CentOS7 Tensorflow GPU开发环境配置

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sudo yum remove docker \
                  docker-client \
                  docker-client-latest \
                  docker-common \
                  docker-latest \
                  docker-latest-logrotate \
                  docker-logrotate \
                  docker-selinux \
                  docker-engine-selinux \
                  docker-engine 

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sudo yum install -y yum-utils \
  device-mapper-persistent-data \
  lvm2 
sudo yum-config-manager \
    --add-repo \
    https://download.docker.com/linux/centos/docker-ce.repo
sudo yum install docker-ce
sudo systemctl start docker
sudo docker run hello-world

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# Create the docker group.
 sudo groupadd docker
#Add your user to the docker group.
sudo usermod -aG docker $USER
#Log out and log back in so that your group membership is re-evaluated.

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lspci | grep -i nvidia

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uname -m && cat /etc/*release

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gcc --version

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uname -r
sudo yum install kernel-devel-$(uname -r) kernel-headers-$(uname -r)

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# Install repository meta-data
sudo rpm --install cuda-repo-<distro>-<version>.<architecture>.rpm
## Clean Yum repository cache
sudo yum clean expire-cache
## Install CUDA
sudo yum install cuda
export PATH=/usr/local/cuda-10.0/bin${PATH:+:${PATH}}

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# If you have nvidia-docker 1.0 installed: we need to remove it and all existing GPU containers
docker volume ls -q -f driver=nvidia-docker | xargs -r -I{} -n1 docker ps -q -a -f volume={} | xargs -r docker rm -f
sudo yum remove nvidia-docker

# Add the package repositories
distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.repo | \
  sudo tee /etc/yum.repos.d/nvidia-docker.repo

# Install nvidia-docker2 and reload the Docker daemon configuration
sudo yum install -y nvidia-docker2
sudo pkill -SIGHUP dockerd

##  docker GPU
docker run --runtime=nvidia --rm nvidia/cuda nvidia-smi
docker run --runtime=nvidia -it --rm tensorflow/tensorflow:latest-gpu \
   python -c "import tensorflow as tf; tf.enable_eager_execution(); print(tf.reduce_sum(tf.random_normal([1000, 1000])))"