
-MPIAPI
-MPI_Win_unlock(
-    int rank,
-    MPI_Win win
-    );
-int
-MPIAPI
-PMPI_Win_unlock(
-    int rank,
-    MPI_Win win
-    );
-
-
-/*---------------------------------------------------------------------------*/
-/* Chapter 12: External Interfaces                                           */
-/*---------------------------------------------------------------------------*/
-
-/*---------------------------------------------*/
-/* Section 12.2: Generalized Requests          */
-/*---------------------------------------------*/
-
-typedef
-int
-(MPIAPI MPI_Grequest_query_function)(
-    _In_opt_ void* extra_state,
-    _Out_ MPI_Status* status
-    );
-
-typedef
-int
-(MPIAPI MPI_Grequest_free_function)(
-    _In_opt_ void* extra_state
-    );
-
-typedef
-int
-(MPIAPI MPI_Grequest_cancel_function)(
-    _In_opt_ void* extra_state,
-    int complete
-    );
-
-int
-MPIAPI
-MPI_Grequest_start(
-    _In_ MPI_Grequest_query_function* query_fn,
-    _In_ MPI_Grequest_free_function* free_fn,
-    _In_ MPI_Grequest_cancel_function* cancel_fn,
-    _In_opt_ void* extra_state,
-    _Out_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_Grequest_start(
-    _In_ MPI_Grequest_query_function* query_fn,
-    _In_ MPI_Grequest_free_function* free_fn,
-    _In_ MPI_Grequest_cancel_function* cancel_fn,
-    _In_opt_ void* extra_state,
-    _Out_ MPI_Request* request
-    );
-
-int
-MPIAPI
-MPI_Grequest_complete(
-    MPI_Request request
-    );
-int
-MPIAPI
-PMPI_Grequest_complete(
-    MPI_Request request
-    );
-
-
-/*---------------------------------------------*/
-/* Section 12.3: Information with Status       */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Status_set_elements(
-    _In_ MPI_Status* status,
-    MPI_Datatype datatype,
-    int count
-    );
-int
-MPIAPI
-PMPI_Status_set_elements(
-    _In_ MPI_Status* status,
-    MPI_Datatype datatype,
-    int count
-    );
-
-int
-MPIAPI
-MPI_Status_set_cancelled(
-    _In_ MPI_Status* status,
-    int flag
-    );
-int
-MPIAPI
-PMPI_Status_set_cancelled(
-    _In_ MPI_Status* status,
-    int flag
-    );
-
-
-/*---------------------------------------------*/
-/* Section 12.4: Threads                       */
-/*---------------------------------------------*/
-
-#define MPI_THREAD_SINGLE       0
-#define MPI_THREAD_FUNNELED     1
-#define MPI_THREAD_SERIALIZED   2
-#define MPI_THREAD_MULTIPLE     3
-
-int
-MPIAPI
-MPI_Init_thread(
-    _In_opt_ int* argc,
-    _In_opt_count_(*argc) char*** argv,
-    int required,
-    _Out_ int* provided
-    );
-int
-MPIAPI
-PMPI_Init_thread(
-    _In_opt_ int* argc,
-    _In_opt_count_(*argc) char*** argv,
-    int required,
-    _Out_ int* provided
-    );
-
-int
-MPIAPI
-MPI_Query_thread(
-    _Out_ int* provided
-    );
-int
-MPIAPI
-PMPI_Query_thread(
-    _Out_ int* provided
-    );
-
-int
-MPIAPI
-MPI_Is_thread_main(
-    _Out_ int* flag
-    );
-int
-MPIAPI
-PMPI_Is_thread_main(
-    _Out_ int* flag
-    );
-
-
-/*---------------------------------------------------------------------------*/
-/* Chapter 13: I/O                                                           */
-/*---------------------------------------------------------------------------*/
-
-/*---------------------------------------------*/
-/* Section 13.2: File Manipulation             */
-/*---------------------------------------------*/
-
-#define MPI_MODE_CREATE             0x00000001
-#define MPI_MODE_RDONLY             0x00000002
-#define MPI_MODE_WRONLY             0x00000004
-#define MPI_MODE_RDWR               0x00000008
-#define MPI_MODE_DELETE_ON_CLOSE    0x00000010
-#define MPI_MODE_UNIQUE_OPEN        0x00000020
-#define MPI_MODE_EXCL               0x00000040
-#define MPI_MODE_APPEND             0x00000080
-#define MPI_MODE_SEQUENTIAL         0x00000100
-#define MSMPI_MODE_HIDDEN           0x00000200
-
-int
-MPIAPI
-MPI_File_open(
-    MPI_Comm comm,
-    _In_z_ char* filename,
-    int amode,
-    MPI_Info info,
-    _Out_ MPI_File* newfile
-    );
-int
-MPIAPI
-PMPI_File_open(
-    MPI_Comm comm,
-    _In_z_ char* filename,
-    int amode,
-    MPI_Info info,
-    _Out_ MPI_File* newfile
-    );
-
-int
-MPIAPI
-MPI_File_close(
-    _In_ MPI_File* file
-    );
-int
-MPIAPI
-PMPI_File_close(
-    _In_ MPI_File* file
-    );
-
-int
-MPIAPI
-MPI_File_delete(
-    _In_z_ char* filename,
-    MPI_Info info
-    );
-int
-MPIAPI
-PMPI_File_delete(
-    _In_z_ char* filename,
-    MPI_Info info
-    );
-
-int
-MPIAPI
-MPI_File_set_size(
-    MPI_File file,
-    MPI_Offset size
-    );
-int
-MPIAPI
-PMPI_File_set_size(
-    MPI_File file,
-    MPI_Offset size
-    );
-
-int
-MPIAPI
-MPI_File_preallocate(
-    MPI_File file,
-    MPI_Offset size
