| # MKL2017 PLUGIN |
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| MKL2017 is an INTEL released library to accelerate Deep Neural Network (DNN) applications on Intel architecture. |
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| MKL2017_ML is a subset of MKL2017 and only contains DNN acceleration feature, MKL2017 release cycle is longer then MKL2017_ML and MKL2017_ML support latest feature |
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| This README shows the user how to setup and install MKL2017 library with mxnet. |
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| ## Build/Install MXNet with MKL: |
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| 1. Enable USE_MKL2017=1 in make/config.mk |
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| 1.1 By default, MKL_2017_EXPRIEMENTAL=0. If setting MKL_2017_EXPRIEMENTAL=1, MKL buffer will be created and transferred between layers to achiever much higher performance. |
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| 1.2 By default, MKLML_ROOT=/usr/local, MKL2017_ML will be used |
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| 1.2.1 when excute make, Makefile will execute "prepare_mkl.sh" to download the MKL2017_ML library under <MKLML_ROOT> |
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| 1.2.2 manually steps for download MKL2017_ML problem |
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| 1.2.2.1 wget https://github.com/dmlc/web-data/raw/master/mxnet/mklml-release/mklml_lnx_<MKL VERSION>.tgz |
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| 1.2.2.2 tar zxvf mklml_lnx_<MKL VERSION>.tgz |
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| 1.2.2.3 cp -rf mklml_lnx_<MKL VERSION>/* <MKLML_ROOT>/ |
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| 1.2.3 Set LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$MKLML_ROOT/lib |
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| 1.3 If setting USE_BLAS=mkl |
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| 1.3.1 mshadow can also utilize mkl blas function in mklml package |
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| 1.4 MKL version compatibility |
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| 1.3.2.1 If you already have MKL installed and MKLROOT being set in your system, by default, it will not attempt to download the latest mklml package unless you unset MKLROOT. |
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| 2. Run 'make -jX' |
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| 3. Navigate into the python directory |
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| 4. Run 'sudo python setup.py install' |
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