Skip to content

[release-1.13] Fix gpu resource error - #4916

Merged
JesseStutler merged 1 commit into
volcano-sh:release-1.13from
volcano-sh-bot:cherry-pick-4873-to-release-1.13
Jan 6, 2026
Merged

[release-1.13] Fix gpu resource error#4916
JesseStutler merged 1 commit into
volcano-sh:release-1.13from
volcano-sh-bot:cherry-pick-4873-to-release-1.13

Conversation

@volcano-sh-bot

Copy link
Copy Markdown
Contributor

This is an automated cherry-pick of #4873


…aringPredicateAndScore will add the used mem/core to the structure. For avoiding the pod allocated info updating latency, we use addResource it to add the pod the pod map. But it also add the used mem/core. To address this, we new a function that only add pod the map.

Signed-off-by: chenw66 <chenw66@chinaunicom.cn>
@gemini-code-assist

Copy link
Copy Markdown

Summary of Changes

Hello @volcano-sh-bot, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request, which is an automated cherry-pick, addresses a GPU resource error by refining the mechanism for tracking GPU usage per pod. It introduces a dedicated function, addToPodMap, to accurately record allocated memory and core usage for each GPU device associated with a pod during the allocation process, replacing an older, potentially problematic method. This change aims to ensure more reliable and precise management of GPU resources within the scheduler.

Highlights

  • New GPU Resource Mapping Function: A new function, addToPodMap, has been introduced to explicitly handle the mapping of allocated GPU resources (memory and cores) to individual pods based on annotations.
  • Refactored Resource Allocation Logic: The Allocate function now utilizes the newly introduced addToPodMap function instead of the previous addResource function to update GPU usage statistics for pods during the allocation process.
  • Improved GPU Resource Tracking: This change ensures that UsedMem and UsedCore are accurately updated within the PodMap of each GPU device, leading to more reliable tracking of GPU resource consumption by pods.

🧠 New Feature in Public Preview: You can now enable Memory to help Gemini Code Assist learn from your team's feedback. This makes future code reviews more consistent and personalized to your project's style. Click here to enable Memory in your admin console.

Using Gemini Code Assist

The full guide for Gemini Code Assist can be found on our documentation page, here are some quick tips.

Invoking Gemini

You can request assistance from Gemini at any point by creating a comment using either /gemini <command> or @gemini-code-assist <command>. Below is a summary of the supported commands on the current page.

Feature Command Description
Code Review /gemini review Performs a code review for the current pull request in its current state.
Pull Request Summary /gemini summary Provides a summary of the current pull request in its current state.
Comment @gemini-code-assist Responds in comments when explicitly tagged, both in pull request comments and review comments.
Help /gemini help Displays a list of available commands.

Customization

To customize Gemini Code Assist for GitHub experience, repository maintainers can create a configuration file and/or provide a custom code review style guide (such as PEP-8 for Python) by creating and adding files to a .gemini/ folder in the base of the repository. Detailed instructions can be found here.

Limitations & Feedback

Gemini Code Assist may make mistakes. Please leave feedback on any instances where its feedback is incorrect or counter productive. You can react with 👍 and 👎 on @gemini-code-assist comments. If you're interested in giving your feedback about your experience with Gemini Code Assist for Github and other Google products, sign up here.

You can also get AI-powered code generation, chat, as well as code reviews directly in the IDE at no cost with the Gemini Code Assist IDE Extension.

Footnotes

  1. Review the Privacy Notices, Generative AI Prohibited Use Policy, Terms of Service, and learn how to configure Gemini Code Assist in GitHub here. Gemini can make mistakes, so double check it and use code with caution.

@volcano-sh-bot volcano-sh-bot added the size/M Denotes a PR that changes 30-99 lines, ignoring generated files. label Jan 6, 2026

@gemini-code-assist gemini-code-assist Bot left a comment

Copy link
Copy Markdown

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Code Review

This pull request aims to fix a GPU resource error by introducing a new function, addToPodMap, to handle optimistic resource updates during allocation. While the intent is good, the new function has several issues. I've identified a critical flaw that could lead to GPU overcommitment, a high-severity risk of resource miscounting, and a minor logging issue. My review provides a single, comprehensive comment with a suggested rewrite of the function to address all these points, ensuring resource accounting is correct and robust.

