#Verification

This article describes how to verify that the installed Alauda build of Hami and related monitoring is valid.

#Verify Hami

1. Check whether there are allocatable GPU resources on the GPU node in the control node of the business cluster. Run the following command:

   kubectl get node  ${nodeName} -o=jsonpath='{.status.allocatable}'
   # The output contains: "nvidia.com/gpualloc":"10" (the specific value depends on the number of GPU cards and installation parameters)
2. Deploy a GPU demo instance. Check whether there is any GPU-related resource consumption. Run the following command on the GPU node of the business cluster:

   nvidia-smi pmon -s u -d 1

If both sm and mem contain data, the GPU is ready. You can start developing GPU applications on the GPU node. Note: When deploying GPU applications, be sure to configure the following mandatory parameters:

spec:
  containers:
    - image: your-image
      imagePullPolicy: IfNotPresent
      name: gpu
      resources:
        limits:
          cpu: '2'
          memory: 4Gi
          nvidia.com/gpualloc: 1     # Request 1 physical GPU (required)
          nvidia.com/gpucores: "50"  # Request 50% of the compute resources per GPU (optional)
          nvidia.com/gpumem: 8000    # Request 8000MB of video memory per GPU (optional)

#Verify MonitorDashboard

After the HAMi vgpu service has been running for a while, navigate to Administrator -> Operations Center -> Monitor -> Dashboards page and switch to the HAMi GPU Monitoring panel under Hami. You will see the relevant chart data.

#Verify Hami-WebUI

After HAMi-WebUI components have been running for a while, access http://{business cluster node IP}:NodePort in your browser.