nvidia docker install

https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html#docker

Installation Guide

Supported Platforms

The NVIDIA Container Toolkit is available on a variety of Linux distributions and supports different container engines.

Linux Distributions

Supported Linux distributions are listed below:

OS Name / Version	Identifier	amd64 / x86_64	ppc64le	arm64 / aarch64
Amazon Linux 1	amzn1	X
Amazon Linux 2	amzn2	X
Amazon Linux 2017.09	amzn2017.09	X
Amazon Linux 2018.03	amzn2018.03	X
Open Suse Leap 15.0	sles15.0	X
Open Suse Leap 15.1	sles15.1	X
Debian Linux 9	debian9	X
Debian Linux 10	debian10	X
Centos 7	centos7	X	X
Centos 8	centos8	X	X	X
RHEL 7.4	rhel7.4	X	X
RHEL 7.5	rhel7.5	X	X
RHEL 7.6	rhel7.6	X	X
RHEL 7.7	rhel7.7	X	X
RHEL 8.0	rhel8.0	X	X	X
RHEL 8.1	rhel8.1	X	X	X
RHEL 8.2	rhel8.2	X	X	X
Ubuntu 16.04	ubuntu16.04	X	X
Ubuntu 18.04	ubuntu18.04	X	X	X
Ubuntu 20.04	ubuntu20.04	X	X	X

Container Runtimes

Supported container runtimes are listed below:

OS Name / Version	amd64 / x86_64	ppc64le	arm64 / aarch64
Docker 18.09	X	X	X
Docker 19.03	X	X	X
RHEL/CentOS 8 podman	X
CentOS 8 Docker	X
RHEL/CentOS 7 Docker	X

Note

On Red Hat Enterprise Linux (RHEL) 8, Docker is no longer a supported container runtime. See Building, Running and Managing Containers for more information on the container tools available on the distribution.

Pre-Requisites

NVIDIA Drivers

Before you get started, make sure you have installed the NVIDIA driver for your Linux distribution. The recommended way to install drivers is to use the package manager for your distribution but other installer mechanisms are also available (e.g. by downloading .run installers from NVIDIA Driver Downloads).

For instructions on using your package manager to install drivers from the official CUDA network repository, follow the steps in this guide.

Platform Requirements

The list of prerequisites for running NVIDIA Container Toolkit is described below:

1. GNU/Linux x86_64 with kernel version > 3.10

2. Docker >= 19.03 (recommended, but some distributions may include older versions of Docker. The minimum supported version is 1.12)

3. NVIDIA GPU with Architecture > Fermi (or compute capability 2.1)

4. NVIDIA drivers ~= 361.93 (untested on older versions)

Note

Your driver version might limit your CUDA capabilities. Newer NVIDIA drivers are backwards-compatible with CUDA Toolkit versions, but each new version of CUDA requires a minimum driver version. Running a CUDA container requires a machine with at least one CUDA-capable GPU and a driver compatible with the CUDA toolkit version you are using. The machine running the CUDA container only requires the NVIDIA driver, the CUDA toolkit doesn’t have to be installed. The CUDA release notes includes a table of the minimum driver and CUDA Toolkit versions.

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Docker

Getting Started

For installing Docker CE, follow the official instructions for your supported Linux distribution. For convenience, the documentation below includes instructions on installing Docker for various Linux distributions.

Warning

If you are migrating fron nvidia-docker 1.0, then follow the instructions in the Migration from nvidia-docker 1.0 guide.

Installing on Ubuntu and Debian

The following steps can be used to setup NVIDIA Container Toolkit on Ubuntu LTS - 16.04, 18.04, 20.4 and Debian - Stretch, Buster distributions.

Setting up Docker

Docker-CE on Ubuntu can be setup using Docker’s official convenience script:

$ curl https://get.docker.com | sh 
  && sudo systemctl --now enable docker

See also

Follow the official instructions for more details and post-install actions.

Setting up NVIDIA Container Toolkit

Setup the stable repository and the GPG key:

$ 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

Note

To get access to experimental features such as CUDA on WSL or the new MIG capability on A100, you may want to add the experimental branch to the repository listing:

$ curl -s -L https://nvidia.github.io/nvidia-container-runtime/experimental/$distribution/nvidia-container-runtime.list | sudo tee /etc/apt/sources.list.d/nvidia-container-runtime.list

Install the nvidia-docker2 package (and dependencies) after updating the package listing:

$ sudo apt-get update

$ sudo apt-get install -y nvidia-docker2

Restart the Docker daemon to complete the installation after setting the default runtime:

$ sudo systemctl restart docker

At this point, a working setup can be tested by running a base CUDA container:

$ sudo docker run --rm --gpus all nvidia/cuda:11.0-base nvidia-smi

This should result in a console output shown below:

+-----------------------------------------------------------------------------+
| NVIDIA-SMI 450.51.06    Driver Version: 450.51.06    CUDA Version: 11.0     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  Tesla T4            On   | 00000000:00:1E.0 Off |                    0 |
| N/A   34C    P8     9W /  70W |      0MiB / 15109MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|  No running processes found                                                 |
+-----------------------------------------------------------------------------+

 conclusion:

254 curl https://get.docker.com | sh && sudo systemctl --now enable docker
255 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
257 sudo apt-get install -y nvidia-docker2
258 sudo systemctl restart docker
259 sudo docker run --rm --gpus all nvidia/cuda:11.0-base nvidia-smi