README.md

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

Verify kubelet socket exists in /var/lib/kubelet/device-plugins/ directory:

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

Deploy GPU device plugin as host process for development purposes

Build GPU device plugin:

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

Run GPU device plugin as administrator:

$ sudo $GOPATH/src/github.com/intel/intel-device-plugins-for-kubernetes/cmd/gpu_plugin/gpu_plugin
device-plugin start server at: /var/lib/kubelet/device-plugins/gpu.intel.com-i915.sock
device-plugin registered

Deploy GPU device plugin as a DaemonSet:

Build plugin image

$ make intel-gpu-plugin

Create plugin DaemonSet

$ kubectl create -f ./deployments/gpu_plugin/gpu_plugin.yaml
daemonset.apps/intel-gpu-plugin created

Verify GPU device plugin is registered on master:

$ kubectl describe node <node name> | grep gpu.intel.com
 gpu.intel.com/i915:  1
 gpu.intel.com/i915:  1

Test GPU device plugin:

1. Build a Docker image with an example program offloading FFT computations to GPU:

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

   This command produces 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. Review the pod's logs:

   $ kubectl logs intelgpu-demo-job-xxxx