8b82f700e4
- Add experiments/dsv4_h200_sglang (config, server start, orchestrator, parser, README) - Fix start_server.sh to wait for HTTP 200 via curl --fail instead of treating 503 as ready - Add H200 SGLang baseline to root README and update .gitignore for per-run raw_outputs/logs - Remove stale experiments/dsv4_h200_dspark/DSPARK_FIX_PR_PREP.md
43 lines
1.2 KiB
Markdown
43 lines
1.2 KiB
Markdown
# DSV4 H200 SGLang Baseline Benchmark
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NVIDIA H200 + native `sglang` + `DeepSeek-V4-Flash` baseline benchmark experiment.
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This experiment uses:
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- `/data/user1/yy/envs/sglang` as both the server and benchmark client environment
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## Quick Start
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```bash
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# Run the full experiment (start server + benchmark + parse)
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bash experiments/dsv4_h200_sglang/run_bench.sh
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# Reuse an already-running server
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SKIP_MANAGE_SERVER=1 bash experiments/dsv4_h200_sglang/run_bench.sh
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```
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Results land in `experiments/dsv4_h200_sglang/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 \
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PORT=30006 \
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SCENARIOS=("32 512 256" "128 512 256") \
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bash experiments/dsv4_h200_sglang/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, scenarios) |
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| `start_server.sh` | Start a plain SGLang baseline server for DeepSeek-V4-Flash |
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| `run_bench.sh` | Orchestrator: metadata → server → benchmark → parse |
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| `parse_results.py` | Parse raw JSONL outputs into `results.json` + `report.md` |
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## Platform
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This experiment targets `platforms/nvidia_h200.env`.
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