== Author of the README ==
	Wengong Jin,
	Shanghai Jiao Tong University
	email: acmgokun@gmail.com

== Preeliminaries ==
To build the cpu version, you have to install intel mkl blas library first:
	https://software.intel.com/en-us/intel-mkl
You can modify variable MKL_PATH in makefile.cpu to change your mkl path.
Then add ${MKL_PATH}/mkl/lib/intel64, ${MKL_PATH}/mkl/lib/mic, ${MKL_PATH}/compiler/lib/intel64. ${MKL_PATH}/compiler/lib/mic to your ${LD_LIBRARY_PATH} to make sure the program links the library correctly.

To build the gpu version, you have to install NIVIDIA CUDA first
You can modify the path CUDA_PATH in makefile.cpu to change your cuda path
We use cuda-6.5 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.


== Build ==
To build the cpu version, run
	make -f Makefile.cpu 
To build the gpu version, run
	make -f Makefile.gpu
To clean the compile, just run
	make -f Makefile.cpu clean
or
	make -f Makefile.gpu clean

== Run ==
All executables are in bin/ directory:
	cn.exe: The main executable for CNTK
	*.so: shared library for corresponding reader, these readers will be linked and loaded dynamically at runtime.

To run the executable, make sure bin/ is in your ${LD_LIBRARY_PATH}, if not, running cn.exe will fail when cn.exe tries to link the corresponding reader. Once it's done, run in command line:
	./cn.exe configFile=${your config file}