perf: [Perf script] QWEN3 30B-A3B tensor_parallel_size from 4 to 2

[youngeunkwon0405]

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Summary by CodeRabbit

• Chores
  • Updated example configuration parameters for GRPO performance optimization scenarios.

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📝 Walkthrough

Walkthrough

A single configuration file in the GRPO Qwen model recipe is updated, reducing the tensor parallelism setting for the vLLM generation backend from 4 to 2. This is a parameter adjustment with no logic changes.

Changes

Cohort / File(s)	Summary
Configuration Adjustment examples/configs/recipes/llm/performance/grpo-qwen3-30ba3b-4n8g.yaml	Reduced generation.vllm_cfg.tensor_parallel_size from 4 to 2

Estimated code review effort

🎯 1 (Trivial) | ⏱️ ~2 minutes

• Minimal change scope: single parameter update in a configuration file

Possibly related PRs

• perf: perf script change for qwen30b-a3b #1526: Modifies the same generation.vllm_cfg.tensor_parallel_size parameter (4 → 2) in the identical configuration file

Suggested reviewers

• guyueh1
• terrykong

Pre-merge checks and finishing touches

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Test Results For Major Changes	⚠️ Warning	PR modifies performance configuration (tensor_parallel_size 4→2) but lacks before-and-after metrics, test results, and workload context required for performance changes.	Add concrete before-and-after performance metrics, hardware/workload configuration, and benchmark evidence demonstrating the optimization improves performance.

✅ Passed checks (3 passed)

Check name	Status	Explanation
Description Check	✅ Passed	Check skipped - CodeRabbit’s high-level summary is enabled.
Title check	✅ Passed	The title clearly and specifically describes the main change: reducing tensor_parallel_size from 4 to 2 in the QWEN3 30B configuration file.
Docstring Coverage	✅ Passed	No functions found in the changed files to evaluate docstring coverage. Skipping docstring coverage check.

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Actionable comments posted: 1

📜 Review details

Configuration used: Path: .coderabbit.yaml

Review profile: CHILL

Plan: Pro

📥 Commits

Reviewing files that changed from the base of the PR and between 1c371a9 and 44fba45.

📒 Files selected for processing (1)

• examples/configs/recipes/llm/performance/grpo-qwen3-30ba3b-4n8g.yaml (1 hunks)

🧰 Additional context used

🧠 Learnings (2)

📓 Common learnings

Learnt from: CR
Repo: NVIDIA-NeMo/RL PR: 0
File: coderabbit-custom-pre-merge-checks-unique-id-file-non-traceable-F7F2B60C-1728-4C9A-8889-4F2235E186CA.txt:0-0
Timestamp: 2025-09-20T14:59:08.052Z
Learning: If a change could affect performance, include before-and-after performance numbers in the PR description, along with configuration and context.

📚 Learning: 2025-10-30T20:50:44.126Z

Learnt from: adil-a
Repo: NVIDIA-NeMo/RL PR: 1440
File: examples/configs/sft_automodel.yaml:48-58
Timestamp: 2025-10-30T20:50:44.126Z
Learning: In DTensor configurations for MoE (Mixture of Experts) models, expert_parallel_size and data_parallel_size can be applied together without multiplying the GPU requirements. Expert Parallelism (EP) only applies to MoE layers, while Data Parallelism/FSDP applies to non-MoE layers. Therefore, configurations like expert_parallel_size: 8 and data_parallel_size: 8 are valid on an 8-GPU cluster for MoE models.

Applied to files:

• examples/configs/recipes/llm/performance/grpo-qwen3-30ba3b-4n8g.yaml

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• GitHub Check: build-container / main
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[youngeunkwon0405]

Hi @terrykong, can I ask for your help to merge this PR?