intel-device-plugins-for-kubernetes/cmd/gpu_plugin

Build and test Intel GPU Device Plugin for Kubernetes

Get source code

$ mkdir -p $GOPATH/src/github.com/intel/
$ cd $GOPATH/src/github.com/intel/
$ git clone https://github.com/intel/intel-device-plugins-for-kubernetes.git

Build GPU device plugin

$ cd $GOPATH/src/github.com/intel/intel-device-plugins-for-kubernetes
$ make gpu_plugin

Make sure kubelet socket exists in /var/lib/kubelet/device-plugins/

$ ls /var/lib/kubelet/device-plugins/kubelet.sock
/var/lib/kubelet/device-plugins/kubelet.sock

Run GPU device plugin as administrator

$ sudo $GOPATH/src/github.com/intel/intel-device-plugins-for-kubernetes/cmd/gpu_plugin/gpu_plugin
GPU device plugin started
Adding '/dev/dri/card0' to GPU 'card0'
Adding '/dev/dri/controlD64' to GPU 'card0'
Adding '/dev/dri/renderD128' to GPU 'card0'
device-plugin start server at: /var/lib/kubelet/device-plugins/intelGPU.sock
device-plugin registered
device-plugin: ListAndWatch start
ListAndWatch: send devices &ListAndWatchResponse{Devices:[&Device{ID:card0,Health:Healthy,}],}

Check if GPU device plugin is registered on master

$ kubectl describe node <node name> | grep intel.com/gpu
 intel.com/gpu:  1
 intel.com/gpu:  1

Test GPU device plugin

1. Build a Docker image with beignet unit tests:

   $ cd demo
   $ ./build-image.sh ubuntu-demo-opencl
   

   This command will produce a Docker image named ubuntu-demo-opencl.

2. Create a pod running unit tests off the local Docker image:

   $ kubectl apply -f demo/intelgpu_job.yaml
   

3. Observe the pod's logs:

   $ kubectl logs intelgpu-demo-job-xxxx