# FlagOS S2 提交 PR 模板(给队长孙蓓)

> 复制下面这块,直接贴到 GitHub PR 描述里

```markdown
## What

Optimized `[算子名]` operator for FlagOS Open Computing Challenge S2 - Track 1.

Baseline: `FlagOpen/FlagGems/[原文件路径]`
This PR: `FlagOpen/FlagGems/[新文件路径]`

## Why

The baseline uses `[默认配置 / sequential for-loop / fixed num_warps]`.
This PR adds `[autotune / 2D grid / 3D grid / 头维并行]` to extract
additional `[1.X% / X 倍]` speedup.

## How

1. Added `triton.autotune` over `(BLOCK_SIZE, num_warps, num_stages)` with N configs
2. Restructured grid from `[1D / 2D]` to `[2D / 3D]` for `[维度]` parallelization
3. Constexpr inlined `[常量]` for `[省 Python→Triton 转换 / 减少指令]`

## Benchmarks

```
shape         baseline(ms)   v2(ms)     speedup
[B, S, H, D]   X.XXXX         X.XXXX     X.XXx
```

GPU: NVIDIA A100 80GB
Triton: 3.0.0
PyTorch: 2.3.0
FlagGems: master @ commit [hash]

## Tests

- [x] Numerical correctness vs PyTorch reference (max abs_diff < 1e-2)
- [x] Numerical correctness vs FlagGems baseline (max abs_diff < 1e-2)
- [x] Tested on fp16 / bf16 / fp32
- [x] Tested on multiple shapes

## Team

GuanghuLab · 孙蓓(队长)· 9478_apiqttc · 陈淑婷 · 4348_apiratk · 8592_apivqhj
```

---

# flagos.net 平台提交模板

```
参赛赛道: 赛道一 · SGLang 框架算子在多款芯片的性能优化
赛题编号: Task XX
赛题名称: [算子名]
GitHub PR: https://github.com/FlagOpen/FlagGems/pull/XXX
提交说明:
- 团队:GuanghuLab
- 优化要点:[2-3 行说明]
- 加速比:[X.XX×]
- 测试设备:[NVIDIA A100 80GB / 国产 XX 芯片]
- 备注:[可选:跑了哪些 shape,dtype 等]
```