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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.

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1. Add node pool and hardware tiers

  1. Create or add a Gaudi-enabled node to an existing node-pool in your Domino cluster.
  2. 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.

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2. Install the Habana Device Plugin for Kubernetes

Prerequisite: Admin kubectl permissions to your cluster
  1. 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
  2. Run the following command to verify the plugin is running: 
    kubectl get pods -n habana-system

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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.
For instance: 
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.