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

# 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:

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.

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