RKE2/K3s Nvidia GPU-Operator installation

Makefile

prep:
	helm repo add nvidia https://helm.ngc.nvidia.com/nvidia \
   && helm repo update

install:
	helm install --wait nvidiagpu \
     -n gpu-operator --create-namespace \
    --set toolkit.env[0].name=CONTAINERD_CONFIG \
    --set toolkit.env[0].value=/var/lib/rancher/k3s/agent/etc/containerd/config.toml \
    --set toolkit.env[1].name=CONTAINERD_SOCKET \
    --set toolkit.env[1].value=/run/k3s/containerd/containerd.sock \
    --set toolkit.env[2].name=CONTAINERD_RUNTIME_CLASS \
    --set toolkit.env[2].value=nvidia \
    --set toolkit.env[3].name=CONTAINERD_SET_AS_DEFAULT \
    --set-string toolkit.env[3].value=true \
     nvidia/gpu-operator

delete:
	helm uninstall -n gpu-operator nvidiagpu

cluster-info:
	kubectl get nodes -o wide

probably you could try nvcr.io/nvidia/l4t-cuda:12.2.2-devel-arm64-ubuntu22.04 or images from https://catalog.ngc.nvidia.com/orgs/nvidia/containers/l4t-cuda/tags
note: I am particularly sure and didn't tried it out.