87 lines
4.4 KiB
Markdown
87 lines
4.4 KiB
Markdown
# NVIDIA Container Toolkit
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[](https://raw.githubusercontent.com/NVIDIA/nvidia-docker/master/LICENSE)
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[](https://github.com/NVIDIA/nvidia-docker/wiki)
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[](https://nvidia.github.io/nvidia-docker)
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## Introduction
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The NVIDIA Container Toolkit allows users to build and run GPU accelerated Docker containers. The toolkit includes a container runtime [library](https://github.com/NVIDIA/libnvidia-container) and utilities to automatically configure containers to leverage NVIDIA GPUs. Full documentation and frequently asked questions are available on the [repository wiki](https://github.com/NVIDIA/nvidia-docker/wiki).
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## Quickstart
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**Make sure you have installed the [NVIDIA driver](https://github.com/NVIDIA/nvidia-docker/wiki/Frequently-Asked-Questions#how-do-i-install-the-nvidia-driver) and Docker 19.03 for your Linux distribution**
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Note that with the release of Docker 19.03, usage of nvidia-docker2 packages are deprecated since NVIDIA GPUs are now natively supported as devices in the Docker runtime.
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If you are an existing user of the nvidia-docker2 packages, review the instructions in the [“Upgrading with nvidia-docker2” section](https://github.com/NVIDIA/nvidia-docker/tree/master#upgrading-with-nvidia-docker2-deprecated).
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For first-time users of Docker 19.03 and GPUs, continue with the instructions for getting started below.
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### Ubuntu 16.04/18.04, Debian Jessie/Stretch
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```sh
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# Add the package repositories
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$ distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
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$ curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add -
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$ curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list
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$ sudo apt-get update && sudo apt-get install -y nvidia-container-toolkit
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$ sudo systemctl restart docker
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```
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#### CentOS 7 (docker-ce), RHEL 7.4/7.5 (docker-ce), Amazon Linux 1/2
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```
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$ distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
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$ curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.repo | sudo tee /etc/yum.repos.d/nvidia-docker.repo
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$ sudo yum install -y nvidia-container-toolkit
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$ sudo systemctl restart docker
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```
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## Usage
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```
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#### Test nvidia-smi with the latest official CUDA image
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$ docker run --gpus all nvidia/cuda:9.0-base nvidia-smi
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# Start a GPU enabled container on two GPUs
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$ docker run --gpus 2 nvidia/cuda:9.0-base nvidia-smi
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# Starting a GPU enabled container on specific GPUs
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$ docker run --gpus '"device=1,2"' nvidia/cuda:9.0-base nvidia-smi
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$ docker run --gpus '"device=UUID-ABCDEF,1'" nvidia/cuda:9.0-base nvidia-smi
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# Specifying a capability (graphics, compute, ...) for my container
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# Note this is rarely if ever used this way
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$ docker run --gpus all,capabilities=utility nvidia/cuda:9.0-base nvidia-smi
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```
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## Upgrading with nvidia-docker2 (Deprecated)
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If you are running an old version of docker (< 19.03) check the instructions on installing the [`nvidia-docker2`](https://github.com/NVIDIA/nvidia-docker/wiki/Installation-(version-2.0)) package which supports Docker >= 1.12.
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If you already have the old package installed (nvidia-docker2), updating to the latest Docker version (>= 19.03) will still work and will give you access to the new CLI options for supporting GPUs:
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```
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# On debian based distributions: Ubuntu / Debian
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$ sudo apt-get update
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$ sudo apt-get --only-upgrade install docker-ce nvidia-docker2
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$ sudo systemctl restart docker
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# On RPM based distributions: Centos / RHEL / Amazon Linux
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$ sudo yum upgrade -y nvidia-docker2
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$ sudo systemctl restart docker
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# All of the following options will continue working
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$ docker run --gpus all nvidia/cuda:9.0-base nvidia-smi
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$ docker run --runtime nvidia nvidia/cuda:9.0-base nvidia-smi
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$ nvidia-docker run nvidia/cuda:9.0-base nvidia-smi
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```
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Note that in the future, nvidia-docker2 packages will no longer be supported.
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## Issues and Contributing
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[Checkout the Contributing document!](CONTRIBUTING.md)
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* Please let us know by [filing a new issue](https://github.com/NVIDIA/nvidia-docker/issues/new)
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* You can contribute by opening a [pull request](https://help.github.com/articles/using-pull-requests/)
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