Huawei Cloud Ascend Op Mfu Calculator

Organization

huaweicloud

huawei-cloud-ascend-op-mfu-calculator

Calculate MFU (Machine FLOP Utilization) for operators like matmul/GEMM/FlashAttention on Ascend NPU, providing clear formulas and derivation process Use this skill when the user wants to: (1) calculate MFU for matrix operations, (2) analyze operator performance efficiency, (3) understand hardware utilization, (4) optimize operator implementation Trigger: user mentions "MFU", "machine flop utilization", "operator FLOPs", "matmul performance", "GEMM efficiency", "Ascend MFU", "算子MFU", "算力利用率", "矩阵乘效率", "GEMM性能", "FlashAttention性能"

Overview

Publisher	huaweicloud
Repository	`huaweicloud-skills`
Skill name	`huawei-cloud-ascend-op-mfu-calculator`
Stars	59
Forks	24
Bundled files	2
License	MIT
Links	Skill source Repository

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.
2 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by huaweicloud on GitHub. Read the source before you install it.

Installation

Install the Huawei Cloud Ascend Op Mfu Calculator AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/huaweicloud/huaweicloud-skills/tree/master/skills/ai/modelarts/huawei-cloud-ascend-op-mfu-calculator
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/huaweicloud/huaweicloud-skills/tree/master/skills/ai/modelarts/huawei-cloud-ascend-op-mfu-calculator

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

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/huaweicloud/huaweicloud-skills.git /tmp/huaweicloud-skills
mkdir -p .claude/skills
cp -r /tmp/huaweicloud-skills/skills/ai/modelarts/huawei-cloud-ascend-op-mfu-calculator .claude/skills/huawei-cloud-ascend-op-mfu-calculator

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Huawei Cloud Ascend Op Mfu Calculator 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 Huawei Cloud Ascend Op Mfu Calculator 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 Huawei Cloud Ascend Op Mfu Calculator 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.

Huawei Cloud Ascend Operator MFU Calculator

Overview

This skill calculates MFU (Machine FLOP Utilization) for operators like matmul/GEMM/FlashAttention on Ascend NPU, providing clear formulas and derivation process.

Architecture: Input Validation → FLOPs Calculation → Achieved TFLOPs/s → MFU Calculation → Result Analysis

Related Skills:

huawei-cloud-ascend-profiler-db-explorer - Profiling data analysis for operator performance data

Prerequisites

Python 3.8+ installed
Basic understanding of FLOPs calculation concepts

Usage Scenarios

Typical Problem Scenarios:

Evaluating how well an operator utilizes Ascend NPU compute power
Comparing performance of different operator implementations
Identifying optimization opportunities for matrix operations

Typical User Utterances:

"Calculate MFU for my GEMM operator"
"What's the machine FLOP utilization for FlashAttention?"
"Analyze my matmul operator performance efficiency"

Workflow

Input Collection: Gather operator parameters (matrix dimensions, data types, execution time)
FLOPs Calculation: Compute theoretical FLOPs for the operation
Achieved Performance: Calculate achieved TFLOPs/s from execution time
MFU Calculation: Apply formula MFU = Achieved FLOPs / Peak FLOPs
Result Analysis: Provide interpretation and optimization suggestions

MFU Calculation Formula

MFU = (Achieved FLOPs / Peak FLOPs) × 100%

Where:

Achieved FLOPs = Operation FLOPs / Execution Time
Peak FLOPs = Hardware-specific peak performance (e.g., Ascend 910B: 256 TFLOPs for FP16)

Reference Documents

Document	Description
Ascend 910B Series Technical Specifications	Official Ascend 910B series product specifications
MFU Calculation Methodology	Detailed MFU calculation formulas and examples
FlashAttention Technical Paper	Original FlashAttention research paper

Enhanced Features

Intelligent Bottleneck Diagnoser

AI-powered bottleneck diagnosis that analyzes profiling data to identify root causes automatically
Classifies bottlenecks into categories: memory-bound, compute-bound, communication-bound, or operator-fallback
Provides actionable optimization recommendations with priority ranking
Includes pattern matching for known performance anti-patterns

Parameter Confirmation

Parameter	Description	Required
operator	Operator type (matmul/flash_attention/gemm, etc.)	Yes
flops	Theoretical FLOPs of the operator	Yes
time_ms	Operator execution time (milliseconds)	Yes
peak_tflops	Hardware peak computing power (TFLOPS)	Yes
device	NPU device type (910B/910, etc.)	No

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 Huawei Cloud Ascend Op Mfu Calculator AI skill do?

Why use Huawei Cloud Ascend Op Mfu Calculator on TypingMind?

Because you install it once and use it with any model. Huawei Cloud Ascend Op Mfu Calculator 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 Huawei Cloud Ascend Op Mfu Calculator in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/huaweicloud/huaweicloud-skills/tree/master/skills/ai/modelarts/huawei-cloud-ascend-op-mfu-calculator. 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 Huawei Cloud Ascend Op Mfu Calculator?

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 Huawei Cloud Ascend Op Mfu Calculator?

As many as you like. As long as a model supports skills, you can use Huawei Cloud Ascend Op Mfu Calculator with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Huawei Cloud Ascend Op Mfu Calculator AI skill free?

Yes. It is published on GitHub by huaweicloud under the MIT 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Huawei Cloud Ascend Operator MFU Calculator

Overview

Prerequisites

Usage Scenarios

Workflow

MFU Calculation Formula

Reference Documents

Enhanced Features

Intelligent Bottleneck Diagnoser

Parameter Confirmation

Bundled files

Frequently asked questions

Related AI Skills

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