Fast Portable Noise Library - C# C++ C Java HLSL GLSL JavaScript Rust Go
MIT License
FastNoise Lite is an extremely portable open source noise generation library with a large selection of noise algorithms. This library focuses on high performance while avoiding platform/language specific features, allowing for easy ports to as many possible languages.
This project is an evolution of the original FastNoise library and shares the same goal: An easy to use library that can quickly be integrated into a project and provides performant modern noise generation. See a breakdown of changes from the transition to FastNoise Lite here
If you are looking for a more extensive noise generation library consider using FastNoise2. It provides large performance gains thanks to SIMD and uses a node graph structure to allow complex noise configurations with lots of flexibility.
If you want to port FastNoise Lite to a new language create a pull request or discuss it on the discord linked above
Link: https://auburn.github.io/FastNoiseLite
A compact testing application is available for testing all features included in FastNoise Lite with a visual representation. This can be used for development purposes, testing noise settings and generating noise textures for export.
Source code can be found in the WebPreviewApp directory.
Benchmarked using C++ version with NoiseBenchmarking
Million points of noise generated per second (higher = better)
3D | Value | Perlin | (*Open)Simplex | Cellular |
---|---|---|---|---|
FastNoise Lite | 64.13 | 47.93 | 36.83* | 12.49 |
FastNoise (Legacy) | 49.34 | 37.75 | 44.74 | 13.27 |
FastNoise 2 (AVX2) | 494.49 | 261.10 | 268.44 | 52.43 |
libnoise | 27.35 | 0.65 | ||
stb perlin | 34.32 |
2D | Value | Perlin | Simplex | Cellular |
---|---|---|---|---|
FastNoise Lite | 114.01 | 92.83 | 71.30 | 39.15 |
FastNoise (Legacy) | 102.12 | 87.99 | 65.29 | 36.84 |
FastNoise 2 (AVX2) | 776.33 | 624.27 | 466.03 | 194.30 |
New ports of FastNoise Lite are always welcome, create a PR or come discuss the port with me on the discord linked above. I'm not an expert or even familiar with every language FastNoise lite has been ported to, so if you see something that could be improved please contribute or create a GitHub issue.