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parallel-algorithms

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Rigorously analyze fork-join parallelism

Software Engineering#concurrency#analysis-framework#parallel-algorithms#fork-join#work-span#determinacy-race#production-analysis
AuthorArcadi4
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This skill helps researchers and practitioners analyze fork-join parallel algorithms to verify correctness before speed, focusing on work, span, race detection, slackness, and practical production considerations.

Core Features & Use Cases

  • Provides a clear framework for fork-join semantics, including spawn, sync, and parallel for constructs, and how to project serial and parallel executions.
  • Emphasizes deterministic reasoning about work and span, race freedom, and safe performance tradeoffs, with production-oriented checks like granularity, scheduler overhead, and memory behavior.
  • Suitable for analyzing classic textbook algorithms (e.g., matrix multiplication, merges, scans) and evaluating reductions, scans, and stochastic components in concurrent settings.

Quick Start

Review a fork-join parallel algorithm and determine its serial projection, work, span, and any determinacy races.

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

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Please help me install this Skill:
Name: parallel-algorithms
Download link: https://github.com/Arcadi4/nerdy/archive/main.zip#parallel-algorithms

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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