auburn/fastnoiselite

Fast Portable Noise Library - C# C++ C Java HLSL GLSL JavaScript Rust Go

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Summary Information

Updated 48 minutes ago
Added to GitGenius on September 19th, 2026
Created on March 28th, 2016
Open Issues & Pull Requests: 29 (+0)
GitHub issues: Enabled
Number of forks: 371
Total Stargazers: 3,513 (+0)
Total Subscribers: 63 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 7.7 hours
Mean response time: 193.3 days
90th percentile: 823.6 days
Tracked items: 7

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Issue Activity (beta)

Open issues: 11
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 472 days
Stale 30+ days: 10
Stale 90+ days: 9

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Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

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Detailed Description

FastNoise Lite is a noise generation library that provides portable implementations across multiple programming languages including C#, C++, Java, Rust, Go, JavaScript, and shader languages.

The library solves the problem of needing performant procedural noise generation that works consistently across different platforms and languages. It offers a selection of noise algorithms including OpenSimplex2, Perlin, Cellular (Voronoi), and Value noise, along with domain warping and fractal options for all of them. The approach prioritizes portability by avoiding platform-specific features, making it straightforward to integrate into projects and maintain consistent behavior across language implementations.

Developers should choose this tool when they need reliable noise generation for procedural content in games, terrain generation, or graphics applications where portability across languages matters. It suits projects that require 2D or 3D noise sampling with support for both float and double precision. For projects demanding significantly higher performance through SIMD optimization and complex noise configurations, the README recommends considering FastNoise2 instead, which uses a node graph structure for greater flexibility.

The project maintains active support across a broad ecosystem of language ports, with community contributions encouraged through pull requests for new language implementations. Development activity shows ongoing refinement of the core algorithms and consistent maintenance of the existing language implementations.