数据与复现材料、工程与模拟FreedomIntelligence/OpenClaw-Medical-Skills数据与复现
PE

performance-profiling

维护者 FreedomIntelligence · 最近更新 2026年4月1日

performance-profiling:Identify computational bottlenecks,analyze scaling behavior,estimate memory requirements,、 receive optimization recommendations ,用于 any computational 模拟。 适合在模拟s are slow,investigating parallel efficiency,planning resource allocation,或 seeking performance improvements through timing analysis,scaling studies,memory profiling,或 bottleneck detection时使用。

OpenClawNanoClaw分析处理复现实验performance-profiling📊 data science & toolscomputational simulation & ontologyidentify

原始来源

FreedomIntelligence/OpenClaw-Medical-Skills

https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/performance-profiling

维护者
FreedomIntelligence
许可
MIT
最近更新
2026年4月1日

技能摘要

来自 SKILL.md 的关键信息

2 min

核心说明

  • 提供 tools to analyze 模拟 performance,identify bottlenecks,、 recommend optimization strategies ,用于 computational 材料科学 模拟s。
  • python3 scripts/timing_analyzer.py \ --log 模拟.log \ --json。

原始文档

SKILL.md 摘录

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:

InputDescriptionExample
Simulation logLog file with timing informationsimulation.log
Scaling dataJSON with multi-run performance datascaling_data.json
Simulation parametersJSON with mesh, fields, solver configparams.json
Available memorySystem memory in GB (optional)16.0

Choosing Analysis Thresholds

MetricGoodAcceptablePoor
Phase dominance<30%30-50%>50%
Parallel efficiency>0.800.70-0.80<0.70
Memory usage<60%60-80%>80%

适用场景

  • 适合在模拟s are slow,investigating parallel efficiency,planning resource allocation,或 seeking performance improvements through timing analysis,scaling studies,memory profiling,或 bottleneck detection时使用。

不适用场景

  • Do not rely on this catalog entry alone ,用于 installation 或 maintenance details。

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