Run NCCL AllGather Benchmarks for Model Parallel Validation
Use all-gather NCCL tests to evaluate GPU communication behavior and throughput for tensor-parallel and model-parallel distributed AI workloads on Kubernetes.
π‘ Quick Answer: Execute
all_gather_perf -b 8 -e 1G -f 2 -g 1to validate communication efficiency for model-parallel patterns.
All-gather performance is important for tensor-parallel inference and training pipelines.
Benchmark Command
all_gather_perf -b 8 -e 1G -f 2 -g 1Execution Tips
- Keep pod CPU/memory limits realistic to avoid host bottlenecks.
- Use fixed node placement between runs.
- Run at least 3 iterations and compare averages.
Troubleshooting Signals
- Large variance between runs suggests noisy neighbors or unstable links.
- Sudden drops at specific sizes can indicate MTU or transport fallback issues.
Output to Store
Save logs with node names, GPU count, and NIC interface metadata for trend analysis.

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