xinyu-intel commented on a change in pull request #11049: Add linux and macos MKLDNN Building Instruction URL: https://github.com/apache/incubator-mxnet/pull/11049#discussion_r196632249
########## File path: MKLDNN_README.md ########## @@ -0,0 +1,287 @@ +# Build/Install MXNet with MKL-DNN + +<h2 id="0">Contents</h2> + +* [1. Linux](#1) +* [2. MacOS](#2) +* [3. Windows](#3) +* [4. Verify MXNet with python](#4) +* [5. Enable MKL BLAS](#5) + +<h2 id="1">Linux</h2> + +### Prerequisites + +``` +apt-get update && apt-get install -y build-essential git libopencv-dev curl gcc libopenblas-dev python python-pip python-dev python-opencv graphviz python-scipy python-sklearn +``` + +### Clone MXNet sources + +``` +git clone --recursive https://github.com/apache/incubator-mxnet.git +cd incubator-mxnet +git submodule update --recursive --init +``` + +### Build MXNet with MKL-DNN + +``` +make -j $(nproc) USE_OPENCV=1 USE_MKLDNN=1 USE_BLAS=mkl USE_INTEL_PATH=/opt/intel +``` + +If you don't have full MKL library installed, you can use OpenBLAS by setting `USE_BLAS=openblas`. + +<h2 id="2">MacOS</h2> + +### Prerequisites + +Install the dependencies, required for MXNet, with the following commands: + +- [Homebrew](https://brew.sh/) +- gcc (clang in macOS does not support OpenMP) +- OpenCV (for computer vision operations) + +``` +# Paste this command in Mac terminal to install Homebrew +/usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)" + +# install dependency +brew update +brew install pkg-config +brew install graphviz +brew tap homebrew/core +brew install opencv +brew tap homebrew/versions +brew install gcc49 +brew link gcc49 +``` + +### Enable OpenMP for MacOS + +If you want to enable OpenMP for better performance, you should modify these two files: + +1. Makefile L138: + +``` +ifeq ($(USE_OPENMP), 1) +# ifneq ($(UNAME_S), Darwin) + CFLAGS += -fopenmp +# endif +endif +``` + +2. prepare_mkldnn.sh L96: + +``` +CC=gcc-4.9 CXX=g++-4.9 cmake $MKLDNN_ROOTDIR -DCMAKE_INSTALL_PREFIX=$MKLDNN_INSTALLDIR -B$MKLDNN_BUILDDIR -DARCH_OPT_FLAGS="-mtune=generic" -DWITH_TEST=OFF -DWITH_EXAMPLE=OFF >&2 +``` + +### Build MXNet with MKL-DNN + +``` +make -j $(sysctl -n hw.ncpu) CC=gcc-4.9 CXX=g++-4.9 USE_OPENCV=0 USE_OPENMP=1 USE_MKLDNN=1 USE_BLAS=apple USE_PROFILER=1 +``` + +*Note: Temporarily disable OPENCV.* + +<h2 id="3">Windows</h2> + +We recommend to build and install MXNet yourself using [Microsoft Visual Studio 2015](https://www.visualstudio.com/vs/older-downloads/), or you can also try experimentally the latest [Microsoft Visual Studio 2017](https://www.visualstudio.com/downloads/). + +**Visual Studio 2015** + +To build and install MXNet yourself, you need the following dependencies. Install the required dependencies: + +1. If [Microsoft Visual Studio 2015](https://www.visualstudio.com/vs/older-downloads/) is not already installed, download and install it. You can download and install the free community edition. +2. Download and Install [CMake](https://cmake.org/) if it is not already installed. +3. Download and install [OpenCV](http://sourceforge.net/projects/opencvlibrary/files/opencv-win/3.0.0/opencv-3.0.0.exe/download). +4. Unzip the OpenCV package. +5. Set the environment variable ```OpenCV_DIR``` to point to the ```OpenCV build directory``` (```C:\opencv\build\x64\vc14``` for example). Also, you need to add the OpenCV bin directory (```C:\opencv\build\x64\vc14\bin``` for example) to the ``PATH`` variable. +6. If you have Intel Math Kernel Library (MKL) installed, set ```MKL_ROOT``` to point to ```MKL``` directory that contains the ```include``` and ```lib```. If you want to use MKL blas, you should set ```-DUSE_BLAS=mkl``` when cmake. Typically, you can find the directory in +```C:\Program Files (x86)\IntelSWTools\compilers_and_libraries_2018\windows\mkl```. +7. If you don't have the Intel Math Kernel Library (MKL) installed, download and install [OpenBLAS](http://sourceforge.net/projects/openblas/files/v0.2.14/). Note that you should also download ```mingw64.dll.zip`` along with openBLAS and add them to PATH. +8. Set the environment variable ```OpenBLAS_HOME``` to point to the ```OpenBLAS``` directory that contains the ```include``` and ```lib``` directories. Typically, you can find the directory in ```C:\Program files (x86)\OpenBLAS\```. + +After you have installed all of the required dependencies, build the MXNet source code: + +1. Download the MXNet source code from [GitHub](https://github.com/apache/incubator-mxnet). Don't forget to pull the submodules: +``` +git clone --recursive https://github.com/apache/incubator-mxnet.git +``` + +2. Copy file `3rdparty/mkldnn/config_template.vcxproj` to incubator-mxnet root. + +3. Start