8e15ffe1c7
- Move dspark_deepseekv4_fix_pr_prep.md into experiments/dsv4_h200_dspark/ - Move dsv4_inference_comparison_report.md into docs/ - Delete obsolete cleanup_summary.md - Add experiments/dsv4_h200_vllm/ baseline experiment (envs/vllm + envs/sglang)
DSV4 H200 vLLM Baseline Benchmark
NVIDIA H200 + native vllm + DeepSeek-V4-Flash baseline benchmark experiment.
This experiment uses:
/data/user1/yy/envs/vllmas the server environment/data/user1/yy/envs/sglangas the benchmark client environment
Quick Start
# Run the full experiment (start server + benchmark + parse)
bash experiments/dsv4_h200_vllm/run_bench.sh
# Reuse an already-running server
SKIP_MANAGE_SERVER=1 bash experiments/dsv4_h200_vllm/run_bench.sh
Results land in experiments/dsv4_h200_vllm/results/<RUN_ID>/.
Configuration
Edit config.env or override via environment variables:
MODEL_PATH=/data/models/DeepSeek-V4-Flash \
PORT=30005 \
SCENARIOS="32 512 256 128 512 256" \
bash experiments/dsv4_h200_vllm/run_bench.sh
Files
| File | Purpose |
|---|---|
config.env |
Experiment-level configuration (model, port, venv paths, scenarios) |
start_server.sh |
Start a plain vLLM 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.