OpenShell/e2e/gpu/images/cuda-basic/README.md

GPU workload CUDA basic

cuda-basic validates that a GPU-enabled environment can run a basic CUDA runtime workload. It is a single image that runs two validation steps:

1. deviceQuery checks CUDA runtime, driver, and device discovery.
2. vectorAdd checks kernel launch, device memory allocation, host/device copies, synchronization, and result validation.

The image builds the samples from NVIDIA/cuda-samples tag v12.8 with a CUDA 12.8 builder image, then copies only the compiled binaries into the OpenShell default workload final image.

The workload prints OPENSHELL_GPU_WORKLOAD_SUCCESS only after both samples pass. On failure it prints OPENSHELL_GPU_WORKLOAD_FAILURE and exits non-zero.

Build it with:

mise run e2e:workloads:build

That command also refreshes the local workload manifest at e2e/gpu/images/.build/workloads.yaml.

To build only this workload locally, set:

OPENSHELL_GPU_WORKLOAD_IMAGES=cuda-basic mise run e2e:workloads:build

Run it directly with Docker CDI:

source e2e/gpu/images/.build/latest.env
docker run --rm --device nvidia.com/gpu=all \
  "${OPENSHELL_E2E_GPU_CUDA_WORKLOAD_IMAGE}"

Use podman run with the same --device nvidia.com/gpu=all option when Podman CDI is configured.

The image does not vendor GPU driver libraries such as libcuda.so.1. Those libraries must be provided by the host GPU runtime or CDI injection.

The CUDA samples are redistributed under the NVIDIA CUDA samples license. The license text is copied into the image at /usr/local/share/doc/openshell-gpu-workload/cuda-samples.LICENSE.