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performance-profiling

Identify computational bottlenecks, analyze scaling behavior, estimate memory requirements, and receive optimization recommendations for any computational simulation. Use when simulations are slow, investigating parallel efficiency, planning resource allocation, or seeking performance improvements through timing analysis, scaling studies, memory profiling, or bottleneck detection.

2estrelas
Atualizado há 4 meses

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Ler descrição completa

Performance Profiling

Goal

Provide tools to analyze simulation performance, identify bottlenecks, and recommend optimization strategies for computational materials science simulations.

Requirements

  • Python 3.8+
  • No external dependencies (uses Python standard library only)
  • Works on Linux, macOS, and Windows

Inputs to Gather

Before running profiling scripts, collect from the user:

| Input | Description | Example | |-------|-------------|---------| | Simulation log | Log file

[Description truncada. Veja o README completo no GitHub.]

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