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MPS Support in the Kubernetes GPU Device Plugin

Install Drivers

distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
curl -s -L https://nvidia.github.io/libnvidia-container/gpgkey | sudo apt-key add -
curl -s -L https://nvidia.github.io/libnvidia-container/$distribution/libnvidia-container.list | sudo tee /etc/apt/sources.list.d/libnvidia-container.list

sudo apt-get update && sudo apt-get install -y nvidia-container-toolkit

sudo add-apt-repository ppa:graphics-drivers/ppa && sudo apt-get update

lspci | grep -i nvidia
ubuntu-drivers devices
ubuntu-drivers autoinstall
nvidia-smi

Uninstall K3s

/usr/local/bin/k3s-uninstall.sh
/usr/local/bin/k3s-agent-uninstall.sh

Add a RuntimeClass:

cat <<EOF | kubectl apply -f -
apiVersion: node.k8s.io/v1
kind: RuntimeClass
metadata:
  name: nvidia
handler: nvidia
EOF

Enabling GPU Support in K3s

# kubectl create -f https://raw.githubusercontent.com/NVIDIA/k8s-device-plugin/v0.16.1/nvidia-device-plugin.yml

cat <<EOF | kubectl apply -f -
apiVersion: apps/v1
kind: DaemonSet
metadata:
  name: nvidia-device-plugin-daemonset
  namespace: kube-system
spec:
  selector:
    matchLabels:
      name: nvidia-device-plugin-ds
  updateStrategy:
    type: RollingUpdate
  template:
    metadata:
      labels:
        name: nvidia-device-plugin-ds
    spec:
      runtimeClassName: nvidia # Added 😈
      tolerations:
      - key: nvidia.com/gpu
        operator: Exists
        effect: NoSchedule
      priorityClassName: "system-node-critical"
      containers:
      - image: nvcr.io/nvidia/k8s-device-plugin:v0.12.2
        name: nvidia-device-plugin-ctr
        env:
          - name: FAIL_ON_INIT_ERROR
            value: "false"
        securityContext:
          allowPrivilegeEscalation: false
          capabilities:
            drop: ["ALL"]
        volumeMounts:
          - name: device-plugin
            mountPath: /var/lib/kubelet/device-plugins
      volumes:
        - name: device-plugin
          hostPath:
            path: /var/lib/kubelet/device-plugins
EOF

TEST

cat <<EOF | kubectl apply -f -
apiVersion: apps/v1
kind: Deployment
metadata:
  name: nvidia-deployment
  namespace: default
spec:
  replicas: 1
  selector:
    matchLabels:
      app: nvidia
  template:
    metadata:
      labels:
        app: nvidia
    spec:
      runtimeClassName: nvidia
      restartPolicy: Always
      containers:
        - name: nvidia
          image: "nvidia/cuda:12.6.1-base-ubuntu22.04"
          command: [ "/bin/bash", "-c", "--" ]
          args: [ "while true; do sleep 30; done;" ]
          resources:
            limits:
              nvidia.com/gpu: 1
EOF

Rancher

curl https://raw.githubusercontent.com/helm/helm/master/scripts/get-helm-3 | bash
helm version

# If you have installed the CRDs manually instead of with the `--set installCRDs=true` option added to your Helm install command, you should upgrade your CRD resources before upgrading the Helm chart:
kubectl apply -f https://github.com/cert-manager/cert-manager/releases/download/v1.7.1/cert-manager.crds.yaml

# Add the Jetstack Helm repository
helm repo add jetstack https://charts.jetstack.io

# Update your local Helm chart repository cache
helm repo update

# Install the cert-manager Helm chart
helm install cert-manager jetstack/cert-manager \
  --namespace cert-manager \
  --create-namespace \
  --version v1.7.1

helm repo add rancher-stable https://releases.rancher.com/server-charts/stable
helm repo update

echo "export KUBECONFIG=/etc/rancher/k3s/k3s.yaml" >> ~/.bash_profile
source .bash_profile

kubectl create namespace cattle-system

helm install rancher rancher-stable/rancher \
  --namespace cattle-system \
  --set hostname=rancher.x.run \
  --set bootstrapPassword=admin

Other

k3s kubectl get pods -A
kubectl describe node