-    );
-int
-MPIAPI
-PMPI_File_preallocate(
-    MPI_File file,
-    MPI_Offset size
-    );
-
-int
-MPIAPI
-MPI_File_get_size(
-    MPI_File file,
-    _Out_ MPI_Offset* size
-    );
-int
-MPIAPI
-PMPI_File_get_size(
-    MPI_File file,
-    _Out_ MPI_Offset* size
-    );
-
-int
-MPIAPI
-MPI_File_get_group(
-    MPI_File file,
-    _Out_ MPI_Group* group
-    );
-int
-MPIAPI
-PMPI_File_get_group(
-    MPI_File file,
-    _Out_ MPI_Group* group
-    );
-
-int
-MPIAPI
-MPI_File_get_amode(
-    MPI_File file,
-    _Out_ int* amode
-    );
-int
-MPIAPI
-PMPI_File_get_amode(
-    MPI_File file,
-    _Out_ int* amode
-    );
-
-int
-MPIAPI
-MPI_File_set_info(
-    MPI_File file,
-    MPI_Info info
-    );
-int
-MPIAPI
-PMPI_File_set_info(
-    MPI_File file,
-    MPI_Info info
-    );
-
-int
-MPIAPI
-MPI_File_get_info(
-    MPI_File file,
-    _Out_ MPI_Info* info
-    );
-int
-MPIAPI
-PMPI_File_get_info(
-    MPI_File file,
-    _Out_ MPI_Info* info
-    );
-
-
-/*---------------------------------------------*/
-/* Section 13.3: File Views                    */
-/*---------------------------------------------*/
-
-#define MPI_DISPLACEMENT_CURRENT (-54278278)
-
-int
-MPIAPI
-MPI_File_set_view(
-    MPI_File file,
-    MPI_Offset disp,
-    MPI_Datatype etype,
-    MPI_Datatype filetype,
-    _In_z_ char* datarep,
-    MPI_Info info
-    );
-int
-MPIAPI
-PMPI_File_set_view(
-    MPI_File file,
-    MPI_Offset disp,
-    MPI_Datatype etype,
-    MPI_Datatype filetype,
-    _In_z_ char* datarep,
-    MPI_Info info
-    );
-
-#define MPI_MAX_DATAREP_STRING  128
-
-int
-MPIAPI
-MPI_File_get_view(
-    MPI_File file,
-    _Out_ MPI_Offset* disp,
-    _Out_ MPI_Datatype* etype,
-    _Out_ MPI_Datatype* filetype,
-    _Out_z_cap_(MPI_MAX_DATAREP_STRING) char* datarep
-    );
-int
-MPIAPI
-PMPI_File_get_view(
-    MPI_File file,
-    _Out_ MPI_Offset* disp,
-    _Out_ MPI_Datatype* etype,
-    _Out_ MPI_Datatype* filetype,
-    _Out_z_cap_(MPI_MAX_DATAREP_STRING) char* datarep
-    );
-
-
-/*---------------------------------------------*/
-/* Section 13.4: Data Access                   */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_File_read_at(
-    MPI_File file,
-    MPI_Offset offset,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_File_read_at(
-    MPI_File file,
-    MPI_Offset offset,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_File_read_at_all(
-    MPI_File file,
-    MPI_Offset offset,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_File_read_at_all(
-    MPI_File file,
-    MPI_Offset offset,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_File_write_at(
-    MPI_File file,
-    MPI_Offset offset,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_File_write_at(
-    MPI_File file,
-    MPI_Offset offset,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_File_write_at_all(
-    MPI_File file,
-    MPI_Offset offset,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_File_write_at_all(
-    MPI_File file,
-    MPI_Offset offset,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_File_iread_at(
-    MPI_File file,
-    MPI_Offset offset,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_File_iread_at(
-    MPI_File file,
-    MPI_Offset offset,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Request* request
-    );
-
-int
-MPIAPI
-MPI_File_iwrite_at(
-    MPI_File file,
-    MPI_Offset offset,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_File_iwrite_at(
-    MPI_File file,
-    MPI_Offset offset,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Request* request
-    );
-
-int
-MPIAPI
-MPI_File_read(
-    MPI_File file,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_File_read(
-    MPI_File file,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_File_read_all(
-    MPI_File file,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_File_read_all(
-    MPI_File file,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_File_write(
-    MPI_File file,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_File_write(
-    MPI_File file,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_File_write_all(
-    MPI_File file,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_File_write_all(
-    MPI_File file,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-
-
-int
-MPIAPI
-MPI_File_iread(
-    MPI_File file,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_File_iread(
-    _In_ MPI_File file,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Request* request
-    );
-
-int
-MPIAPI
-MPI_File_iwrite(
-    MPI_File file,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_File_iwrite(
-    MPI_File file,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Request* request
