45 строки
1.8 KiB
Plaintext
45 строки
1.8 KiB
Plaintext
== Author of the README ==
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Wengong Jin,
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Shanghai Jiao Tong University
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email: acmgokun@gmail.com
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Hakan Erdogan
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MERL, Sabanci University
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email: haerdogan@sabanciuniv.edu
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== Preeliminaries ==
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To build the cpu version, you have to install intel MKL blas library or ACML library first. Note that ACML is free, where MKL may not be.
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for MKL:
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1. Download from https://software.intel.com/en-us/intel-mkl
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2. You can modify variable MKL_PATH in makefile.cpu to change your mkl path.
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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.
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for ACML:
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1. Download from http://developer.amd.com/tools-and-sdks/cpu-development/amd-core-math-library-acml/
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2. Modify ACML_PATH in the makefile.cpu and makefile.gpu to provide your ACML library path.
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You need to add ${ACML_PATH}/lib to your ${LD_LIBRARY_PATH}.
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To build the gpu version, you have to install NIVIDIA CUDA first
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You can modify the path CUDA_PATH in makefile.cpu to change your cuda path
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We use cuda-6.5 as default.
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Then add ${CUDA_PATH}/lib, ${CUDA_PATH}/lib64 to your ${LD_LIBRARY_PATH} to make sure the program links to the library correctly.
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== Build ==
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To build the cpu version, run
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make -f Makefile.cpu
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To build the gpu version, run
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make -f Makefile.gpu
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To clean the compile, just run
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make -f Makefile.cpu clean
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or
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make -f Makefile.gpu clean
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== Run ==
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All executables are in bin/ directory:
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cn.exe: The main executable for CNTK
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*.so: shared library for corresponding reader, these readers will be linked and loaded dynamically at runtime.
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To run the executable, make sure bin/ is in your ${LD_LIBRARY_PATH}, if not, running cn.exe will fail when cn.exe tries to link the corresponding reader. Once it's done, run in command line:
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./cn.exe configFile=${your config file}
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