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Using CUDA in Docker Images
Compute Resources
Have questions or need help with compute, including activation or issues? Follow this link.
Docker Usage
The information on this page assumes that you have a knowledge base of using Docker to create images and push them to a repository for use. If you need to review that information, please see the links below.
Overview
This documentation will guide you on making sure you’re using the most appropriate CUDA version for your Docker image in regards to the Scientific Compute Platform.
Using the Correct Version
Examples of appropriate base images:
nvidia/cuda:12.4.1-base-ubuntu22.04
nvidia/cuda:12.4.1-runtime-ubuntu22.04
ghcr.io/washu-it-ris/novnc:ubuntu22.04_cuda12.4_runtime
ghcr.io/washu-it-ris/novnc:ubuntu22.04_cuda12.4_develNvidia has a lot of base images to develop from and can be found here: https://hub.docker.com/r/nvidia/cuda/tags
Testing Your Image
Shown below are the steps to run a test job.
Start up an interactive job with your Docker image.
There is a test script in
GitHub - WashU-IT-RIS/docker-osu-micro-benchmarks for the OSU GPU test.Clone the repository.
git clone https://github.com/WashU-IT-RIS/docker-osu-micro-benchmarks.gitChange directory to docker-osu-micro-benchmarks.
cd docker-osu-micro-benchmarksRun an OSU Benchmark GPU test.
Replace <test> with an OSU test that you want to run. For example, osu_bw for OSU bandwidth test.
Replace <compute-group> with the compute group you are a member of.
QUEUE=subscription bin/osu-test-gpu.sh <test> -G <compute-group>