-    );
-
-
-/* File seek whence */
-#define MPI_SEEK_SET    600
-#define MPI_SEEK_CUR    602
-#define MPI_SEEK_END    604
-
-int
-MPIAPI
-MPI_File_seek(
-    MPI_File file,
-    MPI_Offset offset,
-    int whence
-    );
-int
-MPIAPI
-PMPI_File_seek(
-    MPI_File file,
-    MPI_Offset offset,
-    int whence
-    );
-
-int
-MPIAPI
-MPI_File_get_position(
-    MPI_File file,
-    _Out_ MPI_Offset* offset
-    );
-int
-MPIAPI
-PMPI_File_get_position(
-    MPI_File file,
-    _Out_ MPI_Offset* offset
-    );
-
-int
-MPIAPI
-MPI_File_get_byte_offset(
-    MPI_File file,
-    MPI_Offset offset,
-    _Out_ MPI_Offset* disp
-    );
-int
-MPIAPI
-PMPI_File_get_byte_offset(
-    MPI_File file,
-    MPI_Offset offset,
-    _Out_ MPI_Offset* disp
-    );
-
-int
-MPIAPI
-MPI_File_read_shared(
-    MPI_File file,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-     );
-int
-MPIAPI
-PMPI_File_read_shared(
-    MPI_File file,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-     );
-
-int
-MPIAPI
-MPI_File_write_shared(
-    MPI_File file,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_File_write_shared(
-    MPI_File file,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_File_iread_shared(
-    MPI_File file,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_File_iread_shared(
-    MPI_File file,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Request* request
-    );
-
-int
-MPIAPI
-MPI_File_iwrite_shared(
-    MPI_File file,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Request* request
-    );
-int
-MPIAPI
-PMPI_File_iwrite_shared(
-    MPI_File file,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Request* request
-    );
-
-int
-MPIAPI
-MPI_File_read_ordered(
-    MPI_File file,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_File_read_ordered(
-    MPI_File file,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_File_write_ordered(
-    _In_ MPI_File file,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_File_write_ordered(
-    MPI_File file,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_File_seek_shared(
-    MPI_File file,
-    MPI_Offset offset,
-    int whence
-    );
-int
-MPIAPI
-PMPI_File_seek_shared(
-    MPI_File file,
-    MPI_Offset offset,
-    int whence
-    );
-
-int
-MPIAPI
-MPI_File_get_position_shared(
-    MPI_File file,
-    _Out_ MPI_Offset* offset
-    );
-int
-MPIAPI
-PMPI_File_get_position_shared(
-    MPI_File file,
-    _Out_ MPI_Offset* offset
-    );
-
-int
-MPIAPI
-MPI_File_read_at_all_begin(
-    MPI_File file,
-    MPI_Offset offset,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype
-    );
-int
-MPIAPI
-PMPI_File_read_at_all_begin(
-    MPI_File file,
-    MPI_Offset offset,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype
-    );
-
-int
-MPIAPI
-MPI_File_read_at_all_end(
-    MPI_File file,
-    _Out_ void* buf,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_File_read_at_all_end(
-    MPI_File file,
-    _Out_ void* buf,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_File_write_at_all_begin(
-    MPI_File file,
-    MPI_Offset offset,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype
-    );
-int
-MPIAPI
-PMPI_File_write_at_all_begin(
-    MPI_File file,
-    MPI_Offset offset,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype
-    );
-
-int
-MPIAPI
-MPI_File_write_at_all_end(
-    MPI_File file,
-    _In_ void* buf,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_File_write_at_all_end(
-    MPI_File file,
-    _In_ void* buf,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_File_read_all_begin(
-    MPI_File file,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype
-    );
-int
-MPIAPI
-PMPI_File_read_all_begin(
-    MPI_File file,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype
-    );
-
-int
-MPIAPI
-MPI_File_read_all_end(
-    MPI_File file,
-    _Out_ void* buf,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_File_read_all_end(
-    MPI_File file,
-    _Out_ void* buf,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_File_write_all_begin(
-    MPI_File file,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype
-    );
-int
-MPIAPI
-PMPI_File_write_all_begin(
-    MPI_File file,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype
-    );
-
-int
-MPIAPI
-MPI_File_write_all_end(
-    MPI_File file,
-    _In_ void* buf,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_File_write_all_end(
-    MPI_File file,
-    _In_ void* buf,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_File_read_ordered_begin(
-    MPI_File file,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype
-    );
-int
-MPIAPI
