35 строки
1.4 KiB
Plaintext
35 строки
1.4 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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== Preeliminaries ==
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To build the cpu version, you have to install intel mkl blas library first:
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https://software.intel.com/en-us/intel-mkl
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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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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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