• Steps to install nvidia container runtime for Docker:
    • Check that nvidia device is visible: lspci -vv | grep -i nvidia
    • Use Additional Drivers Ubuntu application to install the supported nvidia driver. Reboot.
    • Install Docker
    • Add current user to docker group

    • Install the nvidia container runtime

      curl -s -L https://nvidia.github.io/nvidia-container-runtime/gpgkey | \
sudo apt-key add -
distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
curl -s -L https://nvidia.github.io/nvidia-container-runtime/$distribution/nvidia-container-runtime.list | \
sudo tee /etc/apt/sources.list.d/nvidia-container-runtime.list
sudo apt-get update
sudo apt-get install -y nvidia-container-toolkit
sudo nvidia-ctk runtime configure --runtime=docker
  • Alternative steps on Fedora:
    • curl -s -L https://nvidia.github.io/libnvidia-container/centos8/libnvidia-container.repo | sudo tee /etc/yum.repos.d/nvidia-container-toolkit.repo
    • sudo dnf install nvidia-docker2
    • Edit /etc/nvidia-container-runtime/config.toml and disable cgroups:
      • no-cgroups = true
    • sudo nvidia-ctk runtime configure --runtime=docker
  • Verify –gpus option under docker run: 
      $ docker run --help | grep -i gpus
    --gpus gpu-request               GPU devices to add to the container ('all' to pass all GPUs)
  • Restart the docker service: sudo systemctl restart docker
  • Run a Ubuntu container which leverages GPUs: docker run -it --rm --gpus all ubuntu nvidia-smi
  • Listing out GPU devices 
      $ docker run -it --rm --gpus all ubuntu nvidia-smi -L
  GPU 0: Tesla P4 (UUID: GPU-fa974b1d-3c17-ed92-28d0-805c6d089601)

  $ docker run -it --rm --gpus all ubuntu nvidia-smi  --query-gpu=index,name,uuid,serial --format=csv
  index, name, uuid, serial
  0, Tesla P4, GPU-fa974b1d-3c17-ed92-28d0-805c6d089601, 0325017070224