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 SGLang Baseline Benchmark

NVIDIA H200 + native sglang + DeepSeek-V4-Flash baseline benchmark experiment.

This experiment uses:

/data/user1/yy/envs/sglang as both the server and benchmark client environment

Quick Start

# Run the full experiment (start server + benchmark + parse)
bash experiments/dsv4_h200_sglang/run_bench.sh

# Reuse an already-running server
SKIP_MANAGE_SERVER=1 bash experiments/dsv4_h200_sglang/run_bench.sh

Results land in experiments/dsv4_h200_sglang/results/<RUN_ID>/.

Configuration

Edit config.env or override via environment variables:

MODEL_PATH=/data/models/DeepSeek-V4-Flash \
PORT=30006 \
SCENARIOS=("32 512 256" "128 512 256") \
bash experiments/dsv4_h200_sglang/run_bench.sh

Files

File	Purpose
`config.env`	Experiment-level configuration (model, port, venv paths, scenarios)
`start_server.sh`	Start a plain SGLang baseline server for DeepSeek-V4-Flash
`run_bench.sh`	Orchestrator: metadata → server → benchmark → parse
`parse_results.py`	Parse raw JSONL outputs into `results.json` + `report.md`

Platform

This experiment targets platforms/nvidia_h200.env.

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