Get Docker Engine - Community for CentOS
参考：https://docs.docker.com/install/linux/docker-ce/centos/
1、Install using the repository
Before you install Docker Engine - Community for the first time on a new host machine, you need to set up the Docker repository. Afterward, you can install and update Docker from the repository.
(1) SET UP THE REPOSITORY
Install required packages. yum-utils provides the yum-config-manager utility, and device-mapper-persistent-data and lvm2 are required by the devicemapper storage driver.
$ sudo yum install -y yum-utils \
device-mapper-persistent-data \
lvm2
Use the following command to set up the stable repository.
$ sudo yum-config-manager \
--add-repo \
https://download.docker.com/linux/centos/docker-ce.repo
(2) INSTALL DOCKER ENGINE - COMMUNITY
(a) Install the latest version of Docker Engine - Community and containerd, or go to the next step to install a specific version:
$ sudo yum install docker-ce docker-ce-cli containerd.io
If prompted to accept the GPG key, verify that the fingerprint matches 060A 61C5 1B55 8A7F 742B 77AA C52F EB6B 621E 9F35, and if so, accept it.
(b) Start Docker.
$ sudo systemctl start docker
(c) Verify that Docker Engine - Community is installed correctly by running the hello-world image.
$ sudo docker run hello-world
This command downloads a test image and runs it in a container. When the container runs, it prints an informational message and exits.
Docker Engine - Community is installed and running. You need to use sudo to run Docker commands.
2、Add the NVIDIA Container Toolkit
参考：https://github.com/NVIDIA/nvidia-docker
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. If you are an existing user of the nvidia-docker2 packages, review the instructions in the “Upgrading with nvidia-docker2” section.
For first-time users of Docker 19.03 and GPUs, continue with the instructions for getting started below.
$ distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
$ curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.repo | sudo tee /etc/yum.repos.d/nvidia-docker.repo
$ sudo yum install -y nvidia-container-toolkit
$ sudo systemctl restart docker
Usage
#### Test nvidia-smi with the latest official CUDA image
$ docker run --gpus all nvidia/cuda:9.0-base nvidia-smi
# Start a GPU enabled container on two GPUs
$ docker run --gpus 2 nvidia/cuda:9.0-base nvidia-smi
# Starting a GPU enabled container on specific GPUs
$ docker run --gpus '"device=1,2"' nvidia/cuda:9.0-base nvidia-smi
$ docker run --gpus '"device=UUID-ABCDEF,1"' nvidia/cuda:9.0-base nvidia-smi
# Specifying a capability (graphics, compute, ...) for my container
# Note this is rarely if ever used this way
$ docker run --gpus all,capabilities=utility nvidia/cuda:9.0-base nvidia-smi