# Triton Ascend Case Reduction Amax Medium

> 中等规模归约（amax）优化：计算重组（循环内累加、循环外归约）减少归约次数，grid=40等于核数时性能最优（25.73us），适用于非reduce轴中等、reduce轴较大（千万级元素）的2D归约场景

- Skill: `wenyi-li/triton-ascend-case-reduction-amax-medium` (Agent Skill)
- Install (CLI): `npx skillmds@latest add wenyi-li/triton-ascend-case-reduction-amax-medium`
- Raw SKILL.md: https://api.skillmd.com/api/skills/wenyi-li/triton-ascend-case-reduction-amax-medium/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: wenyi-li (https://skillmd.com/u/wenyi-li)
- Updated: 2026-09-22
- Page: https://skillmd.com/skills/wenyi-li/triton-ascend-case-reduction-amax-medium

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# 中等规模 Amax 归约优化

## 任务特征
- **数据尺寸**：(2048, 8192)，非reduce轴中等，reduce轴较大

## 优化 1：计算重组

```python
# 错误：简单方式：循环内多次归约
row_max = -float('inf')
for n_offset in range(0, N, BLOCK_SIZE):
    curr_max = tl.max(data_block, 1)
    row_max = tl.maximum(curr_max, row_max)

# 正确：优化方式：维护矩阵结构，循环外归约
curr_max = tl.full((BLOCK_SIZE_M, BLOCK_SIZE_N), -float('inf'), dtype=tl.float32)
for n_start in range(0, N, BLOCK_SIZE_N):
    curr_max = tl.maximum(data_block, curr_max)
row_max = tl.max(curr_max, 1)
```

## 优化 2：Grid 配置

```python
# （AI core=40）
# 1. grid=32<40, UB用满 -> 29.05 us
triton.Config({'BLOCK_SIZE_M': 64, 'BLOCK_SIZE_N': 256})

# 2. grid>40, UB用满 -> 29.09 us
triton.Config({'BLOCK_SIZE_M': 32, 'BLOCK_SIZE_N': 512})

# 3. grid=40, UB不超出 -> 25.73 us 最优
triton.Config({'BLOCK_SIZE_M': 52, 'BLOCK_SIZE_N': 256})
```

### 总结
1. 计算重组：将多次归约合并为一次，减少归约次数
2. Grid配置：grid等于核数时性能最优，需确保UB不超出