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Nvidia:Docker

lastmod 2025-12-18created 2018-07-2425 edits

How to install

(2024-04-08) Ubuntu 20.04 installation verified with the latest version 

curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg \
  && curl -s -L https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list | \
    sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' | \
    sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list

sudo apt-get update
sudo apt-get install -y nvidia-container-toolkit

Configure the container runtime by using the nvidia-ctk command: 

sudo nvidia-ctk runtime configure --runtime=docker

Running the command above prints a log like the following. 

WARN[0000] Ignoring runtime-config-override flag for docker 
INFO[0000] Config file does not exist; using empty config 
INFO[0000] Wrote updated config to /etc/docker/daemon.json 
INFO[0000] It is recommended that docker daemon be restarted.

The nvidia-ctk command modifies the /etc/docker/daemon.json file on the host. The file is updated so that Docker can use the NVIDIA Container Runtime.

Restart the docker service: 

sudo systemctl restart docker

Running a Sample Workload with Docker: 

docker run --rm --runtime=nvidia --gpus all ubuntu nvidia-smi

(2022-10-27) Ubuntu 20.04 installation verified with the latest version

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

Setting up NVIDIA Container Toolkit

Setup the package repository and the GPG key: 

distribution=$(. /etc/os-release;echo $ID$VERSION_ID) \
      && curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg \
      && curl -s -L https://nvidia.github.io/libnvidia-container/$distribution/libnvidia-container.list | \
            sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' | \
            sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list

WARNING

For versions of the NVIDIA Container Toolkit prior to 1.6.0, the nvidia-docker repository should be used instead of the libnvidia-container repository above.

In some cases, the downloaded list file may contain URLs that do not match the expected distribution value, because the packages can be used for all compatible distributions. For example:

  • For distribution values of ubuntu20.04 or ubuntu22.04, the file contains ubuntu18.04 URLs.
  • For a distribution value of debian11, the file contains debian10 URLs.

WARNING

If you get an error about conflicting Signed-By options when running apt update after configuring the repository, see the relevant troubleshooting section.

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:11.0.3-base-ubuntu20.04 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                                                 |
+-----------------------------------------------------------------------------+

Ubuntu 16.04/18.04/20.04, Debian Jessie/Stretch/Buster 

# Add the package repositories
$ 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

$ sudo apt-get update && sudo apt-get install -y nvidia-container-toolkit
$ sudo systemctl restart docker

CentOS 7.X/8.X (docker-ce), RHEL 7.X/8.X (docker-ce), Amazon Linux 1/2 

$ 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:10.0-base nvidia-smi

# Start a GPU enabled container on two GPUs
docker run --gpus 2 nvidia/cuda:10.0-base nvidia-smi

# Starting a GPU enabled container on specific GPUs
docker run --gpus '"device=1,2"' nvidia/cuda:10.0-base nvidia-smi
docker run --gpus '"device=UUID-ABCDEF,1"' nvidia/cuda:10.0-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:10.0-base nvidia-smi

Legacy versions used --runtime=nvidia instead of --gpus all.

nvidia-docker-compose

See nvidia-docker-compose.

Troubleshooting

libnvidia-tls.so no search file

The following error may occur. 

docker: Error response from daemon: OCI runtime create failed: container_linux.go:349: starting container process caused "process_linux.go:449: conatiner init caused \"process_linux.go:432: running prestart hook 0 caused \\\"error running hook: exit status 1, stdout: , stderr: nvidia-container-cli: detection error: open failed: /usr/lib/x86_64-linux-gnu/libnvidia-tls.so.450.36.06: no such file or directory

The file /usr/lib/x86_64-linux-gnu/libnvidia-tls.so.450.36.06 cannot be found. Running the nvidia-container-cli -V command probably won't work properly either.

Reinstall nvidia-docker.

could not select device driver 

docker run --gpus all --rm --name deepstream nvcr.io/nvidia/deepstream:7.1-samples-multiarch

The following error is printed: 

docker: Error response from daemon: could not select device driver "" with capabilities: [[gpu]].

Reinstall the container toolkit: 

sudo apt-get update
sudo apt-get install -y nvidia-container-toolkit
sudo systemctl restart docker

See also

Favorite site

References

  1. EXPERIENTIA_DOCET_-_nvidia_docker_ngc.pdf ↩

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