Concurrency on custom nvidia runners

[msaroufim]

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[github-actions]

Coverage report

This PR does not seem to contain any modification to coverable code.

[Copilot]

Pull request overview

This PR adds concurrency control and dynamic runner selection to the NVIDIA workflow to distribute jobs across multiple GPU runners. The changes implement a round-robin distribution strategy based on the GitHub run number to select from 8 available GPU runners.

Changes:

• Added workflow-level concurrency configuration with a global group
• Introduced a new select-runner job that dynamically picks one of 8 GPU runners using round-robin selection
• Updated the run job to use the dynamically selected runner label

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[Copilot]

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.