-PMPI_File_read_ordered_begin(
-    MPI_File file,
-    _Out_ void* buf,
-    int count,
-    MPI_Datatype datatype
-    );
-
-int
-MPIAPI
-MPI_File_read_ordered_end(
-    MPI_File file,
-    _Out_ void* buf,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_File_read_ordered_end(
-    MPI_File file,
-    _Out_ void* buf,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_File_write_ordered_begin(
-    MPI_File file,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype
-    );
-int
-MPIAPI
-PMPI_File_write_ordered_begin(
-    MPI_File file,
-    _In_ void* buf,
-    int count,
-    MPI_Datatype datatype
-    );
-
-int
-MPIAPI
-MPI_File_write_ordered_end(
-    MPI_File file,
-    _In_ void* buf,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_File_write_ordered_end(
-    MPI_File file,
-    _In_ void* buf,
-    _Out_ MPI_Status* status
-    );
-
-
-/*---------------------------------------------*/
-/* Section 13.5: File Interoperability         */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_File_get_type_extent(
-    MPI_File file,
-    MPI_Datatype datatype,
-    _Out_ MPI_Aint* extent
-    );
-int
-MPIAPI
-PMPI_File_get_type_extent(
-    MPI_File file,
-    MPI_Datatype datatype,
-    _Out_ MPI_Aint* extent
-    );
-
-
-typedef
-int
-(MPIAPI MPI_Datarep_conversion_function)(
-    _Inout_ void* userbuf,
-    MPI_Datatype datatype,
-    int count,
-    _Inout_ void* filebuf,
-    MPI_Offset position,
-    _In_ void* extra_state
-    );
-
-typedef
-int
-(MPIAPI MPI_Datarep_extent_function)(
-    MPI_Datatype datatype,
-    _Out_ MPI_Aint* file_extent,
-    _In_ void* extra_state
-    );
-
-#define MPI_CONVERSION_FN_NULL ((MPI_Datarep_conversion_function*)0)
-
-int
-MPIAPI
-MPI_Register_datarep(
-    _In_z_ char* datarep,
-    _In_opt_ MPI_Datarep_conversion_function* read_conversion_fn,
-    _In_opt_ MPI_Datarep_conversion_function* write_conversion_fn,
-    _In_ MPI_Datarep_extent_function* dtype_file_extent_fn,
-    _In_opt_ void* extra_state
-    );
-int
-MPIAPI
-PMPI_Register_datarep(
-    _In_z_ char* datarep,
-    _In_opt_ MPI_Datarep_conversion_function* read_conversion_fn,
-    _In_opt_ MPI_Datarep_conversion_function* write_conversion_fn,
-    _In_ MPI_Datarep_extent_function* dtype_file_extent_fn,
-    _In_opt_ void* extra_state
-    );
-
-
-/*---------------------------------------------*/
-/* Section 13.6: Consistency and Semantics     */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_File_set_atomicity(
-    MPI_File file,
-    int flag
-    );
-int
-MPIAPI
-PMPI_File_set_atomicity(
-    MPI_File file,
-    int flag
-    );
-
-int
-MPIAPI
-MPI_File_get_atomicity(
-    MPI_File file,
-    _Out_ int* flag
-    );
-int
-MPIAPI
-PMPI_File_get_atomicity(
-    MPI_File file,
-    _Out_ int* flag
-    );
-
-int
-MPIAPI
-MPI_File_sync(
-    MPI_File file
-    );
-int
-MPIAPI
-PMPI_File_sync(
-    MPI_File file
-    );
-
-
-/*---------------------------------------------------------------------------*/
-/* Chapter 14: Profiling Interface                                           */
-/*---------------------------------------------------------------------------*/
-
-int
-MPIAPI
-MPI_Pcontrol(
-    const int level,
-    ...);
-int
-MPIAPI
-PMPI_Pcontrol(
-    const int level,
-    ...);
-
-
-/*---------------------------------------------------------------------------*/
-/* Chapter 15: Depricated Functions                                          */
-/*---------------------------------------------------------------------------*/
-
-#ifdef MSMPI_NO_DEPRECATE_20
-#define MSMPI_DEPRECATE_20( x )
-#else
-#define MSMPI_DEPRECATE_20( x ) __declspec(deprecated( \
-    "Deprecated in MPI 2.0, use '" #x "'.  " \
-    "To disable deprecation, define MSMPI_NO_DEPRECATE_20." ))
-#endif
-
-MSMPI_DEPRECATE_20( MPI_Type_create_hvector )
-int
-MPIAPI
-MPI_Type_hvector(
-    int count,
-    int blocklength,
-    MPI_Aint stride,
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-MSMPI_DEPRECATE_20( PMPI_Type_create_hvector )
-int
-MPIAPI
-PMPI_Type_hvector(
-    int count,
-    int blocklength,
-    MPI_Aint stride,
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-
-MSMPI_DEPRECATE_20( MPI_Type_create_hindexed )
-int
-MPIAPI
-MPI_Type_hindexed(
-    int count,
-    _In_count_(count) int array_of_blocklengths[],
-    _In_count_(count) MPI_Aint array_of_displacements[],
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-MSMPI_DEPRECATE_20( PMPI_Type_create_hindexed )
-int
-MPIAPI
-PMPI_Type_hindexed(
-    int count,
-    _In_count_(count) int array_of_blocklengths[],
-    _In_count_(count) MPI_Aint array_of_displacements[],
-    MPI_Datatype oldtype,
-    _Out_ MPI_Datatype* newtype
-    );
-
