OpenCL版Caffe安装教程

我不是女神ヾ 2022-06-06 09:09 213阅读 0赞

**转载请注明来源：[http://blog.csdn.net/greenlight\_74110/article/details/78446339][http_blog.csdn.net_greenlight_74110_article_details_78446339]**

## 安装前的准备 ##

### 添加epel的源： ###

最新的版本可以在[这里][Link 1]找到。

sudo rpm -ivh https://dl.fedoraproject.org/pub/epel/7/x86_64/Packages/e/epel-release-7-11.noarch.rpm

### 安装依赖 ###

sudo yum install opencl-headers gflags-devel glog-devel lmdb-devel python-devel opencv-devel protobuf-devel leveldb-devel snappy-devel hdf5-devel numpy scipy python-scikit-image python-matplotlib

**注：** ubuntu请使用以下操作：

sudo apt-get install libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libhdf5-serial-dev protobuf-compiler
    sudo apt-get install --no-install-recommends libboost-all-dev
    sudo apt-get install libopenblas-dev liblapack-dev libatlas-base-dev
    sudo apt-get install libgflags-dev libgoogle-glog-dev liblmdb-dev

### 下载OpenCL驱动 ###

使用4版本的[驱动][Link 2]，不要使用最新的5版本，可能会出现一些问题。

1.  查询是否已经安装过opencl
    
        $ rpm -qa | grep intel-opencl
        PACKAGE1.x86_64
        PACKAGE2.x86_64
2.  移除已有的版本
    
        $ sudo rpm -e --nodeps PACKAGE1 PACKAGE2
3.  解压下载的zip包，运行以下命令：
    
        $ sudo rpm -Uvh intel-opencl-r4.1-BUILD_ID.x86_64.rpm
        $ sudo rpm -Uvh intel-opencl-devel-r4.1-BUILD_ID.x86_64.rpm
        $ sudo rpm -Uvh intel-opencl-cpu-r4.1-BUILD_ID.x86_64.rpm

对于ubuntu可以使用以下安装方法：

$ mkdir intel-opencl
    $ tar -C intel-opencl -Jxf intel-opencl-r4.1-BUILD_ID.x86_64.tar.xz
    $ tar -C intel-opencl -Jxf intel-opencl-devel-r4.1-BUILD_ID.x86_64.tar.xz
    $ tar -C intel-opencl -Jxf intel-opencl-cpu-r4.1-BUILD_ID.x86_64.tar.xz
    $ sudo cp -R intel-opencl/* / $ sudo ldconfig

对于atom或者3代及3代以下的cpu型号，建议使用[Beignet][]。

### 安装ViennaCL ###

mkdir -p $HOME/code
    cd $HOME/code
    git clone https://github.com/viennacl/viennacl-dev.git
    cd viennacl-dev
    mkdir build && cd build
    cmake -DBUILD_TESTING=OFF -DBUILD_EXAMPLES=OFF -DCMAKE_INSTALL_PREFIX=$HOME/local -DOPENCL_LIBRARY=/opt/intel/opencl/libOpenCL.so ..
    make -j4
    make install
    # 如果你还想用到显卡的话，以下isaac不用安装
    # cd $HOME/code
    # git clone https://github.com/intel/isaac
    # cd isaac
    # mkdir build && cd build
    # cmake -DCMAKE_INSTALL_PREFIX=$HOME/local .. && make -j4
    # make install

### 安装OpenBLAS（或MKL、Atlas） ###

官方推荐的是MKL，英特尔官方的一套针对它家cpu加速的LAS，速度是最快的，但是需要付费，不过学生可以申请非商业用途的教育版。

安装完后记得在命令行内运行：

LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/opt/intel/mkl/lib/intel64_lin/

**在这里不建议使用Atlas，可能会出错。**

我这里安装的是OpenBLAS：

sudo yum install openblas-devel.x86_64

## 安装Caffe ##

cd $HOME/code
    git clone https://github.com/BVLC/caffe
    cd caffe
    git checkout opencl
    mkdir build && cd build
    # export ISAAC_HOME=$HOME/local
    cmake .. -DUSE_GREENTEA=ON -DUSE_CUDA=OFF -DUSE_INTEL_SPATIAL=ON -DBUILD_docs=0 -DUSE_ISAAC=0 -DViennaCL_INCLUDE_DIR=$HOME/local/include -DBLAS=open -DOPENCL_LIBRARIES=/opt/intel/opencl/libOpenCL.so -DOPENCL_INCLUDE_DIRS=/opt/intel/opencl/include -DOpenCV_DIR=path/to/yourOpenCV/build
    make -j6
    export CAFFE_ROOT=$HOME/code/caffe

