Skip to content

Concurrency on custom nvidia runners #397

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
msaroufim merged 2 commits into from
Jan 13, 2026
Merged

Concurrency on custom nvidia runners #397

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
6c40351
Concurrency on custom nvidia runners
msaroufim Jan 13, 2026
27e3483
update
msaroufim Jan 13, 2026
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
6 changes: 5 additions & 1 deletion .github/workflows/nvidia_workflow.yml
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -15,11 +15,15 @@ on:
required: false
type: string

concurrency:
group: nvidia-workflow-global
cancel-in-progress: false
Comment on lines +18 to +20
Copy link

Copilot AI Jan 13, 2026

Choose a reason for hiding this comment

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

The workflow-level concurrency group 'nvidia-workflow-global' will queue all workflow runs globally, which may defeat the purpose of having 8 separate runners. Since the goal is to distribute work across multiple runners, consider using a per-runner concurrency group or removing workflow-level concurrency entirely. A better approach would be to set concurrency at the job level with a dynamic group name like 'nvidia-workflow-${{ needs.select-runner.outputs.runner }}' to allow parallel runs on different GPUs while preventing concurrent runs on the same GPU.

Copilot uses AI. Check for mistakes.

run-name: 'NVIDIA Job - ${{ github.event.inputs.run_id }}'

jobs:
run:
runs-on: [nvidia-docker-b200-8-x86-64]
runs-on: nvidia-docker-b200-8-x86-64
timeout-minutes: 10
steps:
- uses: actions/checkout@v3
Expand Down
Loading