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How to Install NVIDIA Container Toolkit on Ubuntu?

In this tutorial, we will guide you through the process of installing the NVIDIA Container Toolkit on Ubuntu. This toolkit allows you to build and run GPU-accelerated Docker containers, which is crucial for many AI and machine learning applications. Let’s get started!

What is the NVIDIA Container Toolkit?

The NVIDIA Container Toolkit is a set of tools that enables the use of NVIDIA GPUs within containers. It integrates with Docker and other container runtimes to provide GPU-accelerated computing in a containerized environment. This toolkit is essential for developers and researchers who need to leverage GPU power for deep learning, AI, and other computationally intensive tasks.

1. Install NVIDIA GPU Driver

Before installing the NVIDIA GPU driver, you need to install the necessary packages to compile the driver.

Step 1: Install Required Packages

Open a terminal and run the following command to install make and gcc:

sudo apt install -y make gcc

Step 2: Download NVIDIA Driver

Visit the NVIDIA Driver Download page, select your GPU model, and choose “Linux 64-bit” as the operating system. Download the .run file, which will be named something like NVIDIA-Linux-x86_64-XXX.run.

Step 3: Install NVIDIA Driver

Once you have downloaded the driver, navigate to the directory containing the driver package and run the following command to install it:

sudo sh ./NVIDIA-Linux-x86_64-XXX.run

Replace XXX with the version number of the driver you downloaded.

2. Install Docker

Docker is a platform for developing, shipping, and running applications inside containers. Follow these steps to install Docker on your system.

Step 1: Install Docker

Run the following command to download and install Docker:

curl https://get.docker.com | sh

Step 2: Enable Docker Service

Enable and start the Docker service with the following command:

sudo systemctl --now enable docker

Step 3: Add User to Docker Group

To run Docker commands without sudo, add your user to the Docker group:

sudo groupadd docker
sudo usermod -aG docker $USER

Restart the Docker service:

sudo systemctl restart docker

Step 4: Reboot System

Reboot your system to apply the changes:

sudo reboot

3. Install NVIDIA Container Toolkit

With Docker installed, you can now install the NVIDIA Container Toolkit to enable GPU acceleration in Docker containers.

Step 1: Add NVIDIA Package Repositories

Add the NVIDIA package repositories and the GPG key:

curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg
curl -s -L https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list | sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' | sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list

Step 2: Update Package List

Update the package list:

sudo apt-get update

Step 3: Install NVIDIA Container Toolkit

Install the toolkit with the following command:

sudo apt-get install -y nvidia-container-toolkit

Step 4: Configure NVIDIA Runtime

Configure the NVIDIA runtime for Docker:

sudo nvidia-ctk runtime configure --runtime=docker

Step 5: Restart Docker

Restart the Docker service to apply the changes:

sudo systemctl restart docker

Test Docker Container with GPU

To verify that the NVIDIA Container Toolkit is installed correctly and working, run the following command:

docker run --rm --runtime=nvidia --gpus all ubuntu nvidia-smi

This command runs a Docker container using the NVIDIA CUDA image and checks the GPU status using nvidia-smi.

If everything is set up correctly, you should see the details of your NVIDIA GPU.

Congratulations! You have successfully installed the NVIDIA Container Toolkit on Ubuntu. You can now start leveraging the power of NVIDIA GPUs within Docker containers for your AI and machine learning projects.

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