一、apt安装
sudo apt-get install libopenblas-dev
二、手动从source安装
1. 下载OpenBLAS并编译
git clone https://github.com/xianyi/OpenBLAS.git
cd OpenBLAS
make -j8
sudo make PREFIX=/usr/local/OpenBLAS install
2. 修改Caffe配置文件以下几行
# 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. 添加环境变量
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:直接安装在/usr/local 下应该就不需要添加环境变量
4. 编译Caffe
5. 可在环境变量中设置OpenBLAS所使用的CPU线程数
export OPENBLAS_NUM_THREADS=
参考自:wxyblog.com/2015/08/27/openblas-with-caffe-on-ubuntu/
三、测试
用theano测试
1. 安装theano
sudo apt-get install python-numpy python-scipy python-dev python-pip python-nose g++ libopenblas-dev git
sudo pip install Theano
2. 测试脚本
python `python -c "import os, theano; print os.path.dirname(theano.__file__)"`/misc/check_blas.py
在8核i7上的测试结果:
cpu信息:8 Intel(R) Core(TM) i7-4790K CPU @ 4.00GHz
测试结果:Total execution time: 2.58s on CPU (with direct Theano binding to blas).
在intel双核上:
cpu信息:2 Intel(R) Pentium(R) CPU G3240 @ 3.10GHz
测试结果: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./dist-packages/theano/misc/check_blas.py
GPU信息:一颗TitanX
测试结果:Total execution time: 0.05s on GPU.