Chapter 3. AMD GPU Operator

Next steps

1. Install the Node Feature Discovery Operator.
2. Install the Kernel Module Management Operator.
3. Install and configure the AMD GPU Operator.

Procedure

1. Create a YAML file that tests ROCmInfo:

   $ cat << EOF > rocminfo.yaml
   
   apiVersion: v1
   kind: Pod
   metadata:
    name: rocminfo
   spec:
    containers:
    - image: docker.io/rocm/pytorch:latest
      name: rocminfo
      command: ["/bin/sh","-c"]
      args: ["rocminfo"]
      resources:
       limits:
         amd.com/gpu: 1
       requests:
         amd.com/gpu: 1
    restartPolicy: Never
   EOF

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2. Create the rocminfo pod:

   $ oc create -f rocminfo.yaml

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   Example output

   apiVersion: v1
   pod/rocminfo created

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3. Check the rocmnfo log with one MI210 GPU:

   $ oc logs rocminfo | grep -A5 "Agent"

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   Example output

   HSA Agents
   ==========
   *******
   Agent 1
   *******
     Name:                    Intel(R) Xeon(R) Gold 6330 CPU @ 2.00GHz
     Uuid:                    CPU-XX
     Marketing Name:          Intel(R) Xeon(R) Gold 6330 CPU @ 2.00GHz
     Vendor Name:             CPU
   --
   Agent 2
   *******
     Name:                    Intel(R) Xeon(R) Gold 6330 CPU @ 2.00GHz
     Uuid:                    CPU-XX
     Marketing Name:          Intel(R) Xeon(R) Gold 6330 CPU @ 2.00GHz
     Vendor Name:             CPU
   --
   Agent 3
   *******
     Name:                    gfx90a
     Uuid:                    GPU-024b776f768a638b
     Marketing Name:          AMD Instinct MI210
     Vendor Name:             AMD

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4. Delete the pod:

   $ oc delete -f rocminfo.yaml

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   Example output

   pod "rocminfo" deleted

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