Can I access the DOM or WebGL from within a worker?

No, worker threads do not have access to main-thread-only APIs like the DOM or standard WebGL contexts. This skill focuses on moving numeric math and pure logic to workers.

How do I prevent the application from crashing if a worker fails?

The skill includes workflow steps for catching worker errors, logging failures, and implementing main-thread fallbacks to ensure graceful degradation.

Does this work in both browser and Node.js environments?

Yes, this skill provides implementation patterns suitable for both browser Web Workers and Node.js worker_threads.

How does it handle data transfer between threads?

It emphasizes using TypedArrays with transferables to move memory ownership or SharedArrayBuffers for zero-copy data sharing, avoiding expensive structured cloning.

JS Worker Multithreading

Name: JS Worker Multithreading
Author: deadronos

bydeadronos

ゲーム開発

Optimizes JavaScript and TypeScript application performance by offloading CPU-heavy tasks to background worker pools.

概要

This skill provides a comprehensive framework for implementing, refactoring, and debugging multithreading in JavaScript and TypeScript environments. It guides developers through the complexities of Web Workers and Node.js threads, focusing on creating high-performance worker kernels that handle heavy computation while keeping the main thread responsive for UI and user interaction. By leveraging advanced patterns like buffer transfers, SharedArrayBuffer synchronization, and hardware-aware pool sizing, it helps eliminate frame drops and UI lag in compute-intensive applications such as games, simulations, and data processing tools.

主な機能

Robust fallback patterns for environments without shared memory
Resource lifecycle management and buffer reuse strategies
0 GitHub stars
Implementation of scalable worker pools for browser and Node.js
Optimization of data transfers using TypedArrays and Move helpers
Hardware-aware pool sizing based on CPU concurrency

ユースケース

Implementing background data parsing and image manipulation in real-time apps
Offloading complex physics or voxel calculations in web-based games
Processing large datasets or running heavy math simulations without UI freezing

概要

主な機能

Robust fallback patterns for environments without shared memory
Resource lifecycle management and buffer reuse strategies
0 GitHub stars
Implementation of scalable worker pools for browser and Node.js
Optimization of data transfers using TypedArrays and Move helpers
Hardware-aware pool sizing based on CPU concurrency

ユースケース

Implementing background data parsing and image manipulation in real-time apps
Offloading complex physics or voxel calculations in web-based games
Processing large datasets or running heavy math simulations without UI freezing