**说明：**  
1. make -j6后面为你要指定用来编译的cpu核数，不要设置超过你的cpu最大的核数。  
2. DOpenCV\_DIR后面请设置为你的OpenCV安装目录的build目录下。  
3. 如果你使用的MKL，请将DBLAS设置成：-DBLAS=mkl

确保caffe能找到你的OpenCL设备：

#:~/code/clcaffe/build (opencl)$ ./tools/caffe device_query -gpu all
    I0914 10:48:49.130982   890 common.cpp:373] Total devices: 2
    I0914 10:48:49.131080   890 common.cpp:374] CUDA devices: 0
    I0914 10:48:49.131099   890 common.cpp:375] OpenCL devices: 2
    I0914 10:48:49.131101   890 common.cpp:399] Device id:                     0
    I0914 10:48:49.131103   890 common.cpp:401] Device backend:                OpenCL
    I0914 10:48:49.131130   890 common.cpp:403] Backend details:               Intel(R) Corporation: OpenCL 2.0
    I0914 10:48:49.131134   890 common.cpp:405] Device vendor:                 Intel(R) Corporation
    I0914 10:48:49.131155   890 common.cpp:407] Name:                          Intel(R) HD Graphics
    I0914 10:48:49.131157   890 common.cpp:409] Total global memory:           26878951424
    I0914 10:48:49.131160   890 common.cpp:399] Device id:                     1
    I0914 10:48:49.131178   890 common.cpp:401] Device backend:                OpenCL
    I0914 10:48:49.131182   890 common.cpp:403] Backend details:               Intel(R) Corporation: OpenCL 2.0
    I0914 10:48:49.131188   890 common.cpp:405] Device vendor:                 Intel(R) Corporation
    I0914 10:48:49.131192   890 common.cpp:407] Name:                          Intel(R) Core(TM) i5-6600K CPU @ 3.50GHz
    I0914 10:48:49.131283   890 common.cpp:409] Total global memory:           33609175040

运行Alexnet例子来测试caffe是否安装成功：

./tools/caffe time -model ../models/bvlc_alexnet/deploy.prototxt -gpu 0

\-gpu后面的0表示opencl设备的编号。

进一步对caffe的各项功能进行测试：

make runtest -j6

最后对OPENCL功能进行测试：

./build/test/test.testbin --gtest_filter=*OpenCLKernelCompileTest* X

X是OPENCL设备编号。

## 配置PyCaffe ##

先引入环境变量：

export PYTHONPATH=/path/to/caffe/python:$PYTHONPATH

也可以添加到环境中去：

$ sudo gedit /etc/profile
    
    # 添加： export PYTHONPATH=/path/to/caffe/python:$PYTHONPATH
    
    $ source /etc/profile # 使之生效

测试caffe:

Python 2.7.12 (default, Nov 19 2016, 06:48:10) 
    [GCC 5.4.0 20160609] on linux2
    Type "help", "copyright", "credits" or "license" for more information.
    >>> import caffe
    /home/hejunhua/code/clCaffe/python/caffe/pycaffe.py:13: RuntimeWarning: to-Python converter for caffe::LayerParameter already registered; second conversion method ignored.
      from ._caffe import \
    /home/hejunhua/code/clCaffe/python/caffe/pycaffe.py:13: RuntimeWarning: to-Python converter for caffe::SolverParameter already registered; second conversion method ignored.
      from ._caffe import \
    /home/hejunhua/code/clCaffe/python/caffe/pycaffe.py:13: RuntimeWarning: to-Python converter for std::vector<int, std::allocator<int> > already registered; second conversion method ignored.
      from ._caffe import \
    >>> import caffe
    >>>

注：如果出现上述的warning, 不用在意。

[http_blog.csdn.net_greenlight_74110_article_details_78446339]: http://blog.csdn.net/greenlight_74110/article/details/78446339
[Link 1]: https://dl.fedoraproject.org/pub/epel/7/x86_64/Packages/e/
[Link 2]: http://registrationcenter-download.intel.com/akdlm/irc_nas/11396/SRB4.1_linux64.zip
[Beignet]: https://www.freedesktop.org/wiki/Software/Beignet/