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"
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/huaweicloud/huaweicloud-skills --skill huawei-cloud-ascend-op-mfu-calculator- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads huawei-cloud-ascend-op-mfu-calculator automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
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 |
FAQ
What does the huawei-cloud-ascend-op-mfu-calculator skill do?
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"
How do I install huawei-cloud-ascend-op-mfu-calculator?
Run npx skills add https://github.com/huaweicloud/huaweicloud-skills --skill huawei-cloud-ascend-op-mfu-calculator in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/huawei-cloud-ascend-op-mfu-calculator/ (personal) or .claude/skills/huawei-cloud-ascend-op-mfu-calculator/ (project).
Which AI agents can use huawei-cloud-ascend-op-mfu-calculator?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is huawei-cloud-ascend-op-mfu-calculator safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains huawei-cloud-ascend-op-mfu-calculator?
It is published by huaweicloud in huaweicloud/huaweicloud-skills. It has 262 recorded installs.
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