一、apt安裝
sudo apt-get install libopenblas-dev
二、手動從source安裝
1. 下載OpenBLAS並編譯
1 git clone https://github.com/xianyi/OpenBLAS.git 2 cd OpenBLAS 3 make -j8 4 sudo make PREFIX=/usr/local/OpenBLAS install
2. 修改Caffe配置文件以下幾行
# open for OpenBlas BLAS := open # Custom (MKL/ATLAS/OpenBLAS) include and lib directories. # Leave commented to accept the defaults for your choice of BLAS # (which should work)! BLAS_INCLUDE := /usr/local/OpenBLAS/include BLAS_LIB := /usr/local/OpenBLAS/lib
3. 添加環境變量
在 /etc/profile 末尾加上 export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/OpenBLAS/lib/ 然后 sudo source /etc/profile
注：直接安裝在/usr/local 下應該就不需要添加環境變量
4. 編譯Caffe
5. 可在環境變量中設置OpenBLAS所使用的CPU線程數
export OPENBLAS_NUM_THREADS=4
參考自：wxyblog.com/2015/08/27/openblas-with-caffe-on-ubuntu/
三、測試
用theano測試
1. 安裝theano
sudo apt-get install python-numpy python-scipy python-dev python-pip python-nose g++ libopenblas-dev git sudo pip install Theano
2. 測試腳本
python `python -c "import os, theano; print os.path.dirname(theano.__file__)"`/misc/check_blas.py
在8核i7上的測試結果：
cpu信息：8 Intel(R) Core(TM) i7-4790K CPU @ 4.00GHz
測試結果：Total execution time: 2.58s on CPU (with direct Theano binding to blas).
在intel雙核上：
cpu信息：2 Intel(R) Pentium(R) CPU G3240 @ 3.10GHz
測試結果：Total execution time: 25.77s on CPU (with direct Theano binding to blas).
GPU上：
THEANO_FLAGS=floatX=float32,device=gpu python /usr/local/lib/python2.7/dist-packages/theano/misc/check_blas.py
GPU信息：一顆TitanX
測試結果：Total execution time: 0.05s on GPU.