Amazon AWS上Tensorflow+GPU+CUDA 8+cuDNN 5+OpenBLAS配置

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//环境：Amazon AWS g2.2xlarge实例，Ubuntu 16.04, python3.5, Nvidia cuda 8, Tensorflow
//安装Python3和Tensorflow方法：
sudo apt-get install -y python3-pip
sudo pip3 install -y tensorflow
sudo pip3 install -y tensorflow-gpu
sudo pip3 install --upgrade \
https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.0.1-cp35-cp35m-linux_x86_64.whl

//安装NVIDIA CUDA Toolkit 8.0
wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/cuda-repo-ubuntu1604_8.0.61-1_amd64.deb
sudo dpkg -i cuda-repo-ubuntu1604_8.0.61-1_amd64.deb
rm -rf cuda-repo-ubuntu1604_8.0.61-1_amd64.deb
sudo apt-get update
sudo apt-get install -y cuda

//安装NVIDIA cuDNN库
https://developer.nvidia.com/rdp/cudnn-download 注册下载 cudnn-8.0-linux-x64-v5.1.tgz
tar -xzvf cudnn-8.0-linux-x64-v5.0-ga.tgz
sudo cp -R cuda/lib64/lib* /usr/local/cuda/lib64/
sudo cp cuda/include/cudnn.h /usr/local/cuda/include

//配置cuda路径
echo 'export CUDA_HOME=/usr/local/cuda
export CUDA_ROOT=/usr/local/cuda
export PATH=$PATH:$CUDA_ROOT/bin
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$CUDA_ROOT/lib64' >> ~/.bashrc

//配置OpenBLAS
git clone https://github.com/xianyi/OpenBLAS.git
cd OpenBLAS
sudo apt-get install -y gfortran
make FC=gfortran -j $(($(nproc) + 1))
sudo make PREFIX=/usr/local install
echo 'export LD_LIBRARY_PATH=/usr/local/lib:$LD_LIBRARY_PATH' >> ~/.bashrc

//验证安装正确：
python3
>>> import tensorflow as tf
>>> hello = tf.constant('Hello, TensorFlow!')
>>> sess = tf.Session()
>>> print(sess.run(hello))

//执行效果如图：

参考：
1. https://www.tensorflow.org/install/install_linux#InstallingNativePip
2. http://ramhiser.com/2016/01/05/installing-tensorflow-on-an-aws-ec2-instance-with-gpu-support/
3. http://blog.csdn.net/langb2014/article/details/51579491

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