Installing Docker CE on Linux Mint 21
If you’re interested in developing applications in a containerized environment, Docker is an excellent choice. Docker is a tool that allows developers to create, deploy, and run applications as containers.
With Docker, applications can be easily moved between development, testing, and production environments. In this article, we will guide you on installing Docker CE on Linux Mint 21.
We’ll cover everything from checking for NVIDIA GPU and drivers to checking if Docker CE is installed correctly.
Checking for NVIDIA GPU and drivers
Before installing Docker CE, it’s important to check if your system has an NVIDIA GPU and if the official NVIDIA drivers are installed. If you’re planning to use the NVIDIA Container Toolkit, this step is crucial.
To check for an NVIDIA GPU, run the following command in the terminal:
“`
lspci | grep -i nvidia
“`
If the command outputs information about your NVIDIA GPU, you have an NVIDIA GPU installed on your system. To check if the official NVIDIA drivers are installed, run the following command in the terminal:
“`
nvidia-smi
“`
If the command outputs information about your NVIDIA GPU and driver version, the official NVIDIA drivers are installed on your system.
Installing Docker CE dependencies
Docker CE has a few dependency packages that need to be installed before you can successfully install Docker. These dependencies can be easily installed using the APT package repository.
To install the dependencies, run the following command in the terminal:
“`
sudo apt-get update
sudo apt-get install apt-transport-https ca-certificates curl gnupg-agent software-properties-common
“`
Installing Docker CE GPG keys
Before you can install Docker CE, you need to add the Docker GPG keys to your system. GPG keys are used to verify the authenticity of software packages that are downloaded from package repositories.
To add the Docker GPG keys, run the following command in the terminal:
“`
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add –
“`
Installing Docker CE repository
Once the GPG keys are added, you can add the Docker CE repository to your system. The repository contains the Docker CE packages that you’ll need to install Docker.
To add the Docker CE repository, run the following command in the terminal:
“`
sudo add-apt-repository “deb [arch=amd64] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable”
“`
Installing Docker CE
Finally, you can install Docker CE on your system by running the following command in the terminal:
“`
sudo apt-get update
sudo apt-get install docker-ce docker-ce-cli containerd.io
“`
In addition to Docker CE, you may also want to install the docker-compose-plugin. The docker-compose-plugin provides a simple and efficient way to manage multi-container applications.
To install the docker-compose-plugin, run the following command in the terminal:
“`
sudo apt-get install docker-compose
“`
Checking if Docker CE is installed correctly
To check if Docker CE is installed correctly, you can run the following command in the terminal:
“`
docker version
“`
This command will display the Docker client version and the Docker server version. If the command outputs information about your Docker installation, Docker CE is installed correctly.
Additionally, if you plan to use Docker without using the sudo command, you can add your user to the docker group. To do so, run the following command in the terminal:
“`
sudo usermod -aG docker $USER
“`
This will add your current user to the docker group, allowing you to run Docker commands without using sudo.
Installing NVIDIA Container Toolkit on Linux Mint 21
If you’re planning to use Docker in conjunction with your NVIDIA GPU, you’ll need to install the NVIDIA Container Toolkit on your system. The NVIDIA Container Toolkit provides a set of tools and libraries that allow GPU-accelerated Docker containers to run on your system.
Installing NVIDIA Container Toolkit GPG keys
Before you can install the NVIDIA Container Toolkit, you need to add the NVIDIA Container Toolkit GPG keys to your system. To add the NVIDIA Container Toolkit GPG keys, run the following command in the terminal:
“`
curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add –
“`
Installing NVIDIA Container Toolkit repository
Once the GPG keys are added, you can add the NVIDIA Container Toolkit repository to your system. To add the NVIDIA Container Toolkit repository, run the following command in the terminal:
“`
distribution=$(.
/etc/os-release;echo $ID$VERSION_ID)
curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list |
sudo tee /etc/apt/sources.list.d/nvidia-docker.list
“`
Installing NVIDIA Docker drivers
Finally, you can install the NVIDIA Docker drivers on your system. The NVIDIA Docker drivers enable Docker containers to access your NVIDIA GPU.
To install the NVIDIA Docker drivers, run the following command in the terminal:
“`
sudo apt-get update
sudo apt-get install -y nvidia-docker2
sudo systemctl restart docker
“`
With the NVIDIA Container Toolkit installed, you can now run GPU-accelerated Docker containers on your system. To run a GPU-accelerated Docker container, use the following command:
“`
docker run –gpus all
“`
Conclusion
In this article, we’ve covered how to install Docker CE and the NVIDIA Container Toolkit on Linux Mint 21. By following the steps outlined in this article, you’ll be able to create, deploy, and run Docker containers on your system, with or without GPU acceleration.
