triton-ascend-case-reduction-amin-medium

triton-ascend-case-reduction-amin-medium is a skill for Claude Code, Codex from mindspore-ai/akg. It costs 91 tokens per session (541 once invoked), scanned A, original, Apache-2.0.

A Triton optimization guide for finding row minimums in a large two-dimensional array on Ascend hardware. It handles cases where the dimension being reduced contains hundreds of thousands of elements.

In plain words
What is it for?
Use it to optimize 2D `amin` operations with a medium-sized row dimension and a very large reduction dimension, such as a 2,048 by 262,144 array.
Why use it?
It reduces repeated reduction work and limits each operation to a manageable hardware-buffer size. Larger chunks along the reduced dimension can also reduce loop iterations.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to optimize 2D amin operations with a medium-sized row dimension and a very large reduction dimension, such as a 2,048 by 262,144 array.

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Install with agentmods
npx agentmods add skills/mindspore-ai/akg/triton-ascend-case-reduction-amin-medium
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add mindspore-ai/akg --skill triton-ascend-case-reduction-amin-medium
Clone the repo
git clone --depth 1 https://github.com/mindspore-ai/akg

Made for: Claude Code, Codex.

Wrote this? Show the measurements

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README.md
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Your own site · 80×15
<a href="https://agentmods.dev/skills/mindspore-ai/akg/triton-ascend-case-reduction-amin-medium"><img src="https://agentmods.dev/badge/skills/mindspore-ai/akg/triton-ascend-case-reduction-amin-medium.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 91 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 541 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00091 $0.00541
Opus 5 $0.00046 $0.00270
Sonnet 5 $0.00018 $0.00108
Haiku 4.5 $0.00009 $0.00054

Measured 9d ago against content hash 7a30ccf9c3a6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

triton-ascend-case-reduction-amin-medium scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

akg_agents/python/akg_agents/op/resources/skills/triton-ascend/cases/triton-ascend-case-reduction-amin-medium/SKILL.md · 47 lines

What it actually says

大规模 2D Amin 归约优化

任务特征

  • 数据尺寸:(2048, 262144),非reduce轴中等,reduce轴很大

优化:reduce轴大切分

# 错误:简单:循环内多次归约
row_min = float('inf')
for n_start in range(0, N, BLOCK_SIZE_N):
    curr_min = tl.min(data_block, 1)
    row_min = tl.minimum(curr_min, row_min)

# 正确:优化:维护矩阵结构
curr_min = tl.full((BLOCK_SIZE_M, BLOCK_SIZE_N), float('inf'), dtype=tl.float32)
for n_start in range(0, N, BLOCK_SIZE_N):
    curr_min = tl.minimum(data_block, curr_min)
row_min = tl.min(curr_min, 1)

Autotune 配置

# 1. reduce轴切分较大, UB用满 -> 2864.90 us
triton.Config({'BLOCK_SIZE_M': 8, 'BLOCK_SIZE_N': 2048})

# 2-4. reduce轴切分逐渐增大,M切分相应减小 -> 性能逐渐提升
triton.Config({'BLOCK_SIZE_M': 4, 'BLOCK_SIZE_N': 4096})   # 2840.48 us
triton.Config({'BLOCK_SIZE_M': 2, 'BLOCK_SIZE_N': 8192})   # 2801.20 us
triton.Config({'BLOCK_SIZE_M': 1, 'BLOCK_SIZE_N': 16384})  # 2779.78 us 最优

总结

在优先占满UB前提下,为reduce轴分配较大切分尺寸,减少循环次数,但需权衡单次迭代计算负载。

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 47 lines · 91 tokens per session scan A 7a30ccf9c3a6

Subscribe to this mod's changes

triton-ascend-case-reduction-amin-medium is a skill published in the GitHub repository mindspore-ai/akg (259 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 91 tokens to every session and 541 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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