-MSMPI_DEPRECATE_20( MPI_Type_create_struct )
-int
-MPIAPI
-MPI_Type_struct(
-    int count,
-    _In_count_(count) int array_of_blocklengths[],
-    _In_count_(count) MPI_Aint array_of_displacements[],
-    _In_count_(count) MPI_Datatype array_of_types[],
-    _In_ MPI_Datatype* newtype
-    );
-MSMPI_DEPRECATE_20( PMPI_Type_create_struct )
-int
-MPIAPI
-PMPI_Type_struct(
-    int count,
-    _In_count_(count) int array_of_blocklengths[],
-    _In_count_(count) MPI_Aint array_of_displacements[],
-    _In_count_(count) MPI_Datatype array_of_types[],
-    _In_ MPI_Datatype* newtype
-    );
-
-MSMPI_DEPRECATE_20( MPI_Get_address )
-int
-MPIAPI
-MPI_Address(
-    _In_ void* location,
-    _Out_ MPI_Aint* address
-    );
-MSMPI_DEPRECATE_20( PMPI_Get_address )
-int
-MPIAPI
-PMPI_Address(
-    _In_ void* location,
-    _Out_ MPI_Aint* address
-    );
-
-MSMPI_DEPRECATE_20( MPI_Type_get_extent )
-int
-MPIAPI
-MPI_Type_extent(
-    MPI_Datatype datatype,
-    _Out_ MPI_Aint* extent
-    );
-MSMPI_DEPRECATE_20( PMPI_Type_get_extent )
-int
-MPIAPI
-PMPI_Type_extent(
-    MPI_Datatype datatype,
-    _Out_ MPI_Aint* extent
-    );
-
-MSMPI_DEPRECATE_20( MPI_Type_get_extent )
-int
-MPIAPI
-MPI_Type_lb(
-    MPI_Datatype datatype,
-    _Out_ MPI_Aint* displacement
-    );
-MSMPI_DEPRECATE_20( PMPI_Type_get_extent )
-int
-MPIAPI
-PMPI_Type_lb(
-    MPI_Datatype datatype,
-    _Out_ MPI_Aint* displacement
-    );
-
-MSMPI_DEPRECATE_20( MPI_Type_get_extent )
-int
-MPIAPI
-MPI_Type_ub(
-    MPI_Datatype datatype,
-    _Out_ MPI_Aint* displacement
-    );
-MSMPI_DEPRECATE_20( PMPI_Type_get_extent )
-int
-MPIAPI
-PMPI_Type_ub(
-    MPI_Datatype datatype,
-    _Out_ MPI_Aint* displacement
-    );
-
-
-typedef MPI_Comm_copy_attr_function MPI_Copy_function;
-typedef MPI_Comm_delete_attr_function MPI_Delete_function;
-
-#define MPI_NULL_COPY_FN ((MPI_Copy_function*)0)
-#define MPI_NULL_DELETE_FN ((MPI_Delete_function*)0)
-#define MPI_DUP_FN MPIR_Dup_fn
-
-
-MSMPI_DEPRECATE_20( MPI_Comm_create_keyval )
-int
-MPIAPI
-MPI_Keyval_create(
-    _In_ MPI_Copy_function* copy_fn,
-    _In_ MPI_Delete_function* delete_fn,
-    _Out_ int* keyval,
-    _In_opt_ void* extra_state
-    );
-MSMPI_DEPRECATE_20( PMPI_Comm_create_keyval )
-int
-MPIAPI
-PMPI_Keyval_create(
-    _In_ MPI_Copy_function* copy_fn,
-    _In_ MPI_Delete_function* delete_fn,
-    _Out_ int* keyval,
-    _In_opt_ void* extra_state
-    );
-
-MSMPI_DEPRECATE_20( MPI_Comm_free_keyval )
-int
-MPIAPI
-MPI_Keyval_free(
-    _Inout_ int* keyval
-    );
-MSMPI_DEPRECATE_20( PMPI_Comm_free_keyval )
-int
-MPIAPI
-PMPI_Keyval_free(
-    _Inout_ int* keyval
-    );
-
-MSMPI_DEPRECATE_20( MPI_Comm_set_attr )
-int
-MPIAPI
-MPI_Attr_put(
-    MPI_Comm comm,
-    int keyval,
-    _In_ void* attribute_val
-    );
-MSMPI_DEPRECATE_20( PMPI_Comm_set_attr )
-int
-MPIAPI
-PMPI_Attr_put(
-    MPI_Comm comm,
-    int keyval,
-    _In_ void* attribute_val
-    );
-
-MSMPI_DEPRECATE_20( MPI_Comm_get_attr )
-int
-MPIAPI
-MPI_Attr_get(
-    MPI_Comm comm,
-    int keyval,
-    _Out_ void* attribute_val,
-    _Out_ int* flag
-    );
-MSMPI_DEPRECATE_20( PMPI_Comm_get_attr )
-int
-MPIAPI
-PMPI_Attr_get(
-    MPI_Comm comm,
-    int keyval,
-    _Out_ void* attribute_val,
-    _Out_ int* flag
-    );
-
-MSMPI_DEPRECATE_20( MPI_Comm_delete_attr )
-int
-MPIAPI
-MPI_Attr_delete(
-    MPI_Comm comm,
-    int keyval
-    );
-MSMPI_DEPRECATE_20( PMPI_Comm_delete_attr )
-int
-MPIAPI
-PMPI_Attr_delete(
-    MPI_Comm comm,
-    int keyval
-    );
-
-
-typedef MPI_Comm_errhandler_fn MPI_Handler_function;
-
-MSMPI_DEPRECATE_20( MPI_Comm_create_errhandler )
-int
-MPIAPI
-MPI_Errhandler_create(
-    _In_ MPI_Handler_function* function,
-    _Out_ MPI_Errhandler* errhandler
-    );
-MSMPI_DEPRECATE_20( PMPI_Comm_create_errhandler )
-int
-MPIAPI
-PMPI_Errhandler_create(
-    _In_ MPI_Handler_function* function,
-    _Out_ MPI_Errhandler* errhandler
-    );
-
-MSMPI_DEPRECATE_20( MPI_Comm_set_errhandler )
-int
-MPIAPI
-MPI_Errhandler_set(
-    MPI_Comm comm,
-    MPI_Errhandler errhandler
-    );
-MSMPI_DEPRECATE_20( PMPI_Comm_set_errhandler )
-int
-MPIAPI
-PMPI_Errhandler_set(
-    MPI_Comm comm,
-    MPI_Errhandler errhandler
-    );
-
-MSMPI_DEPRECATE_20( MPI_Comm_get_errhandler )
-int
-MPIAPI
-MPI_Errhandler_get(
-    MPI_Comm comm,
-    _Out_ MPI_Errhandler* errhandler
-    );
-MSMPI_DEPRECATE_20( PMPI_Comm_get_errhandler )
-int
-MPIAPI
-PMPI_Errhandler_get(
-    MPI_Comm comm,
-    _Out_ MPI_Errhandler* errhandler
-    );
-
-
-/*---------------------------------------------------------------------------*/
-/* Chapter 16: Language Bindings                                             */
