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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 --env NVIDIA_DISABLE_REQUIRE=1 -it --rm -v $(realpath ~/notebooks):/tf/notebooks -p 8888:8888 tensorflow/tensorflow:latest-gpu-jupyter