Versions Compared

Key

  • This line was added.
  • This line was removed.
  • Formatting was changed.

...

  1. Install Docker 
    In ubuntu:

    Code Block
    sudo apt install -y docker.io
    sudo usermod -aG docker $USER

    In Centos:

    Code Block
    sudo yum-config-manager \
        --add-repo \
        https://download.docker.com/linux/centos/docker-ce.repo
    sudo yum install docker-ce docker-ce-cli containerd.io
    sudo systemctl --now enable docker
    sudo usermod -aG docker $USER


  2. Logout and login again
  3. Install nvidia-container toolkit
    Ubuntu:

    Code Block
    distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
    curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add -
    curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list
    sudo apt-get update && sudo apt-get install -y nvidia-container-toolkit
    sudo systemctl restart docker

    Centos:

    Code Block
    	distribution=$(. /etc/os-release;echo $ID$VERSION_ID) \
       && curl -s -L https://nvidia.github.io/libnvidia-container/$distribution/libnvidia-container.repo | sudo tee /etc/yum.repos.d/nvidia-container-toolkit.repo
    sudo yum clean expire-cache && sudo yum install -y nvidia-docker2
    sudo systemctl restart docker


  4. Run GPU-compatible notebook. For example:

    Code Block
    # might need sudo
    docker run --gpus all -it --rm -v $(realpath ~/notebooks):/tf/notebooks -p 8888:8888 tensorflow/tensorflow:latest-gpu-jupyter