docs: record chip/accelerator and inference engine in benchmark workflow

Update BENCHMARK_WORKFLOW.md to require scripts and final outputs to
capture the hardware platform (e.g. NVIDIA H200, Kunlun XPU) and the
inference engine/backend (e.g. vllm-dspark, sglang, vllm-xpu). This
includes directory/file naming conventions, the results.json metadata
schema, and the pre-archive checklist.

BENCHMARK_WORKFLOW.md

@@ -43,7 +43,8 @@
    - The directory may also contain a `README.md` documenting provenance if the report alone does not cover it.
 
 4. **Final JSON must contain raw/structured data, not just summary numbers.**
-   - Metadata: experiment name, timestamp, model, backend, hardware, script path, environment/commit info.
+   - Metadata: experiment name, timestamp, model, backend/inference engine, hardware/accelerator, script path, environment/commit info.
+   - Record the **chip/accelerator** (e.g. `NVIDIA H200`, `Kunlun XPU`) and the **inference engine** (e.g. `vllm-dspark`, `sglang`, `vllm-xpu`) explicitly. Do not infer them from directory names.
    - Per-scenario/per-configuration results: all request latencies, TTFT, TPOT, ITL, token counts, throughput, accept length, success/failure counts.
    - Include P50 / P90 / P95 / P99 percentiles where applicable.
    - Keep the schema stable so downstream Python scripts can parse all experiments uniformly.
@@ -57,6 +58,11 @@
    - `logs/<service>_<timestamp>.log`
    - Keep server logs separate from benchmark result logs.
 
+7. **Scripts and outputs must record chip/accelerator and inference engine.**
+   - Every benchmark script should capture or accept the platform and engine it is running on (e.g. via environment variables `CHIP`, `ACCELERATOR`, `ENGINE`, `BACKEND`, or auto-detection).
+   - Final reports and JSON outputs must include both the accelerator/chip family and the inference engine/backend used for the run.
+   - Do not rely on the experiment name alone to identify the platform or engine.
+
 ## Naming Conventions
 
 ### Result directories
@@ -70,18 +76,27 @@ Examples:
 - `bench_results/dspark_grid_20260707-132641/`
 - `bench_results/dsv4_backend_comparison_20260707/`
 
+When the same experiment is repeated across chips or engines, include them in the directory name or organize by subdirectories so results are not confused:
+
+```
+bench_results/<experiment>_<chip>_<engine>_<YYYYMMDD-HHMMSS>/
+bench_results/<experiment>/<chip>/<engine>/<YYYYMMDD-HHMMSS>/
+```
+
 ### Raw output files
 
+Include the accelerator and inference engine in raw output filenames so files from different platforms cannot overwrite each other.
+
 For detailed per-request JSONL outputs:
 
 ```
-{backend}_{MMDD}_{concurrency}_{input_len}_{output_len}.jsonl
+{chip}_{engine}_{MMDD}_{concurrency}_{input_len}_{output_len}.jsonl
 ```
 
 For summary JSON outputs from `sglang.bench_serving --output-file`:
 
 ```
-{backend}_{scenario}_{params}.json
+{chip}_{engine}_{scenario}_{params}.json
 ```
 
 ### Logs
@@ -105,8 +120,11 @@ The JSON file inside each `bench_results/<run>/` directory should follow a stabl
     "timestamp": "2026-07-07T13:26:41+08:00",
     "model": "/data/models/DeepSeek-V4-Flash-DSpark",
     "backend": "vllm-dspark",
-    "script": "scripts/benchmark_dspark_0707/run_dspark_benchmark_grid.sh",
+    "engine": "vllm-dspark",
     "hardware": "8x NVIDIA H200 143GB",
+    "accelerator": "NVIDIA H200",
+    "chip": "NVIDIA H200",
+    "script": "scripts/benchmark_dspark_0707/run_dspark_benchmark_grid.sh",
     "env": "/data/user1/yy/envs/vllm-dspark",
     "git_commit": "optional git sha",
     "description": "optional free-text note"
@@ -163,6 +181,11 @@ The JSON file inside each `bench_results/<run>/` directory should follow a stabl
 - `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`.
 - Always include **P50 / P90 / P95 / P99** for TTFT, TPOT, E2E, and ITL. P95 is the primary SLO metric.
 - Keep field names snake_case and consistent across experiments.
+- Record hardware and engine information explicitly:
+  - `accelerator` / `chip`: the accelerator family, e.g. `NVIDIA H200`, `Kunlun XPU`, `AMD MI300X`.
+  - `engine` / `backend`: the inference engine or serving backend, e.g. `vllm-dspark`, `sglang`, `vllm-xpu`.
+  - `hardware`: a human-readable full hardware description, e.g. `8x NVIDIA H200 143GB`, `8x Kunlun XPU R480`.
+  - Keep at least one of `accelerator` or `chip`, and at least one of `engine` or `backend`, populated in every run.
 - If a metric is not applicable (e.g. `accept_length` for non-speculative decoding), set it to `null` rather than omitting the key.
 
 ## Quick Start
@@ -199,6 +222,8 @@ bash scripts/benchmark_dsv4_backend_comparison.sh all
 - [ ] All outputs moved to `bench_results/<experiment>_<timestamp>/`.
 - [ ] `bench_results/<run>/report.md` (or equivalent human-readable `.md`) exists.
 - [ ] `bench_results/<run>/results.json` exists and follows the [Final JSON Schema](#final-json-schema).
+- [ ] `bench_results/<run>/results.json` metadata records the `chip`/`accelerator` and `engine`/`backend` used.
+- [ ] Raw output filenames include the chip/accelerator and engine when cross-platform runs may collide.
 - [ ] `bench_results/<run>/README.md` exists and documents provenance (or the report itself covers provenance).
 - [ ] Scripts moved to `scripts/` (or `scripts/<group>/`).
 - [ ] Script path references updated after moving.