docs: 规范 benchmark 结果存储格式,要求每个实验同时产出 .md 报告和结构化 results.json
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- Logs go in `logs/`.
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- Reports (e.g. `report.md`, `comparison_report.md`) go in the run root.
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3. **Each `bench_results/<run>/` directory must contain a `README.md`.**
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- What was benchmarked.
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- Which script(s) produced the outputs.
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- File naming convention.
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- Inventory of outputs (table).
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3. **Each `bench_results/<run>/` directory must contain two final artifacts.**
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- A Markdown report for human reading (e.g. `report.md`, `comparison_report.md`).
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- A JSON file with the complete structured result data for programmatic analysis (e.g. `results.json`).
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- The directory may also contain a `README.md` documenting provenance if the report alone does not cover it.
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4. **Scripts should default `RESULT_ROOT` to `bench_results/<experiment>_${RUN_ID}`.**
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4. **Final JSON must contain raw/structured data, not just summary numbers.**
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- Metadata: experiment name, timestamp, model, backend, hardware, script path, environment/commit info.
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- Per-scenario/per-configuration results: all request latencies, TTFT, TPOT, ITL, token counts, throughput, accept length, success/failure counts.
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- Include P50 / P90 / P95 / P99 percentiles where applicable.
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- Keep the schema stable so downstream Python scripts can parse all experiments uniformly.
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- See [Final JSON Schema](#final-json-schema) below for the recommended structure.
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5. **Scripts should default `RESULT_ROOT` to `bench_results/<experiment>_${RUN_ID}`.**
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- Allow override via `RESULT_ROOT` env var.
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- Use `RUN_ID=$(date '+%Y%m%d-%H%M%S')` unless specified.
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5. **Server start scripts write to `logs/`.**
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6. **Server start scripts write to `logs/`.**
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- `logs/<service>_<timestamp>.log`
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- Keep server logs separate from benchmark result logs.
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@ -85,6 +91,80 @@ logs/<service>_YYYYMMDD_HHMMSS.log
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logs/<experiment>_orchestrator_YYYYMMDD_HHMMSS.log
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```
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## Final JSON Schema
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The JSON file inside each `bench_results/<run>/` directory should follow a stable schema so that downstream Python scripts can load every experiment the same way. The file is usually named `results.json`.
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### Required top-level fields
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```json
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{
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"metadata": {
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"experiment": "dspark_grid",
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"run_id": "20260707-132641",
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"timestamp": "2026-07-07T13:26:41+08:00",
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"model": "/data/models/DeepSeek-V4-Flash-DSpark",
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"backend": "vllm-dspark",
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"script": "scripts/benchmark_dspark_0707/run_dspark_benchmark_grid.sh",
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"hardware": "8x NVIDIA H200 143GB",
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"env": "/data/user1/yy/envs/vllm-dspark",
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"git_commit": "optional git sha",
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"description": "optional free-text note"
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},
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"config": {
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"tp": 8,
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"kv_cache_dtype": "fp8",
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"spec_method": "dspark",
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"spec_tokens": 5,
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"block_size": 256,
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"max_num_seqs": 256,
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"extra_args": "--no-disable-hybrid-kv-cache-manager"
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},
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"scenarios": [
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{
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"name": "chat_short",
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"concurrency": 64,
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"input_len": 1000,
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"output_len": 256,
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"duration_s": 21.27,
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"success": 512,
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"failed": 0,
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"request_throughput": 24.07,
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"input_token_throughput": 6391.14,
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"output_token_throughput": 3189.39,
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"total_token_throughput": 9580.52,
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"accept_length": 3.2,
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"latencies": {
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"e2e_ms": { "mean": 2547.81, "p50": 2400.0, "p90": 4800.0, "p95": 5606.07, "p99": 6543.97 },
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"ttft_ms": { "mean": 268.68, "p50": 240.0, "p90": 480.0, "p95": 543.21, "p99": 588.63 },
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"tpot_ms": { "mean": 18.24, "p50": 16.0, "p90": 28.0, "p95": 30.39, "p99": 39.57 },
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"itl_ms": { "mean": 70.29, "p50": 60.0, "p90": 110.0, "p95": 130.0, "p99": 160.0 }
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},
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"raw_requests": [
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{
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"request_id": "uuid-or-index",
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"input_tokens": 1000,
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"output_tokens": 256,
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"e2e_ms": 2500.0,
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"ttft_ms": 260.0,
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"tpot_ms": 18.0,
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"itl_ms": 70.0,
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"accept_length": 3.0,
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"success": true
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}
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]
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}
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]
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}
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```
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### Notes
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- `raw_requests` is optional but recommended when the JSON size is manageable. If a single run produces millions of requests, store per-request data as `raw_outputs/*.jsonl` and keep only aggregated percentiles in `results.json`.
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- Always include **P50 / P90 / P95 / P99** for TTFT, TPOT, E2E, and ITL. P95 is the primary SLO metric.
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- Keep field names snake_case and consistent across experiments.
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- If a metric is not applicable (e.g. `accept_length` for non-speculative decoding), set it to `null` rather than omitting the key.
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## Quick Start
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### Run DSpark grid benchmark
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@ -117,6 +197,8 @@ bash scripts/benchmark_dsv4_backend_comparison.sh all
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- [ ] No `.jsonl`, `.json`, `.log`, or `.md` files left in `/data/user1/yy/` root.
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- [ ] All outputs moved to `bench_results/<experiment>_<timestamp>/`.
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- [ ] `bench_results/<run>/README.md` exists and documents provenance.
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- [ ] `bench_results/<run>/report.md` (or equivalent human-readable `.md`) exists.
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- [ ] `bench_results/<run>/results.json` exists and follows the [Final JSON Schema](#final-json-schema).
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- [ ] `bench_results/<run>/README.md` exists and documents provenance (or the report itself covers provenance).
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- [ ] Scripts moved to `scripts/` (or `scripts/<group>/`).
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- [ ] Script path references updated after moving.
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@ -7,7 +7,7 @@
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| 目录/文件 | 说明 |
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|---|---|
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| `scripts/` | 所有 benchmark 脚本、服务启动脚本、结果解析脚本 |
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| `bench_results/` | 各次实验的最终报告与 summary JSON |
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| `bench_results/` | 各次实验的最终产物:人可读 `.md` 报告 + 结构化 `results.json`(含原始数据与分位统计) |
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| `BENCHMARK_WORKFLOW.md` | benchmark 目录与命名规范 |
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| `scripts/SLO_STANDARDS.md` | 推理服务 SLO 标准(TTFT/TPOT) |
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