SSKJ Dev a4e38b9e33 Reorganize experiments into hardware-specific subdirectories
Move all experiments under hardware-specific folders:
- experiments/h200/     : H200 GPU experiments (15 dirs)
- experiments/h20/      : H20 GPU experiments (2 dirs)
- experiments/p800/     : Kunlun P800 experiments (3 dirs)
- experiments/pro6000/    : RTX 6000D experiments (2 dirs)

This improves discoverability and keeps hardware-specific configs
isolated from each other.
2026-07-16 04:11:07 +00:00

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# DSV4 H200 DSpark Benchmark
NVIDIA H200 + native `vllm-dspark` + `DeepSeek-V4-Flash-DSpark` benchmark experiment.
This is a migration wrapper: it reuses the proven legacy scripts under
`scripts/benchmark_dspark_0707/` and `scripts/start_dsv4_dspark_8card.sh`,
but stores results in the new `experiments/<name>/results/<RUN_ID>/` layout.
## Quick Start
```bash
# Run the full DSpark P1/P2/P3 grid
bash experiments/dsv4_h200_dspark/run_bench.sh
# Reuse an already-running server
SKIP_MANAGE_SERVER=1 bash experiments/dsv4_h200_dspark/run_bench.sh
```
Results land in `experiments/dsv4_h200_dspark/results/<RUN_ID>/`.
## Configuration
Edit `config.env` or override via environment variables:
```bash
MODEL_PATH=/data/models/DeepSeek-V4-Flash-DSpark \
PORT=30004 \
bash experiments/dsv4_h200_dspark/run_bench.sh
```
## Files
| File | Purpose |
|---|---|
| `config.env` | Experiment-level configuration (model, port, venv paths) |
| `run_bench.sh` | Orchestrator: metadata → legacy grid benchmark → parse |
| `parse_results.py` | Wraps the legacy parser to generate `report.md` |
## Platform
This experiment targets `platforms/nvidia_h200.env`.