a5d69dfd9a
- Update platforms/nvidia_h200.env with ENGINE and configurable venv/paths. - Update platforms/README.md with H200 notes and platform-addition guide. - Add docs/H200_QUICKSTART.md with concrete H200 usage steps. - Add experiments/dsv4_h200_dspark/ as a migration wrapper around the existing scripts/benchmark_dspark_0707/ grid benchmark, writing results into the new experiments/<name>/results/<RUN_ID>/ layout. - Update BENCHMARK_WORKFLOW.md with a 'Adding a New Platform or Experiment' section and mention the H200 wrapper in Quick Start. - Update main README.md to index the H200 experiment and link to the guide.
42 lines
1.1 KiB
Markdown
42 lines
1.1 KiB
Markdown
# DSV4 H200 DSpark Benchmark
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NVIDIA H200 + native `vllm-dspark` + `DeepSeek-V4-Flash-DSpark` benchmark experiment.
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This is a migration wrapper: it reuses the proven legacy scripts under
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`scripts/benchmark_dspark_0707/` and `scripts/start_dsv4_dspark_8card.sh`,
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but stores results in the new `experiments/<name>/results/<RUN_ID>/` layout.
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## Quick Start
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```bash
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# Run the full DSpark P1/P2/P3 grid
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bash experiments/dsv4_h200_dspark/run_bench.sh
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# Reuse an already-running server
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SKIP_MANAGE_SERVER=1 bash experiments/dsv4_h200_dspark/run_bench.sh
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```
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Results land in `experiments/dsv4_h200_dspark/results/<RUN_ID>/`.
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## Configuration
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Edit `config.env` or override via environment variables:
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```bash
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MODEL_PATH=/data/models/DeepSeek-V4-Flash-DSpark \
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PORT=30004 \
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bash experiments/dsv4_h200_dspark/run_bench.sh
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```
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## Files
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| File | Purpose |
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|---|---|
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| `config.env` | Experiment-level configuration (model, port, venv paths) |
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| `run_bench.sh` | Orchestrator: metadata → legacy grid benchmark → parse |
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| `parse_results.py` | Wraps the legacy parser to generate `report.md` |
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## Platform
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This experiment targets `platforms/nvidia_h200.env`.
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