a Visual Studio command prompt. + +4. Use [CMake](https://cmake.org/) to create a Visual Studio solution in ```./build``` or some other directory. Make sure to specify the architecture in the +[CMake](https://cmake.org/) command: +``` +mkdir build +cd build +cmake -G "Visual Studio 14 Win64" .. -DUSE_CUDA=0 -DUSE_CUDNN=0 -DUSE_NVRTC=0 -DUSE_OPENCV=1 -DUSE_OPENMP=1 -DUSE_PROFILER=1 -DUSE_BLAS=open -DUSE_LAPACK=1 -DUSE_DIST_KVSTORE=0 -DCUDA_ARCH_NAME=All -DUSE_MKLDNN=1 -DCMAKE_BUILD_TYPE=Release +``` + +5. In Visual Studio, open the solution file,```.sln```, and compile it. +These commands produce a library called ```libmxnet.dll``` in the ```./build/Release/``` or ```./build/Debug``` folder. +Also ```libmkldnn.dll``` with be in the ```./build/3rdparty/mkldnn/src/Release/``` + +6. Make sure that all the dll files used above(such as `libmkldnn.dll`, `libmklml.dll`, `libiomp5.dll`, `libopenblas.dll`, etc) are added to the system PATH. For convinence, you can put all of them to ```\windows\system32```. Or you will come across `Not Found Dependencies` when loading mxnet. + +**Visual Studio 2017** + +To build and install MXNet yourself using [Microsoft Visual Studio 2017](https://www.visualstudio.com/downloads/), you need the following dependencies. Install the required dependencies: + +1. If [Microsoft Visual Studio 2017](https://www.visualstudio.com/downloads/) is not already installed, download and install it. You can download and install the free community edition. +2. Download and install [CMake](https://cmake.org/files/v3.11/cmake-3.11.0-rc4-win64-x64.msi) if it is not already installed. +3. Download and install [OpenCV](https://sourceforge.net/projects/opencvlibrary/files/opencv-win/3.4.1/opencv-3.4.1-vc14_vc15.exe/download). +4. Unzip the OpenCV package. +5. Set the environment variable ```OpenCV_DIR``` to point to the ```OpenCV build directory``` (e.g., ```OpenCV_DIR = C:\utils\opencv\build```). +6. If you don’t have the Intel Math Kernel Library (MKL) installed, download and install [OpenBlas](https://sourceforge.net/projects/openblas/files/v0.2.20/OpenBLAS%200.2.20%20version.zip/download). +7. Set the environment variable ```OpenBLAS_HOME``` to point to the ```OpenBLAS``` directory that contains the ```include``` and ```lib``` directories (e.g., ```OpenBLAS_HOME = C:\utils\OpenBLAS```). + +After you have installed all of the required dependencies, build the MXNet source code: + +1. Start ```cmd``` in windows. + +2. Download the MXNet source code from GitHub by using following command: + +```r +cd C:\ +git clone https://github.com/apache/incubator-mxnet.git --recursive +``` + +3. Copy file `3rdparty/mkldnn/config_template.vcxproj` to incubator-mxnet root. + +4. Follow [this link](https://docs.microsoft.com/en-us/visualstudio/install/modify-visual-studio) to modify ```Individual components```, and check ```VC++ 2017 version 15.4 v14.11 toolset```, and click ```Modify```. + +5. Change the version of the Visual studio 2017 to v14.11 using the following command (by default the VS2017 is installed in the following path): + +```r +"C:\Program Files (x86)\Microsoft Visual Studio\2017\Community\VC\Auxiliary\Build\vcvars64.bat" -vcvars_ver=14.11 +``` + +6. Create a build dir using the following command and go to the directory, for example: + +```r +mkdir C:\build +cd C:\build +``` + +7. CMake the MXNet source code by using following command: + +```r +cmake -G "Visual Studio 15 2017 Win64" .. -T host=x64 -DUSE_CUDA=0 -DUSE_CUDNN=0 -DUSE_NVRTC=0 -DUSE_OPENCV=1 -DUSE_OPENMP=1 -DUSE_PROFILER=1 -DUSE_BLAS=open -DUSE_LAPACK=1 -DUSE_DIST_KVSTORE=0 -DCUDA_ARCH_NAME=All -DUSE_MKLDNN=1 -DCMAKE_BUILD_TYPE=Release +``` + +8. After the CMake successfully completed, compile the the MXNet source code by using following command: + +```r +msbuild mxnet.sln /p:Configuration=Release;Platform=x64 /maxcpucount +``` + +9. Make sure that all the dll files used above(such as `libmkldnn.dll`, `libmklml.dll`, `libiomp5.dll`, `libopenblas.dll`, etc) are added to the system PATH. For convinence, you can put all of them to ```\windows\system32```. Or you will come across `Not Found Dependencies` when loading mxnet. + +<h2 id="4">Verify MXNet with python</h2> + +``` +export PYTHONPATH=~/incubator-mxnet/python +pip install --upgrade pip +pip install --upgrade jupyter graphviz cython pandas bokeh matplotlib opencv-python requests +python -c "import mxnet as mx;print((mx.nd.ones((2, 3))*2).asnumpy());" + +Expected Output: + +[[ 2. 2. 2.] + [ 2. 2. 2.]] +``` + +### Verify whether MKL-DNN works Review comment: Can't you see `<h2 id="4">Verify MXNet with python</h2>` before this title? ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
