This fork is meant to be used as a UPM package inside Unity.

You can be install this package via the Unity Package Manager (UPM). In the top left of the Packages window, navigate to Add Package -> Add package from git URL and paste https://github.com/Eyap53/FastNoiseLite.git.

All credits goes to Jordan Peck and the contributors of the FastNoiseLite library. https://github.com/Auburn/FastNoiseLite.git. You may find a sponsor link there to support his work.

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.

• 2D & 3D
• OpenSimplex2 Noise
• OpenSimplex2S Noise
• Cellular (Voronoi) Noise
• Perlin Noise
• Value Noise
• Value Cubic Noise
• OpenSimplex2-based Domain Warp
• Basic Grid Gradient Domain Warp
• Multiple fractal options for all of the above
• Supports floats and/or doubles

• C#
• C++98
• C99
• Java
• HLSL

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 and testing noise settings.

Download links can be found in the Releases. Build instructions can be found in the PreviewApp directory.

Benchmarked using C++ version with NoiseBenchmarking

• CPU: Intel 7820X @ 4.9Ghz
• OS: Win10 x64
• Compiler: clang-cl 10.0.0 -m64 /O2

Million points of noise generated per second (higher = better)

• OpenSimplex2 for the OpenSimplex2 noise algorithm
• @KdotJPG for implementing all the OpenSimplex alogrithms and the Java port
• CubicNoise for the Value (Cubic) noise algorithm
• @Rover656 for creating the preview GUI and porting FastNoise Lite to C and HLSL.