sudo apt-get install libopenblas-dev

 

 

二、手动从source安装

 

1. 下载OpenBLAS并编译

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=4

 

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/python2.7/dist-packages/theano/misc/check_blas.py 

GPU信息：一颗TitanX

测试结果：Total execution time: 0.05s on GPU.