[Starlingx-discuss] proposal for Intel GPU K8s device plugin support in StarlingX

[Victor Rodriguez]

On Mon, Jul 15, 2019 at 3:37 AM An, Ran1 <ran1.an at intel.com> wrote:
>
> Hi All
>
>   here is the proposal for enabling intel-gpu-plugin on StarlingX ,  welcome suggestion and advise.
>
>
>
> The background:
>
> As a part of resource management, kubernetes provides a device plugin framework [2] for vendors to advertise their resources to the kubelet since version 1.8. StarlingX has already supported SR-IOV CNI plugins now [3].
>
> Intel-gpu-plugins is a device plugin implementation [4] for intel GPU (with driver i915). Users could deploy their pods with Intel GPU resource requests or limits, if intel-gpu-plugins was integrated into StarlingX.
>

+1

>
>
> proposal:
>
> Deploy intel-gpu-plugins as a daemon set with node selector “intelgpu: enabled”. Kubernetes label “intelgpu: enabled” will be set automatically once the node detected supported GPU device.
>
> Details are shown as follows:
>
> 1.      Build StarlingX plugin docker image based on [5], the implement in starlingx are [6] and [7]
>

ok

> 2.      Deploy Intel-gpu-plugins daemon set in tasks “bringup_kubemaster” after kubernetes master has been initialized during ansible bootstrap process. Add value “import_plugins” and value list “kube_plugins” as condition of deploying Intel-gpu-plugins daemon set, so user could determine whether Intel-gpu-plugins would be enabled. Create file “/etc/platform/enabled_kube_plugins” and write list “kube_plugins” into the file after active Intel-gpu-plugin daemon if “import_plugins” is true. Partical Implement is [8]
>
> 3.      Detect supported GPU device with the help of sysinv agent and request to set kubernetes label “intelgpu: enabled” for specific node by calling sysinv conductor rpcapi. Sysinv conductor will check file “/etc/platform/enabled_kube_plugins”, and set kubernetes label if the file is exist and intel-gpu-plugins is in list. Partial implement is [9]
>

I like the approach and the demo, I just have a question:

One question, what kind of workload support the container running in
the GPU, do we have to write it in cuda? Do we have some example of
source code that will be run inside the container that will run on the
GPU ?

regards

>
>
> [1] https://storyboard.openstack.org/#!/story/2005937
>
> [2] https://kubernetes.io/docs/concepts/extend-kubernetes/compute-storage-net/device-plugins/
>
>       https://github.com/kubernetes/community/blob/master/contributors/design-proposals/resource-management/device-plugin.md
>
> [3] https://review.opendev.org/#/c/655495/
>
> [4] https://github.com/intel/intel-device-plugins-for-kubernetes
>
> [5] https://github.com/intel/intel-device-plugins-for-kubernetes/blob/master/cmd/gpu_plugin/README.md
>
> [6] https://review.opendev.org/668803
>
> [7] https://review.opendev.org/668808
>
> [8] https://review.opendev.org/666510
>
> [9] https://review.opendev.org/666511
>
>
>
> Thanks
>
> Ran
>
>
>
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