Intel Gaudi Device Plugin for Kubernetes

This is a Kubernetes device plugin implementation that enables the registration of the Intel® Gaudi® AI accelerator in a container cluster for compute workload. With the appropriate hardware and this plugin deployed in your Kubernetes cluster, you will be able to run jobs that require a Gaudi device.

The Intel Gaudi device plugin for Kubernetes is a Daemonset that allows you to automatically:

• Enable the registration of Gaudi cards in your Kubernetes cluster.

• Keep track of the health of your device.

Prerequisites

The below lists the prerequisites needed for running the Intel Gaudi device plugin:

• Intel Gaudi software drivers loaded on the system

• Kubernetes version listed in the Support Matrix

Deployment

Enable Gaudi cards’ resource support in Kubernetes.

You must run the device plugin on all the nodes that are equipped with Gaudi by deploying the following Daemonset using the kubectl create command (see the below command).

Note

kubectl needs access to a Kubernetes cluster to implement these commands.

For deployment of the device plugin, the associated .yaml file can be used to setup the environment:

$ kubectl create -f
https://vault.habana.ai/artifactory/docker-k8s-device-plugin/habana-k8s-device-plugin.yaml

Check the device plugin deployment status by running the following command:

$ kubectl get pods -n habana-system

Running Gaudi Jobs Example

You can create a Kubernetes Job that acquires a Gaudi device by using the resource.limits field. This is an example using Intel Gaudi’s PyTorch container image:

$ cat <<EOF | kubectl apply -f -

apiVersion: batch/v1
kind: Job
metadata:
   name: habanalabs-gaudi-demo
spec:
   template:
      spec:
         hostIPC: true
         restartPolicy: OnFailure
         containers:
          - name: habana-ai-base-container
            image: vault.habana.ai/gaudi-docker/1.15.1/ubuntu22.04/habanalabs/pytorch-installer-2.2.0:latest
            workingDir: /root
            command: ["hl-smi"]
            securityContext:
               capabilities:
                  add: ["SYS_NICE"]
            resources:
               limits:
                  habana.ai/gaudi: 1
                  memory: 409Gi
                  hugepages-2Mi: 95000Mi
EOF

Check the pod status:

$ kubectl get pods

Retrieve the name of the pod and see the results:

kubectl logs <pod-name>