This is a note on setting up a Docker environment using NVIDIA’s GPGPU with WSL2 on Windows 11.
1. About Hardware and Installed Software
I used a desktop computer ESPRIMO WD2/H2 with NVIDIA GeForce GTX 1650.
I started setting up the environment on Windows 11 with the NVIDIA GeForce GTX 1650 driver (NVIDIA Studio driver) and CUDA Toolkit 12.4 for Windows installed.
2. I booted Ubuntu 22.04 on WSL2 and followed the steps below to set up the environment.
2.1. I installed the NVIDIA Container Toolkit following the instructions in “Installing with Apt” on the following page from NVIDIA.
https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html
2.1.1. The configuration of the apt repository was updated with the following command.
fukagai@ESPRIMOWD2H2:~$ 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
deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://nvidia.github.io/libnvidia-container/stable/deb/$(ARCH) /
#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://nvidia.github.io/libnvidia-container/experimental/deb/$(ARCH) /
2.1.2. The list of apt packages was updated with the following command.
fukagai@ESPRIMOWD2H2:~$ sudo apt-get update Get:1 https://nvidia.github.io/libnvidia-container/stable/deb/amd64 InRelease [1477 B] Get:2 https://nvidia.github.io/libnvidia-container/stable/deb/amd64 Packages [9176 B] Get:3 http://security.ubuntu.com/ubuntu jammy-security InRelease [110 kB] ... Get:40 http://archive.ubuntu.com/ubuntu jammy-backports/multiverse amd64 c-n-f Metadata [116 B] Fetched 31.1 MB in 10s (3012 kB/s) Reading package lists... Done
2.1.3. NVIDIA Container Toolkit was installed with the following command.
fukagai@ESPRIMOWD2H2:~$ sudo apt-get install -y nvidia-container-toolkit Reading package lists... Done Building dependency tree... Done Reading state information... Done The following additional packages will be installed: libnvidia-container-tools libnvidia-container1 nvidia-container-toolkit-base The following NEW packages will be installed: libnvidia-container-tools libnvidia-container1 nvidia-container-toolkit nvidia-container-toolkit-base 0 upgraded, 4 newly installed, 0 to remove and 100 not upgraded. ... Setting up nvidia-container-toolkit (1.15.0-1) ... Processing triggers for libc-bin (2.35-0ubuntu3.4) ... /sbin/ldconfig.real: /usr/lib/wsl/lib/libcuda.so.1 is not a symbolic link
2.2. I installed Docker following the instructions on the following page.
https://docs.docker.com/engine/install/ubuntu/
2.2.1. The following commands were used to set up the Docker apt repository.
fukagai@ESPRIMOWD2H2:~$ sudo apt-get install ca-certificates curl fukagai@ESPRIMOWD2H2:~$ sudo install -m 0755 -d /etc/apt/keyrings fukagai@ESPRIMOWD2H2:~$ sudo curl -fsSL https://download.docker.com/linux/ubuntu/gpg -o /etc/apt/keyrings/docker.asc fukagai@ESPRIMOWD2H2:~$ sudo chmod a+r /etc/apt/keyrings/docker.asc fukagai@ESPRIMOWD2H2:~$ echo \ "deb [arch=$(dpkg --print-architecture) signed-by=/etc/apt/keyrings/docker.asc] https://download.docker.com/linux/ubuntu \ $(. /etc/os-release && echo "$VERSION_CODENAME") stable" | \ sudo tee /etc/apt/sources.list.d/docker.list > /dev/null fukagai@ESPRIMOWD2H2:~$ sudo apt-get update Get:1 https://download.docker.com/linux/ubuntu jammy InRelease [48.8 kB] Hit:2 https://nvidia.github.io/libnvidia-container/stable/deb/amd64 InRelease Get:3 https://download.docker.com/linux/ubuntu jammy/stable amd64 Packages [31.5 kB] Get:4 http://security.ubuntu.com/ubuntu jammy-security InRelease [110 kB] Hit:5 http://archive.ubuntu.com/ubuntu jammy InRelease Get:6 http://archive.ubuntu.com/ubuntu jammy-updates InRelease [119 kB] Hit:7 http://archive.ubuntu.com/ubuntu jammy-backports InRelease Fetched 309 kB in 2s (140 kB/s) Reading package lists... Done
2.2.2. The following command installed the Docker package.
fukagai@ESPRIMOWD2H2:~$ sudo apt-get install docker-ce docker-ce-cli containerd.io docker-buildx-plugin docker-compose-plugin
2.2.3. The following command was used to check the operation of the installed Docker.
fukagai@ESPRIMOWD2H2:~$ sudo docker run hello-world Unable to find image 'hello-world:latest' locally latest: Pulling from library/hello-world c1ec31eb5944: Pull complete Digest: sha256:a26bff933ddc26d5cdf7faa98b4ae1e3ec20c4985e6f87ac0973052224d24302 Status: Downloaded newer image for hello-world:latest Hello from Docker! This message shows that your installation appears to be working correctly. ...
2.3. I executed the following commands following the instructions in the “Configuring Docker” section of the following page from NVIDIA.
https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html
fukagai@ESPRIMOWD2H2:~$ sudo nvidia-ctk runtime configure --runtime=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. fukagai@ESPRIMOWD2H2:~$ sudo systemctl restart docker
The above commands will enable Docker to use NVIDIA Container Runtime.
After executing the command, /etc/docker/daemon.json has the following content.
fukagai@ESPRIMOWD2H2:~$ cat /etc/docker/daemon.json
{
"runtimes": {
"nvidia": {
"args": [],
"path": "nvidia-container-runtime"
}
}
}
2.4. I executed the command described in “Running a Sample Workload with Docker” on the following page from NVIDIA.
https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/sample-workload.html
When the following command was executed, the following message was output to the console.
fukagai@ESPRIMOWD2H2:~$ sudo docker run --rm --runtime=nvidia --gpus all ubuntu nvidia-smi Sun May 5 05:12:27 2024 +-----------------------------------------------------------------------------------------+ | NVIDIA-SMI 550.76.01 Driver Version: 552.22 CUDA Version: 12.4 | |-----------------------------------------+------------------------+----------------------+ | 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 GTX 1650 On | 00000000:01:00.0 Off | N/A | | 23% 42C P8 N/A / 75W | 619MiB / 4096MiB | 0% Default | | | | N/A | +-----------------------------------------+------------------------+----------------------+ +-----------------------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=========================================================================================| | 0 N/A N/A 25 G /Xwayland N/A | +-----------------------------------------------------------------------------------------+