Editing Tutorials:Install the nVidia docker system (section)

== Installing the nVidia docker extension ==

The default docker installation is not able to talk to the nVidia GPUs present in your system. Thus, you have to install an extension by nVidia which allows it to do so.
Run the following script:

<syntaxhighlight lang="bash">
#!/bin/bash
curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | \
  sudo apt-key add -

# hard-coded distro ID so that it also works on Ubuntu flavors like Mint
# ubuntu16.04 is also available, maybe some other versions (see above github)
distribution=ubuntu18.04

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

# Install nvidia-docker2 and reload the Docker daemon configuration
sudo apt-get install -y nvidia-docker2
sudo systemctl restart docker
</syntaxhighlight>


That's it, your system is now configured to run nVidia's base containers for GPU utilization.
To test it and actually run your first container, try out:

<syntaxhighlight lang="bash">
docker run --runtime=nvidia nvidia/cuda:9.0-devel nvcc --version
</syntaxhighlight>

This will pull the docker container with CUDA 9.0 and run the command "nvcc --version" inside it. In effect, you should see a similar output as on your own system, but with a different version of CUDA displayed. You can also try to run nvidia-smi inside the container:

<syntaxhighlight lang="bash">
docker run --runtime=nvidia nvidia/cuda:9.0-devel nvidia-smi
</syntaxhighlight>

This should show a similar output as when you run it directly, i.e. show the same graphics card(s).