-/*---------------------------------------------------------------------------*/
-
-/*---------------------------------------------*/
-/* Section 16.2: Fortran Support               */
-/*---------------------------------------------*/
-
-int
-MPIAPI
-MPI_Type_create_f90_real(
-    int p,
-    int r,
-    _Out_ MPI_Datatype* newtype
-    );
-int
-MPIAPI
-PMPI_Type_create_f90_real(
-    int p,
-    int r,
-    _Out_ MPI_Datatype* newtype
-    );
-
-int
-MPIAPI
-MPI_Type_create_f90_complex(
-    int p,
-    int r,
-    _Out_ MPI_Datatype* newtype
-    );
-int
-MPIAPI
-PMPI_Type_create_f90_complex(
-    int p,
-    int r,
-    _Out_ MPI_Datatype* newtype
-    );
-
-int
-MPIAPI
-MPI_Type_create_f90_integer(
-    int r,
-    _Out_ MPI_Datatype* newtype
-    );
-int
-MPIAPI
-PMPI_Type_create_f90_integer(
-    int r,
-    _Out_ MPI_Datatype* newtype
-    );
-
-/* typeclasses */
-#define MPI_TYPECLASS_REAL      1
-#define MPI_TYPECLASS_INTEGER   2
-#define MPI_TYPECLASS_COMPLEX   3
-
-int
-MPIAPI
-MPI_Type_match_size(
-    int typeclass,
-    int size,
-    _Out_ MPI_Datatype* type
-    );
-int
-MPIAPI
-PMPI_Type_match_size(
-    int typeclass,
-    int size,
-    _Out_ MPI_Datatype* type
-    );
-
-
-/*---------------------------------------------*/
-/* Section 16.3: Language Interoperability     */
-/*---------------------------------------------*/
-
-#define MPI_Comm_c2f(comm)  (MPI_Fint)(comm)
-#define PMPI_Comm_c2f(comm) (MPI_Fint)(comm)
-
-#define MPI_Comm_f2c(comm)  (MPI_Comm)(comm)
-#define PMPI_Comm_f2c(comm) (MPI_Comm)(comm)
-
-
-#define MPI_Type_f2c(datatype)  (MPI_Datatype)(datatype)
-#define PMPI_Type_f2c(datatype) (MPI_Datatype)(datatype)
-
-#define MPI_Type_c2f(datatype)  (MPI_Fint)(datatype)
-#define PMPI_Type_c2f(datatype) (MPI_Fint)(datatype)
-
-
-#define MPI_Group_f2c(group)  (MPI_Group)(group)
-#define PMPI_Group_f2c(group) (MPI_Group)(group)
-
-#define MPI_Group_c2f(group)  (MPI_Fint)(group)
-#define PMPI_Group_c2f(group) (MPI_Fint)(group)
-
-
-#define MPI_Request_f2c(request)  (MPI_Request)(request)
-#define PMPI_Request_f2c(request) (MPI_Request)(request)
-
-#define MPI_Request_c2f(request)  (MPI_Fint)(request)
-#define PMPI_Request_c2f(request) (MPI_Fint)(request)
-
-
-#define MPI_Win_f2c(win)  (MPI_Win)(win)
-#define PMPI_Win_f2c(win) (MPI_Win)(win)
-
-#define MPI_Win_c2f(win)  (MPI_Fint)(win)
-#define PMPI_Win_c2f(win) (MPI_Fint)(win)
-
-
-#define MPI_Op_c2f(op)  (MPI_Fint)(op)
-#define PMPI_Op_c2f(op) (MPI_Fint)(op)
-
-#define MPI_Op_f2c(op)  (MPI_Op)(op)
-#define PMPI_Op_f2c(op) (MPI_Op)(op)
-
-
-#define MPI_Info_c2f(info)  (MPI_Fint)(info)
-#define PMPI_Info_c2f(info) (MPI_Fint)(info)
-
-#define MPI_Info_f2c(info)  (MPI_Info)(info)
-#define PMPI_Info_f2c(info) (MPI_Info)(info)
-
-
-#define MPI_Errhandler_c2f(errhandler)  (MPI_Fint)(errhandler)
-#define PMPI_Errhandler_c2f(errhandler) (MPI_Fint)(errhandler)
-
-#define MPI_Errhandler_f2c(errhandler)  (MPI_Errhandler)(errhandler)
-#define PMPI_Errhandler_f2c(errhandler) (MPI_Errhandler)(errhandler)
-
-
-MPI_File
-MPIAPI
-MPI_File_f2c(
-    MPI_Fint file
-    );
-MPI_File
-MPIAPI
-PMPI_File_f2c(
-    MPI_Fint file
-    );
-
-MPI_Fint
-MPIAPI
-MPI_File_c2f(
-    MPI_File file
-    );
-MPI_Fint
-MPIAPI
-PMPI_File_c2f(
-    MPI_File file
-    );
-
-int
-MPIAPI
-MPI_Status_f2c(
-    _In_ MPI_Fint* f_status,
-    _Out_ MPI_Status* status
-    );
-int
-MPIAPI
-PMPI_Status_f2c(
-    _In_ MPI_Fint* f_status,
-    _Out_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MPI_Status_c2f(
-    _In_ MPI_Status* status,
-    _Out_ MPI_Fint* f_status
-    );
-int
-MPIAPI
-PMPI_Status_c2f(
-    _In_ MPI_Status* status,
-    _Out_ MPI_Fint* f_status
-    );
-
-
-#if !defined(_MPICH_DLL_)
-#define MPIU_DLL_SPEC __declspec(dllimport)
-#else
-#define MPIU_DLL_SPEC
-#endif
-
-extern MPIU_DLL_SPEC MPI_Fint* MPI_F_STATUS_IGNORE;
-extern MPIU_DLL_SPEC MPI_Fint* MPI_F_STATUSES_IGNORE;
-
-
-/*---------------------------------------------------------------------------*/
-/* Implementation Specific                                                   */
-/*---------------------------------------------------------------------------*/
-
-int
-MPIAPI
-MPIR_Dup_fn(
-    MPI_Comm oldcomm,
-    int keyval,
-    _In_opt_ void* extra_state,
-    _In_ void* attribute_val_in,
-    _Out_ void* attribute_val_out,
-    _Out_ int* flag
-    );
-
-
-#if MSMPI_VER >= 0x300
-
-int
-MPIAPI
-MSMPI_Get_bsend_overhead();
-
-#endif
-
-
-#if MSMPI_VER >= 0x300
-
-int
-MPIAPI
-MSMPI_Get_version();
-
-#else
-#  define MSMPI_Get_version() (MSMPI_VER)
-#endif
-
-typedef void
-(MPIAPI MSMPI_Request_callback)(
-    _In_ MPI_Status* status
-    );
-
-int
-MPIAPI
-MSMPI_Request_set_apc(
-    MPI_Request request,
-    _In_ MSMPI_Request_callback* callback_fn,
