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Nvidia:Docker

How to install

(2024-04-08) 최신버전 확인된 Ubuntu 20.04 설치 버전 

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

위 명령을 치면 다음과 같은 로그가 출력된다. 

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.

docker 서비스 재시작한다: 

sudo systemctl restart docker

Running a Sample Workload with Docker: 

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

(2022-10-27) 최신버전 확인된 Ubuntu 20.04 설치 버전

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

NVIDIA Container Toolkit 1.6.0 이전 버전의 경우 위의 libnvidia-container 저장소 대신 nvidia-docker 저장소를 사용해야 합니다.

경우에 따라 다운로드한 목록 파일에 패키지가 호환되는 모든 배포판에 사용될 수 있으므로 예상되는 배포판 값과 일치하지 않는 URL이 포함될 수 있습니다. 예를 들면 다음과 같습니다.

  • ubuntu20.04 또는 ubuntu22.04 배포 값의 경우 파일에 ubuntu18.04 URL이 포함됩니다.
  • debian11 배포 값의 경우 파일에 debian10 URL이 포함됩니다.

WARNING

리포지토리를 구성한 후 apt update를 실행하면 Signed-By 옵션의 충돌과 관련된 오류가 발생하면 관련 문제 해결 섹션을 참조하십시오.

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 버전에서는 --gpus all 대신 --runtime=nvidia를 사용 했었다.

nvidia-docker-compose

nvidia-docker-compose 항목 참조.

Troubleshooting

libnvidia-tls.so no search file

다음과 같은 에러가 발생될 수 있다. 

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

/usr/lib/x86_64-linux-gnu/libnvidia-tls.so.450.36.06파일을 찾을 수 없다. 아마 nvidia-container-cli -V 명령을 실행해도 정상적으로 실행되지 않을 것이다.

nvidia-docker를 다시 설치하자.

could not select device driver 

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

다음과 같은 에러 출력됨: 

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

컨테이너 툴킷을 다시 설치하자: 

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 ↩