k3d-gpu-support

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k3d-gpu-support

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Containerized k3s CUDA support for k3d bootstrapping

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# K3d GPU Support

This is a simple repository for preparing a `k3s` + `nvidia/cuda` base image that enables a K3d cluster to have access to your host machine's NVIDIA, CUDA-capable GPU(s).

## Pre-Requisites

Access to GitHub and GitHub Container Registry. Please follow the [GitHub Container Registry instructions](https://docs.github.com/en/packages/working-with-a-github-packages-registry/working-with-the-container-registry).

Docker and all of its dependencies must be installed.

For the container GPU test, a NVIDIA GPU with CUDA cores and drivers must be present. Additionally, the CUDA toolkit and NVIDIA container toolkit must be installed.

For Kubernetes testing and pre-requisites, please see [Kubernetes Deployment](#kubernetes-deployment) for details.

## Usage

### Building and Pushing the Image

Check out the Make targets for the various options.

## Kubernetes Deployment

Follow the instructions in the [zarf-package-k3d-airgap](https://github.com/defenseunicorns/zarf-package-k3d-airgap) repository for bootstrapping a K3d cluster that can access your NVIDIA GPUs.

You can also a use more abstracted version of the above Kubernetes deployment by following the instructions in the [uds-leapfrogai](https://github.com/defenseunicorns/uds-leapfrogai/tree/main/bundles/gpu) bundle repository.

## Test

Run:

```shell
kubectl apply -f test/cuda-vector-add.yaml
kubectl logs cuda-vector-add
```

## References

* https://k3d.io/v5.7.2/usage/advanced/cuda/

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