The following bash script performs all of the previous actions together. First, we install the CUDA driver:

#!/bin/bash

# Install the CUDA driver
curl -O http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-repo-ubuntu1804_10.0.130-1_amd64.deb
dpkg -i cuda-repo-ubuntu1804_10.0.130-1_amd64.deb
apt-key adv --fetch-keys http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub
apt-get -y update && sudo apt-get -y install cuda

We then install Docker CE:

# Install Docker CE
apt-get remove docker docker-engine docker.io containerd runc
apt-get update
apt-get -y install apt-transport-https ca-certificates curl gnupg-agent software-properties-common
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
add-apt-repository "deb [arch=amd64] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable"
apt-get -y update
apt-get -y install docker-ce docker-ce-cli containerd.io

Finally we install the nvidia-docker driver:

# Install nvidia-docker
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
apt-get -y update && sudo apt-get -y install nvidia-container-toolkit
usermod -aG docker $USER
systemctl restart docker

This is included in the repo at https://git/HighPerformanceWithGo/9-gpu-parallelization-in-go/gcp_scripts and can be executed by running:

sudo bash nvidia-cuda-gcp-setup.sh

within the directory.    In the next section, we'll go through an example CUDA program that is executed using Cgo.