Comment on lines +209 to +235
func (gs *GPUDevices) addToPodMap(annotations map[string]string, pod *v1.Pod) {
ids, ok := annotations[AssignedIDsAnnotations]
if !ok {
klog.Errorf("pod %s has no annotation volcano.sh/devices-to-allocate", pod.Name)
return
}
podDev := decodePodDevices(ids)
for _, val := range podDev {
for _, deviceused := range val {
for _, gsdevice := range gs.Device {
if strings.Contains(deviceused.UUID, gsdevice.UUID) {
podUID := string(pod.UID)
_, ok := gsdevice.PodMap[podUID]
if !ok {
gsdevice.PodMap[podUID] = &GPUUsage{
UsedMem: 0,
UsedCore: 0,
}
}

gsdevice.PodMap[podUID].UsedMem += deviceused.Usedmem
gsdevice.PodMap[podUID].UsedCore += deviceused.Usedcores
}
}
}
}
}

Copy link
Copy Markdown

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

critical

This new function has a few issues that should be addressed:

  1. Critical: It only updates the PodMap but not the summary fields like UsedMem and UsedCore on the gsdevice. This can lead to stale resource usage data within a scheduling session, potentially causing overcommitment of GPU resources as subsequent scheduling decisions will not see the updated usage.
  2. High: The inner loop over gs.Device does not break after finding a match. A single allocated device should belong to exactly one physical GPU. Without a break, its usage might be counted on multiple physical devices if UUIDs are not perfectly distinct, leading to incorrect resource accounting.
  3. Medium: The error message on line 212 is misleading. It refers to volcano.sh/devices-to-allocate, but the code checks for volcano.sh/vgpu-ids-new (AssignedIDsAnnotations).

I'm providing a single suggestion that refactors the function to fix all three issues.

func (gs *GPUDevices) addToPodMap(annotations map[string]string, pod *v1.Pod) {
	ids, ok := annotations[AssignedIDsAnnotations]
	if !ok {
		klog.Errorf("pod %s has no annotation %s", pod.Name, AssignedIDsAnnotations)
		return
	}
	podDev := decodePodDevices(ids)
	for _, val := range podDev {
		for _, deviceused := range val {
			for _, gsdevice := range gs.Device {
				if strings.Contains(deviceused.UUID, gsdevice.UUID) {
					podUID := string(pod.UID)
					if _, ok := gsdevice.PodMap[podUID]; !ok {
						gsdevice.PodMap[podUID] = &GPUUsage{
							UsedMem:  0,
							UsedCore: 0,
						}
					}

					gsdevice.PodMap[podUID].UsedMem += deviceused.Usedmem
					gsdevice.PodMap[podUID].UsedCore += deviceused.Usedcores
					gsdevice.UsedMem += deviceused.Usedmem
					gsdevice.UsedCore += deviceused.Usedcores
					break
				}
			}
		}
	}
}

@JesseStutler

Copy link
Copy Markdown
Member

/approve
/lgtm

@volcano-sh-bot volcano-sh-bot added the lgtm Indicates that a PR is ready to be merged. label Jan 6, 2026
@volcano-sh-bot

Copy link
Copy Markdown
Contributor Author

[APPROVALNOTIFIER] This PR is NOT APPROVED

This pull-request has been approved by: JesseStutler
Once this PR has been reviewed and has the lgtm label, please assign k82cn for approval. For more information see the Kubernetes Code Review Process.

The full list of commands accepted by this bot can be found here.

Details Needs approval from an approver in each of these files:

Approvers can indicate their approval by writing /approve in a comment
Approvers can cancel approval by writing /approve cancel in a comment

@JesseStutler
JesseStutler merged commit 87bf5de into volcano-sh:release-1.13 Jan 6, 2026
14 of 15 checks passed
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Labels

lgtm Indicates that a PR is ready to be merged. size/M Denotes a PR that changes 30-99 lines, ignoring generated files.

Projects

None yet

Development

Successfully merging this pull request may close these issues.

2 participants