Feature Request: GPU Support

[ZongqiangZhang]

This feature request aims to enhance the Node Problem Detector with the ability to monitor GPUs on nodes and detect issues.

Currently NPD does not have direct visibility into GPUs. However, many workloads are GPU accelerated which makes GPU health an important part of node health. e.g. GPUs are widely used in machine learning training and inference. Especially for LLM training which may using tens of thousands of GPU cards. The entire training cluster should be restarted from previous checkpoint if any one of the GPUs in the cluster is gone bad.

This feature request adds the following capabilities:

• GPU device monitoring: NPD will collect GPU device info periodically and look for crashes or errors via nvidia-smi/nvml/dcgm tools.

• GPU device monitoring: NPD will check GPU device info periodically to detect if a GPU is "stuck" (e.g. nvidia-smi command hangs).

• TBD: GPU runtime monitoring: NPD will check for crashes or OOM issues reported in nvidia logs.

Specifically, this feature request includes:

• Code for the gpu_monitor plugin
• A Dockerfile to build an NPD image with GPU support
• Other dependencies

Looking forward to your feedback!

[k8s-triage-robot]

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/lifecycle stale

[k8s-triage-robot]

The Kubernetes project currently lacks enough active contributors to adequately respond to all issues.

This bot triages un-triaged issues according to the following rules:

• After 90d of inactivity, lifecycle/stale is applied
• After 30d of inactivity since lifecycle/stale was applied, lifecycle/rotten is applied
• After 30d of inactivity since lifecycle/rotten was applied, the issue is closed

You can:

• Mark this issue as fresh with /remove-lifecycle rotten
• Close this issue with /close
• Offer to help out with Issue Triage

Please send feedback to sig-contributor-experience at kubernetes/community.

/lifecycle rotten

[zz913922]

Exactly the same situation, did you resolve this issue already?

[stmcginnis]

/remove-lifecycle stale

[stmcginnis]

/remove-lifecycle rotten

[AllenXu93]

I think NPD should support different config for different device or runtime;
For example , I have both GPU and none GPU worker node in one cluster, or containerd and docker nodes in one cluster; currently we need to deploy 2 npd daemonset for different type of node;

[AllenXu93]

BTW, for GPU, we don't need to install more dependencies, it just add env NVIDIA_VISIBLE_DEVICES and NVIDIA_DRIVER_CAPABILITIES , and use nvidia-smi command to check GPU state

[wangzhen127]

Thanks for filing the feature request! I think this totally makes sense. Do you have any more concrete proposal?

/cc @SergeyKanzhelev

[SergeyKanzhelev]

yes, accelerators health is an important functionality and would be great to have it in NPD

Need to design it carefully though. There is already some health checking in a device plugin (like https://github.com/NVIDIA/k8s-device-plugin/blob/bf58cc405af03d864b1502f147815d4c2271ab9a/internal/rm/health.go#L39) that we need to work nicely with. Even simple detection of a device plugin health is a good starting point here.

@AllenXu93 @ZongqiangZhang do you want to work on more detailed design? I definitely will be interested to join the effort

[wangzhen127]

/kind feature