This reposity holds instructions for configuring GPU acclerated Windows nodes in AKS clusters

1. Create an AKS cluster following https://docs.microsoft.com/en-us/azure/aks/learn/quick-windows-container-deploy-cli#create-an-aks-cluster

2. Add a Windows Server node pool following https://learn.microsoft.com/en-us/azure/aks/learn/quick-windows-container-deploy-cli#add-a-windows-node-pool

   Notes:

   1. kubernetes version must be 1.23 or later

   2. node-vm-size should be a NV* series which support DirectX acceleration. [https://docs.microsoft.com/en-us/azure/virtual-machines/sizes-gpu]

3. Add the 'NVDIA GPU Driver Extension' to the VirtualMachineScaleSet created for the new node pool added above

   https://docs.microsoft.com/en-us/azure/virtual-machines/extensions/hpccompute-gpu-windows

   https://docs.microsoft.com/en-us/cli/azure/vmss/extension?view=azure-cli-latest

4. Ensure VirtualMachineScaleSet instances are using the most up-to-date model

   https://docs.microsoft.com/en-us/azure/virtual-machine-scale-sets/virtual-machine-scale-sets-upgrade-scale-set#how-to-bring-vms-up-to-date-with-the-latest-scale-set-model

5. Wait for VM extensions to run

6. Deploy `k8s-directx-device-plugin.yaml to your cluster

   kubectl apply -f https://raw.githubusercontent.com/marosset/aks-windows-gpu-acceleration/main/k8s-directx-device-plugin/k8s-directx-device-plugin.yaml

1. run kubectl describe node {gpu-node} and look for

   Capacity:
       cpu:                    6
       ephemeral-storage:      133703676Ki
       memory:                 58719796Ki
       microsoft.com/directx:  1
       pods:                   30
   Allocatable:
       cpu:                    5840m
       ephemeral-storage:      133703676Ki
       memory:                 51379764Ki
       microsoft.com/directx:  1
       pods:                   30

1. In your workload deployment files add requests for 'microsoft.com/directx` resoruces

   ...
   spec:
     containers:
   ...
       resources:
         requests:
           microsoft.com/directx: "1"

1. Ensure daemonSet pods are running

   Check status with

   kubectl get pods -A

2. Check device plugin pod logs

   kubectl logs -n kube-system {pod-name}

   You should see something like

   kubectl logs -n kube-system directx-device-plugin-5t7dc
   ERROR: logging before flag.Parse: I0505 19:10:39.046785    5076 main.go:98] GPU NVIDIA Tesla M60 id: PCI\VEN_10DE&DEV_13F2&SUBSYS_115E10DE&REV_A1\6&2B78CA89&0&0
   ERROR: logging before flag.Parse: W0505 19:10:39.096589    5076 main.go:90] 'Microsoft Hyper-V Video' doesn't match  'nvidia', ignoring this gpu
   ERROR: logging before flag.Parse: I0505 19:10:39.096589    5076 main.go:101] pluginSocksDir: /var/lib/kubelet/device-plugins/
   ERROR: logging before flag.Parse: I0505 19:10:39.096589    5076 main.go:103] socketPath: /var/lib/kubelet/device-plugins/directx.sock
   2022/05/05 19:10:40 Starting to serve on /var/lib/kubelet/device-plugins/directx.sock
   2022/05/05 19:10:40 Deprecation file not found. Invoke registration
   2022/05/05 19:10:40 ListAndWatch