1、安装显卡驱动
到英伟达官网下载对应的显卡驱动并安装
2、下载cuda8.0的deb包
下载地址
https://developer.nvidia.com/cuda-80-ga2-download-archive
安装指南https://developer.download.nvidia.com/compute/cuda/8.0/secure/Prod2/docs/sidebar/CUDA_Quick_Start_Guide.pdf?lA8eVJXIeTzh4z8j5EpvWudlP9GfoauMt2RUNGI2wU-ZQ7EJdSk5FjiXFt_teTE6xPLauRUPk8QEfsHsJ-g1AzPwe4Ho8u4ETGz0ImOl8cEk9Ionfj8sW36yNBMn-PCOKLcXMIGacd_otdCir1jEngA3ZdDooRdFyPU0Od76dpBPhlbh
设置环境变量
gedit ~/.bashrc
最后添加下面两行
export PATH=/usr/local/cuda-8.0/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda-8.0/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
3、下载安装cudnn6.0
tar -xvf cudnn-8.0-linux-x64-v5.1.tgz
cd cuda
sudo cp ./include/cudnn.h /usr/local/cuda-8.0/include
sudo cp -a ./lib64/libcudnn* /usr/local/cuda-8.0/lib64
4、安装tensorflow
pip install tensorflow-gpu==1.3
