Gaudi accelerators from Habana Labs (an Intel company) deliver low-cost-to-train deep learning models for natural language processing, object detection, and image recognition use cases.

AWS currently offers a dl1.24xlarge EC2 image with eight Gaudi accelerators available. See Amazon EC2 DL1 Instances.

Step 1: Add node pool and hardware tiers

Create or add a Gaudi-enabled node to an existing node-pool in your Domino cluster.
Create a hardware tier so users can use this resource in Domino.
1. Select the Use custom GPU resource name checkbox.
2. In GPU Resource Name enter habana.ai/gaudi.

Step 2: Install the Habana Device Plugin for Kubernetes

Prerequisite: Admin kubectl permissions to your cluster

Use the kubectl command to add the Habana device plugin for Kubernetes.

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

Run the following command to verify the plugin is running:
```
kubectl get pods -n habana-system
```

Step 3: Use Gaudi-enabled Containers

Many Intel Habana environment containers work natively in Domino. To use a custom image to create a new environment, paste the Docker registry path into the FROM field.

vault.habana.ai/gaudi-docker/1.5.0/ubuntu20.04/habanalabs/tensorflow-installer-tf-cpu-2.9.1

See the Habana Developer Catalog for more pre-built container images that can be used in Domino.

Use Intel Habana Accelerators