-    _In_ MPI_Status* callback_status
-    );
-
-typedef struct _MSMPI_LOCK_QUEUE
-{
-    struct _MSMPI_LOCK_QUEUE* volatile next;
-    volatile MPI_Aint flags;
-
-} MSMPI_Lock_queue;
-
-void
-MPIAPI
-MSMPI_Queuelock_acquire(
-    _Out_ MSMPI_Lock_queue* queue
-    );
-
-void
-MPIAPI
-MSMPI_Queuelock_release(
-    _In_ MSMPI_Lock_queue* queue
-    );
-
-int
-MPIAPI
-MSMPI_Waitsome_interruptible(
-    int incount,
-    _Inout_count_(incount) MPI_Request array_of_requests[],
-    _Out_ int* outcount,
-    _Out_cap_post_count_(incount,*outcount) int array_of_indices[],
-    _Out_cap_post_count_(incount,*outcount) MPI_Status array_of_statuses[]
-    );
-
-
-/*---------------------------------------------------------------------------*/
-/* SAL ANNOTATIONS                                                           */
-/*---------------------------------------------------------------------------*/
-
-//OACR_WARNING_POP
-
-#ifdef MSMPI_DEFINED_SAL
-#undef MSMPI_DEFINED_SAL
-#undef _In_
-#undef _In_z_
-#undef _In_opt_
-#undef _In_count_
-#undef _In_bytecount_
-#undef _In_opt_count_
-#undef _Out_
-#undef _Out_cap_
-#undef _Out_cap_post_count_
-#undef _Out_bytecap_
-#undef _Out_z_cap_
-#undef _Out_z_cap_post_count_
-#undef _Out_cap_post_part_
-#undef _Out_opt_
-#undef _Out_opt_cap_
-#undef _Post_z_
-#undef _Inout_
-#undef _Inout_count_
-#endif
-
-#if defined(__cplusplus)
-}
-#endif
-
-#endif /* MPI_INCLUDED */
diff --git a/Math/Math/CNTKMathCUDA.vcxproj b/Math/Math/CNTKMathCUDA.vcxproj
index 46dd5bf6f..2c4c0666b 100644
--- a/Math/Math/CNTKMathCUDA.vcxproj
+++ b/Math/Math/CNTKMathCUDA.vcxproj
@@ -31,7 +31,6 @@
     <UseDebugLibraries>true</UseDebugLibraries>
     <PlatformToolset>v120</PlatformToolset>
     <CharacterSet>Unicode</CharacterSet>
-    <UseIntelMKL>No</UseIntelMKL>
   </PropertyGroup>
   <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'" Label="Configuration">
     <ConfigurationType>StaticLibrary</ConfigurationType>
@@ -39,7 +38,6 @@
     <PlatformToolset>v120</PlatformToolset>
     <WholeProgramOptimization>true</WholeProgramOptimization>
     <CharacterSet>Unicode</CharacterSet>
-    <UseIntelMKL>No</UseIntelMKL>
   </PropertyGroup>
   <Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
   <ImportGroup Label="ExtensionSettings">
diff --git a/Math/Math/Math.vcxproj b/Math/Math/Math.vcxproj
index 6e537fe5b..33b3c951b 100644
--- a/Math/Math/Math.vcxproj
+++ b/Math/Math/Math.vcxproj
@@ -30,8 +30,7 @@
     <UseDebugLibraries>true</UseDebugLibraries>
     <PlatformToolset>v120</PlatformToolset>
     <CharacterSet>Unicode</CharacterSet>
-    <UseIntelMKL>Parallel</UseIntelMKL>
-    <UseMpiLibrary>INTELMPI</UseMpiLibrary>
+    <UseIntelMKL>No</UseIntelMKL>
   </PropertyGroup>
   <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'" Label="Configuration">
     <ConfigurationType>DynamicLibrary</ConfigurationType>
@@ -39,7 +38,7 @@
     <PlatformToolset>v120</PlatformToolset>
     <WholeProgramOptimization>true</WholeProgramOptimization>
     <CharacterSet>Unicode</CharacterSet>
-    <UseIntelMKL>Parallel</UseIntelMKL>
+    <UseIntelMKL>No</UseIntelMKL>
     <UseIntelIPP>false</UseIntelIPP>
   </PropertyGroup>
   <Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
@@ -76,14 +75,13 @@
       <OpenMPSupport>true</OpenMPSupport>
       <MinimalRebuild>false</MinimalRebuild>
       <TreatWarningAsError>true</TreatWarningAsError>
-      <AdditionalOptions>/D USE_MKL %(AdditionalOptions)</AdditionalOptions>
     </ClCompile>
     <Link>
       <SubSystem>Windows</SubSystem>
       <GenerateDebugInformation>true</GenerateDebugInformation>
-      <AdditionalDependencies>%(AdditionalDependencies)</AdditionalDependencies>
-      <AdditionalLibraryDirectories>$(SolutionDir)$(Platform)\$(Configuration)\; c:\Program Files (x86)\Intel\Composer XE 2015\mkl\lib\intel64</AdditionalLibraryDirectories>
-      <DelayLoadDLLs>cublas64_70.dll; cusparse64_70.dll; curand64_70.dll; cudart64_70.dll;  %(DelayLoadDLLs)</DelayLoadDLLs>
+      <AdditionalDependencies>libacml_mp_dll.lib;%(AdditionalDependencies)</AdditionalDependencies>
+      <AdditionalLibraryDirectories>$(SolutionDir)$(Platform)\$(Configuration)\</AdditionalLibraryDirectories>
+      <DelayLoadDLLs>cublas64_70.dll; cusparse64_70.dll; curand64_70.dll; cudart64_70.dll; libacml_dll.dll; libacml_mp_dll.dll; %(DelayLoadDLLs)</DelayLoadDLLs>
       <Profile>true</Profile>
     </Link>
     <PostBuildEvent>
@@ -123,7 +121,7 @@
       <EnableParallelCodeGeneration>true</EnableParallelCodeGeneration>
       <FloatingPointExceptions>false</FloatingPointExceptions>
       <TreatWarningAsError>true</TreatWarningAsError>