To learn more about Docker and the NVIDIA Container Toolkit, be sure to check out the official documentation. Happy containerizing!
Accessing NVIDIA GPU from Docker containers
Docker is a platform for developing and deploying applications in a containerized environment. With Docker, developers can easily create, deploy, and run applications as containers.
In addition, Docker also supports accessing NVIDIA GPUs from within a containerized environment. In this article, we will explore how to check if NVIDIA GPUs are accessible from Docker containers.
We will begin by discussing what a NVIDIA CUDA Docker container is and move onto topics such as the
nvidia-smi command, CUDA version, and the
NVIDIA GPU driver. What is a NVIDIA CUDA Docker container?
A NVIDIA CUDA Docker container is a Docker container that includes the NVIDIA CUDA toolkit. The CUDA toolkit is a programming model that enables developers to write code for NVIDIA GPUs and customize it for different computing workloads.
By using a NVIDIA CUDA Docker container, developers can perform computations on NVIDIA GPUs in a containerized environment.
Checking if NVIDIA GPU is accessible from Docker containers
To check if a NVIDIA GPU is accessible from within a Docker container, the
nvidia-smi command can be used. The
nvidia-smi command is a tool provided by NVIDIA that allows users to monitor and manage their NVIDIA GPUs.
To check if a NVIDIA GPU is accessible from within a Docker container, follow these steps:
1. Start a Docker container using the NVIDIA CUDA image:
“`
docker run –gpus all -it –rm nvidia/cuda:11.2.0-base
nvidia-smi
“`
The –gpus flag specifies that all available GPUs should be accessible from within the container. 2.
Once the container is running, check if the NVIDIA GPU is accessible by running the
nvidia-smi command:
“`
nvidia-smi
“`
This command will show information about the NVIDIA GPU, such as its utilization and memory usage. If the
nvidia-smi command shows information about the NVIDIA GPU, it means that the GPU is accessible from within the Docker container.
CUDA Version
If you’re using a NVIDIA CUDA Docker container, it’s important to ensure that the correct version of CUDA is installed. To check the version of CUDA installed in a Docker container, follow these steps:
1.
Start a Docker container using the NVIDIA CUDA image:
“`
docker run –gpus all -it –rm nvidia/cuda:11.2.0-base
nvidia-smi
“`
The –gpus flag specifies that all available GPUs should be accessible from within the container. 2.
Once the container is running, check the version of CUDA installed by running the nvcc command:
“`
nvcc –version
“`
This command will show the version of CUDA installed in the Docker container. If the Docker container does not have the version of CUDA you require, you can install a different version of the CUDA toolkit by creating a new Docker image with the required version of the CUDA toolkit.
NVIDIA GPU driver
To ensure that a NVIDIA GPU is accessible from within a Docker container, it’s important to install the correct
NVIDIA GPU driver. NVIDIA provides a tool called the NVIDIA Driver Container Toolkit that simplifies the installation of
NVIDIA GPU drivers in Docker containers.
To install the NVIDIA Driver Container Toolkit, follow these steps:
1. Add the NVIDIA GPG key to your system:
“`
curl https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add –
“`
2.
Add the NVIDIA Docker repository to your system:
“`
distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list
“`
3.
Install the NVIDIA Docker runtime:
“`
sudo apt-get update && sudo apt-get install -y nvidia-docker2
“`
Once the NVIDIA Driver Container Toolkit is installed,
NVIDIA GPU drivers will be automatically installed in Docker containers that use the NVIDIA Docker runtime.
Conclusion
In this article, we’ve explored how to check if NVIDIA GPUs are accessible from Docker containers. We’ve discussed the
nvidia-smi command, CUDA version, and the
NVIDIA GPU driver. By following the steps outlined in this article, you’ll be able to ensure that your NVIDIA GPUs can be accessed from within Docker containers.
In summary, this article covered the process of accessing NVIDIA GPUs from Docker containers. We discussed the importance of using NVIDIA CUDA Docker containers, and how to check if a NVIDIA GPU is accessible from within a Docker container using the
nvidia-smi command. We also covered the importance of checking the CUDA version and
NVIDIA GPU driver.
By following the steps outlined in this article, users can ensure their NVIDIA GPUs can be accessed from within Docker containers, enabling them to develop and deploy applications in a containerized environment with the power of GPU acceleration. It’s important to always use the correct NVIDIA CUDA version and GPU driver to ensure maximum efficiency and compatibility.