Skip to content

Conversation

@krishung5
Copy link
Contributor

@krishung5 krishung5 commented Aug 5, 2025

Overview:

We're seeing an error when running vLLM WideEP after updating DeepGEMM commit:

RuntimeError: Failed: CUDA runtime error csrc/jit/kernel_runtime.hpp:108 '98'

Commit was updated here.

Same error was reported here. Fall back to the previous commit resolved the issue.

Details:

Where should the reviewer start?

Related Issues: (use one of the action keywords Closes / Fixes / Resolves / Relates to)

  • closes GitHub issue: #xxx

Summary by CodeRabbit

  • Chores
    • Updated a dependency to improve compatibility and prevent runtime errors on H100 GPUs.

@copy-pr-bot
Copy link

copy-pr-bot bot commented Aug 5, 2025

This pull request requires additional validation before any workflows can run on NVIDIA's runners.

Pull request vetters can view their responsibilities here.

Contributors can view more details about this message here.

@coderabbitai
Copy link
Contributor

coderabbitai bot commented Aug 5, 2025

Walkthrough

The Dockerfile for the vllm container is updated to pin the DeepGEMM dependency to an earlier commit, specifically before a problematic pull request that caused CUDA runtime errors on H100 GPUs. An explanatory comment is added, with no other changes to the Dockerfile’s structure or functionality.

Changes

Cohort / File(s) Change Summary
Dockerfile Dependency Pin Update
container/Dockerfile.vllm
Updated DeepGEMM commit reference to an earlier version to avoid CUDA errors; added explanatory comment.

Estimated code review effort

🎯 1 (Trivial) | ⏱️ ~2 minutes

Poem

A Docker hop, a version skip,
To dodge a CUDA error blip.
With careful paws, the rabbit pins,
A safer build, the container wins!
No more runtime woes to fear—
Just smooth AI, from ear to ear. 🐇✨

Note

⚡️ Unit Test Generation is now available in beta!

Learn more here, or try it out under "Finishing Touches" below.


Thanks for using CodeRabbit! It's free for OSS, and your support helps us grow. If you like it, consider giving us a shout-out.

❤️ Share
🪧 Tips

Chat

There are 3 ways to chat with CodeRabbit:

  • Review comments: Directly reply to a review comment made by CodeRabbit. Example:
    • I pushed a fix in commit <commit_id>, please review it.
    • Explain this complex logic.
    • Open a follow-up GitHub issue for this discussion.
  • Files and specific lines of code (under the "Files changed" tab): Tag @coderabbitai in a new review comment at the desired location with your query. Examples:
    • @coderabbitai explain this code block.
  • PR comments: Tag @coderabbitai in a new PR comment to ask questions about the PR branch. For the best results, please provide a very specific query, as very limited context is provided in this mode. Examples:
    • @coderabbitai gather interesting stats about this repository and render them as a table. Additionally, render a pie chart showing the language distribution in the codebase.
    • @coderabbitai read src/utils.ts and explain its main purpose.
    • @coderabbitai read the files in the src/scheduler package and generate a class diagram using mermaid and a README in the markdown format.

Support

Need help? Create a ticket on our support page for assistance with any issues or questions.

CodeRabbit Commands (Invoked using PR comments)

  • @coderabbitai pause to pause the reviews on a PR.
  • @coderabbitai resume to resume the paused reviews.
  • @coderabbitai review to trigger an incremental review. This is useful when automatic reviews are disabled for the repository.
  • @coderabbitai full review to do a full review from scratch and review all the files again.
  • @coderabbitai summary to regenerate the summary of the PR.
  • @coderabbitai generate sequence diagram to generate a sequence diagram of the changes in this PR.
  • @coderabbitai resolve resolve all the CodeRabbit review comments.
  • @coderabbitai configuration to show the current CodeRabbit configuration for the repository.
  • @coderabbitai help to get help.

Other keywords and placeholders

  • Add @coderabbitai ignore anywhere in the PR description to prevent this PR from being reviewed.
  • Add @coderabbitai summary to generate the high-level summary at a specific location in the PR description.
  • Add @coderabbitai anywhere in the PR title to generate the title automatically.

Documentation and Community

  • Visit our Documentation for detailed information on how to use CodeRabbit.
  • Join our Discord Community to get help, request features, and share feedback.
  • Follow us on X/Twitter for updates and announcements.

Copy link
Contributor

@coderabbitai coderabbitai bot left a comment

Choose a reason for hiding this comment

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

Actionable comments posted: 0

🧹 Nitpick comments (1)
container/Dockerfile.vllm (1)

20-23: Verify DeepGEMM full commit hash before pinning

I tried git ls-remote but didn’t find a matching 12-char (or longer) SHA for 03d0be3—it only lists refs, not every commit. To guarantee deterministic builds:

  • Replace the 7-char shorthand with the confirmed full commit SHA (at least 12 characters).
  • Double-check that this exact hash exists upstream (e.g. by cloning or fetching the repo and running git rev-parse 03d0be3^{}).

Suggested diff:

-ARG DEEPGEMM_REF="03d0be3"
+ARG DEEPGEMM_REF="<full-commit-sha-for-03d0be3>"

Please confirm the full hash and update accordingly.

📜 Review details

Configuration used: .coderabbit.yaml
Review profile: CHILL
Plan: Pro

📥 Commits

Reviewing files that changed from the base of the PR and between 347620a and eddee3a.

📒 Files selected for processing (1)
  • container/Dockerfile.vllm (1 hunks)
🧰 Additional context used
🧠 Learnings (2)
📓 Common learnings
Learnt from: zaristei
PR: ai-dynamo/dynamo#2020
File: container/deps/vllm/install_vllm.sh:115-118
Timestamp: 2025-07-21T00:10:56.947Z
Learning: Graceful fallback for PyTorch wheel installation is broken on ARM architecture, so immediate exit on pinned version failure is preferred over fallback mechanisms in container/deps/vllm/install_vllm.sh for ARM64.
Learnt from: ptarasiewiczNV
PR: ai-dynamo/dynamo#2027
File: container/deps/vllm/install_vllm.sh:0-0
Timestamp: 2025-07-22T10:22:28.972Z
Learning: The `--torch-backend=auto` flag works with vLLM installations via uv pip install, even though it's not a standard pip option. This flag is processed by vLLM's build system during installation to automatically match PyTorch distribution with container CUDA versions.
📚 Learning: graceful fallback for pytorch wheel installation is broken on arm architecture, so immediate exit on...
Learnt from: zaristei
PR: ai-dynamo/dynamo#2020
File: container/deps/vllm/install_vllm.sh:115-118
Timestamp: 2025-07-21T00:10:56.947Z
Learning: Graceful fallback for PyTorch wheel installation is broken on ARM architecture, so immediate exit on pinned version failure is preferred over fallback mechanisms in container/deps/vllm/install_vllm.sh for ARM64.

Applied to files:

  • container/Dockerfile.vllm
⏰ Context from checks skipped due to timeout of 90000ms. You can increase the timeout in your CodeRabbit configuration to a maximum of 15 minutes (900000ms). (1)
  • GitHub Check: Build and Test - vllm

@krishung5
Copy link
Contributor Author

/ok to test eddee3a

@alec-flowers alec-flowers merged commit ef2b0e6 into main Aug 6, 2025
12 of 13 checks passed
@alec-flowers alec-flowers deleted the krish/revert-depgemm-commit branch August 6, 2025 00:07
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Projects

None yet

Development

Successfully merging this pull request may close these issues.

3 participants