Installing on CentOS 7/8
The following steps can be used to setup the NVIDIA Container Toolkit on CentOS 7/8.
Setting up Docker on CentOS 7/8
Note
If you’re on a cloud instance such as EC2, then the official CentOS images may not include
tools such as iptables
which are required for a successful Docker installation. Try this command to get a more functional VM,
before proceeding with the remaining steps outlined in this document.
$ sudo dnf install -y tar bzip2 make automake gcc gcc-c++ vim pciutils elfutils-libelf-devel libglvnd-devel iptables
Setup the official Docker CE repository:
$ sudo dnf config-manager --add-repo=https://download.docker.com/linux/centos/docker-ce.repo
$ sudo yum-config-manager --add-repo=https://download.docker.com/linux/centos/docker-ce.repo
Now you can observe the packages available from the docker-ce repo:
$ sudo dnf repolist -v
$ sudo yum repolist -v
Since CentOS does not support specific versions of containerd.io
packages that are required for newer versions
of Docker-CE, one option is to manually install the containerd.io
package and then proceed to install the docker-ce
packages.
Install the containerd.io
package:
$ sudo dnf install -y https://download.docker.com/linux/centos/7/x86_64/stable/Packages/containerd.io-1.4.3-3.1.el7.x86_64.rpm
$ sudo yum install -y https://download.docker.com/linux/centos/7/x86_64/stable/Packages/containerd.io-1.4.3-3.1.el7.x86_64.rpm
And now install the latest docker-ce
package:
$ sudo dnf install docker-ce -y
$ sudo yum install docker-ce -y
Ensure the Docker service is running with the following command:
$ sudo systemctl --now enable docker
And finally, test your Docker installation by running the hello-world
container:
$ sudo docker run --rm hello-world
This should result in a console output shown below:
Unable to find image 'hello-world:latest' locally
latest: Pulling from library/hello-world
0e03bdcc26d7: Pull complete
Digest: sha256:7f0a9f93b4aa3022c3a4c147a449bf11e0941a1fd0bf4a8e6c9408b2600777c5
Status: Downloaded newer image for hello-world:latest
Hello from Docker!
This message shows that your installation appears to be working correctly.
To generate this message, Docker took the following steps:
1. The Docker client contacted the Docker daemon.
2. The Docker daemon pulled the "hello-world" image from the Docker Hub.
(amd64)
3. The Docker daemon created a new container from that image which runs the
executable that produces the output you are currently reading.
4. The Docker daemon streamed that output to the Docker client, which sent it
to your terminal.
To try something more ambitious, you can run an Ubuntu container with:
$ docker run -it ubuntu bash
Share images, automate workflows, and more with a free Docker ID:
https://hub.docker.com/
For more examples and ideas, visit:
https://docs.docker.com/get-started/
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/$distribution/nvidia-docker.repo | sudo tee /etc/yum.repos.d/nvidia-docker.repo
Install the nvidia-docker2
package (and dependencies) after updating the package listing:
$ sudo dnf clean expire-cache --refresh
$ sudo yum clean expire-cache
$ sudo dnf install -y nvidia-docker2
$ sudo yum 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 |
+-----------------------------------------------------------------------------+