Triton Operator Design logo

Triton Operator Design

Organization
Ascend
triton-operator-design

生成适用于 Ascend NPU 的 Triton 算子需求文档。当用户需要设计新的 Triton 算子、编写算子需求文档、进行算子性能优化设计时使用。核心产出:功能定义、API 接口、Tiling 策略、Kernel 实现方案。

Overview

PublisherAscend
Repositoryagent-skills
Skill nametriton-operator-design
Stars
54
Forks
4
Bundled files
1
LicenseMulanPSL-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Ascend on GitHub. Read the source before you install it.

Installation

Install the Triton Operator Design AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Ascend/agent-skills/tree/master/skills/triton-operator-design
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Ascend/agent-skills.git /tmp/agent-skills
mkdir -p .claude/skills
cp -r /tmp/agent-skills/skills/triton-operator-design .claude/skills/triton-operator-design
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Triton Operator Design in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Triton Operator Design on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Triton Operator Design is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Triton 算子需求文档生成

工作流

  1. 需求分析 → 产出:功能定义、数学公式、竞品对比
  2. 原型设计 → 产出:API 接口定义
  3. 规格约束 → 产出:输入输出约束、硬件限制
  4. 特性实现 → 产出:Tiling 策略、Kernel 实现方案

参考资源加载

阶段必须加载不要加载
需求分析ascend-terminology.mdtemplate, tiling-strategies
原型设计triton-api-reference.mdtiling-strategies
特性实现tiling-strategies.md, triton-operator-template.mdascend-terminology

MANDATORY:阶段 4 前,完整阅读 tiling-strategies.md 和 triton-operator-template.md,不设行数限制。按模板格式输出文档。

关键术语

  • GM:全局内存(DDR),UB:Vector Core 高速缓存(192KB),L1:Cube Core 缓存(~1MB)
  • AI Core:A2/A3 有 24 个,含 1 Cube + 2 Vector
  • 归约操作必须升精度到 FP32

绝对不要做的事

  • ❌ 使用模糊术语("适当切分"、"合理分配")— 必须给出具体计算方法
  • ❌ 忽略 UB 大小(192KB)和对齐要求(32B)
  • ❌ 不区分 Vector Core(向量计算)和 Cube Core(矩阵计算)
  • ❌ 不标注数据流图中的数据类型和 GM↔UB 传输
  • ❌ 归约操作不说明升精度策略

常见陷阱

陷阱症状解决
UB 超限方案不可实现计算缓冲区总大小 < 192KB
内存未对齐硬件报错UB 缓冲区 32B 对齐,单值缓冲区分配 32B
精度损失FP16 结果不准归约前升 FP32,完成后降精度
Tiling 不合理性能差/大 shape 不支持按维度切分,避免跨 Core 数据依赖

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Triton Operator Design AI skill do?

生成适用于 Ascend NPU 的 Triton 算子需求文档。当用户需要设计新的 Triton 算子、编写算子需求文档、进行算子性能优化设计时使用。核心产出:功能定义、API 接口、Tiling 策略、Kernel 实现方案。

Why use Triton Operator Design on TypingMind?

Because you install it once and use it with any model. Triton Operator Design is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Triton Operator Design in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Ascend/agent-skills/tree/master/skills/triton-operator-design. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Triton Operator Design?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Triton Operator Design?

As many as you like. As long as a model supports skills, you can use Triton Operator Design with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Triton Operator Design AI skill free?

Yes. It is published on GitHub by Ascend under the MulanPSL-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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