training-mfu-calculator
CommunityEvaluate large model training efficiency with precise MFU metrics.
Software Engineering#deep learning#performance analysis#mf u#training efficiency#model FLOPs#GPU utilization
Authordongg622
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill provides an automated way to compute the Model FLOPs Utilization (MFU) for large-scale neural network training, enabling users to assess hardware utilization during training sessions.
Core Features & Use Cases
- MFU Calculation: Accurately estimate hardware efficiency based on model configuration, training parameters, and hardware specs.
- Performance Analysis: Generate detailed reports on FLOPs, GPU utilization, and throughput for model training workflows.
- Use Case: A developer trains a 70B parameter model on 128 GPUs; this Skill helps quantify the actual compute utilization to identify optimization opportunities.
Quick Start
Describe the model and training setup, then invoke the tool to produce a comprehensive performance report and MFU value.
Dependency Matrix
Required Modules
None requiredComponents
scriptsreferences
💻 Claude Code Installation
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Please help me install this Skill: Name: training-mfu-calculator Download link: https://github.com/dongg622/china-ai-chip-skill/archive/main.zip#training-mfu-calculator Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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