MKL2017 is an INTEL released library to accelerate Deep Neural Network (DNN) applications on Intel architecture.
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
This README shows the user how to setup and install MKL2017 library with mxnet.
Build/Install MXNet with MKL:
Enable USE_MKL2017=1 in make/config.mk
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.
1.2 By default, USE_BLAS=atlas, MKLML_ROOT=/usr/local, MKL2017_ML will be used
1.2.1 when excute make, Makefile will execute "prepare_mkl.sh" to download the MKL2017_ML library under
1.2.2 manually steps for download MKL2017_ML problem
184.108.40.206 wget https://github.com/dmlc/web-data/raw/master/mxnet/mklml-release/mklml_lnx_<MKL VERSION>.tgz 220.127.116.11 tar zxvf mklml_lnx_<MKL VERSION>.tgz 18.104.22.168 cp -rf mklml_lnx_<MKL VERSION>/* <MKLML_ROOT>/
1.2.3 Set LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$MKLML_ROOT/lib
1.3 If setting USE_BLAS=mkl
1.3.1 please navigate here to do a full MKL installation: https://registrationcenter.intel.com/en/forms/?productid=2558&licensetype=2
1.3.2 do not use MKL2017 and MKL2017_ML at the same time
22.214.171.124 Do not execute MKL2017 compilervars.sh or mklvars.sh script before MxNet compilation. Otherwise, MKL2017 may conflict with MKL2017_ML and MxNet may not be compiled.
Run 'make -jX'
Navigate into the python directory
Run 'sudo python setup.py install'