Nvidia support for docker

If you want to expose your nvidia driver into the docker container this is possible by using the NVIDIA Container Toolkit.

Prerequisites

Before we can install the NVIDIA Container Toolkit we have to install the nvidia drivers for our platform and install docker.

NOTE: Check the end of the file for some tips about throubleshoting.

Nvidia drivers

Make sure you have the NVIDIA drivers for your Linux distribution installed. This can either be done by using your package manager or you can download the .run installers from NVIDIA Driver Downloads. This depends on the operating system and package manager you are using so you have to look it up. You can then check your drivers by typing

nvidia-smi # NVIDIA System Management Interface program

Which should print something like this:

+-----------------------------------------------------------------------------+
| NVIDIA-SMI 515.48.07    Driver Version: 515.48.07    CUDA Version: 11.7     |
|-------------------------------+----------------------+----------------------+
| 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  NVIDIA GeForce ...  Off  | 00000000:01:00.0  On |                  N/A |
| N/A   37C    P8    18W /  N/A |    550MiB /  8192MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|    0   N/A  N/A      1435      G   ...xorg-server-1.20.14/bin/X      288MiB |
|    0   N/A  N/A      2516      G   ....0.2/bin/.firefox-wrapped      144MiB |
+-----------------------------------------------------------------------------+

Docker installation

Make sure docker is installed and it’s working correctly. For instructions on how to install docker have a look in general info on docker installation.

How to setup a container with nvidia support

Install nvidia-docker

NOTE: If you already have installed nvidia-docker, you can skip this and go right to the next section.

  1. You then have to install the NVIDIA Container Toolkit for docker as described in official documentation. For Ubuntu this can be done as follows:

    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

    You then have to update your package list to include the new added nvidia-docker2.

    sudo apt-get update

    And install the the NVIDIA Container Toolkit:

    sudo apt-get install -y nvidia-docker2

    After the installation finished, you need to restart the Docker daemon:

    sudo service docker restart

    At this point you can verify that everything works as intended by running:

    docker run --rm --gpus all nvidia/cuda:11.7.1-base-ubuntu22.04 nvidia-smi

NOTE: if you get an error executing above docker command make sure that you have Nvidia Driver version 515 or above installed!

Which should print something like:

+-----------------------------------------------------------------------------+
| NVIDIA-SMI 515.48.07    Driver Version: 515.48.07    CUDA Version: 11.7     |
|-------------------------------+----------------------+----------------------+
| 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  NVIDIA GeForce ...  Off  | 00000000:01:00.0  On |                  N/A |
| N/A   37C    P8    18W /  N/A |    478MiB /  8192MiB |      3%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
+-----------------------------------------------------------------------------+

Change the Dockerfile

(1.) If you haven’t done so already:

Create a new docker workspace with the setup-ros-workspace-docker command.

NOTE: If you set up a nvidia-docker container, you are finished at this point.

  1. Replace the the FROM ubuntu:<version> directive in your Dockerfile with the nvidia container of your needs. The following table gives you a quick overview:

    Examples for nvidia containers

    Ubuntu version directive

    Nvidia docker replacement

    Ubuntu:20.04

    nvidia/cuda:11.7.1-base-ubuntu20.04

    Ubuntu:22.04

    nvidia/cuda:11.7.1-base-ubuntu22.04

    A list of all available containers can be found in the official documentation.

  2. Remove the existing docker container and image.

    docker container rm <container-name>

    docker image rm <image-name>

  3. Recreate your container. Go inside the .rtw_docker_defines directory in your workspace folder and the execute:

    ./recreate_docker.sh

You now should have a docker container which exposes your nvidia drivers and can switch to your workspace with rtw_switch_to_docker.

Troubleshoting

Be sure that graphics card driver is installed properly

Check if drivers and libraries are installed properly by executing nvidia-smi after a fresh system start (Yes, you have to restart your computer!). There you should see expected version of Nvidia driver. If you get any error follow the next steps to be sure that the expected version of driver is installed properly.

  1. Install required version of the driver using GUI for additional drivers in system’s settings or ubuntu-drivers command.

    Note

    Be careful when executing command if multiple devices are using custom drivers you can unintenntionaly install wrong driver for another device (you will know if this is relevant for you - but it is imprtant to note it.)

  2. Delete all other nvidia driver’s version and corresponding libraries - use purge command for it.

  3. Restart your computer.

  4. If you have issues with the graphics after restart do the following:

    1. Close your eyes and breathe slowely in and out at least once :)

    2. You probably didn’t install everything properly so the open-source nouveau driver is used which is not adequate for this scenario.

    3. Use <CTRL> + <ALT> + <F2-3-4...> keys to switch to a linux terminal.

    4. Login there and execute ubuntu-drivers command to install missing drivers.

    5. Now restart again and everything should work properly.

  5. Now check again output of the ṅvidia-smi command

Graphics card should be used in the Performance mode

If you have only X in the output from nvidia-smi than make sure that the graphics card uses Performance Mode in PRIME profile section of “NVIDIA X Server Settings” application.

nvidia-smi command inside docker container

Take a note that nvidia-smi command in the docker container is necessary test to see if docker has access to the graphic card, but it doesn’t shows any applications that are using it. You can see on your host if a docker application is using graphic card and how much.

References