-      <AdditionalOptions>/d2Zi+ /D USE_MKL %(AdditionalOptions)</AdditionalOptions>
+      <AdditionalOptions>/d2Zi+ %(AdditionalOptions)</AdditionalOptions>
       <RuntimeLibrary>MultiThreadedDLL</RuntimeLibrary>
     </ClCompile>
     <Link>
@@ -131,10 +129,10 @@
       <GenerateDebugInformation>true</GenerateDebugInformation>
       <EnableCOMDATFolding>true</EnableCOMDATFolding>
       <OptimizeReferences>true</OptimizeReferences>
-      <AdditionalLibraryDirectories>c:\Program Files (x86)\Intel\Composer XE 2015\mkl\lib\intel64</AdditionalLibraryDirectories>
-      <AdditionalDependencies>%(AdditionalDependencies)</AdditionalDependencies>
+      <AdditionalLibraryDirectories>$(SolutionDir)$(Platform)\$(Configuration)\</AdditionalLibraryDirectories>
+      <AdditionalDependencies>libacml_mp_dll.lib;%(AdditionalDependencies)</AdditionalDependencies>
       <Profile>true</Profile>
-      <DelayLoadDLLs>cublas64_70.dll;cusparse64_70.dll;curand64_70.dll;cudart64_70.dll;nvcuda.dll;%(DelayLoadDLLs)</DelayLoadDLLs>
+      <DelayLoadDLLs>cublas64_70.dll; cusparse64_70.dll; curand64_70.dll; cudart64_70.dll; libacml_dll.dll; libacml_mp_dll.dll; %(DelayLoadDLLs)</DelayLoadDLLs>
     </Link>
     <PostBuildEvent>
       <Command>xcopy /D /I /Y "$(ACML_PATH)\lib\*.dll" $(OutputPath)</Command>
@@ -199,4 +197,4 @@
   </ItemGroup>
   <Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
   <ImportGroup Label="ExtensionTargets" />
-</Project>
+</Project>
\ No newline at end of file

From 1a0ee86854820937d4267bc96ba578c4fa2d398d Mon Sep 17 00:00:00 2001
From: erw <erw@microsoft.com>
Date: Tue, 19 May 2015 14:40:21 -0700
Subject: [PATCH 49/49] Declare ParseSVDConfigFile and SVDConfigFileUsage
 before it can be used.

---
 MachineLearning/CNTK/CNTK.cpp | 58 +++++++++++++++++------------------
 1 file changed, 28 insertions(+), 30 deletions(-)

diff --git a/MachineLearning/CNTK/CNTK.cpp b/MachineLearning/CNTK/CNTK.cpp
index 8c6de8339..a3fc1bbe3 100644
--- a/MachineLearning/CNTK/CNTK.cpp
+++ b/MachineLearning/CNTK/CNTK.cpp
@@ -445,6 +445,34 @@ void DoCreateLabelMap(const ConfigParameters& config)
 //					4)  ParameterName		-- name (regex) of the parameter node we want to perform a SVD decomposition 
 //				
 //////////////////////////////////////////////////////////////////////////
+//////////////////////////////////////////////////////////////////////////
+//  helper function for DoParameterSVD 
+//////////////////////////////////////////////////////////////////////////
+bool ParseSVDConfigFile(wstring fn, map<wstring, float>& config)
+{
+    msra::files::textreader reader(fn);
+    for (; reader;)
+    {
+        wstring line = reader.wgetline(); 
+        vector<wstring> tokens=msra::strfun::split(line, L"\t ");
+        if (tokens.size() != 2)
+            return false;
+        config[tokens[0]] = (float)msra::strfun::todouble(tokens[1]);
+    }
+    return true;
+}
+// a brief on the SVD config file usage 
+void SVDConfigFileUsage()
+{
+    fprintf(stderr, "usage of SVDConfigFile\n"); 
+    fprintf(stderr, "A SVDConfigFile is referred in main config by \"SVDConfig\"\n"); 
+    fprintf(stderr, "Each line in this file specifies a group of Learnable Parameter nodes using regex and the KeepRatio associated with that group\n");
+    fprintf(stderr, "An example: \n"); 
+    fprintf(stderr, "W0         1.0\n"); 
+    fprintf(stderr, "W[1-5]     0.4\n"); 
+    
+
+}
 template<typename ElemType> 
 void  DoParameterSVD(const ConfigParameters& config)
 {
@@ -487,36 +515,6 @@ void  DoParameterSVD(const ConfigParameters& config)
 
 }
 
-//////////////////////////////////////////////////////////////////////////
-//  helper function for DoParameterSVD 
-//////////////////////////////////////////////////////////////////////////
-bool ParseSVDConfigFile(wstring fn, map<wstring, float>& config)
-{
-    msra::files::textreader reader(fn);
-    for (; reader;)
-    {
-        wstring line = reader.wgetline(); 
-        vector<wstring> tokens=msra::strfun::split(line, L"\t ");
-        if (tokens.size() != 2)
-            return false;
-        config[tokens[0]] = (float)msra::strfun::todouble(tokens[1]);
-    }
-    return true;
-}
-
-// a brief on the SVD config file usage 
-void SVDConfigFileUsage()
-{
-    fprintf(stderr, "usage of SVDConfigFile\n"); 
-    fprintf(stderr, "A SVDConfigFile is referred in main config by \"SVDConfig\"\n"); 
-    fprintf(stderr, "Each line in this file specifies a group of Learnable Parameter nodes using regex and the KeepRatio associated with that group\n");
-    fprintf(stderr, "An example: \n"); 
-    fprintf(stderr, "W0         1.0\n"); 
-    fprintf(stderr, "W[1-5]     0.4\n"); 
-    
-
-}
-
 
 ///
 /// for action writeWordAndClassInfo