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https://github.com/auburn/fastnoise2

Modular node graph based noise generation library using SIMD, C++17 and templates
https://github.com/auburn/fastnoise2

cross-platform fastnoise magnum node-graph noise noise-algorithms noise-generator perlin-noise procedural-generation simd simplex terrain-generation texture-generation

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Modular node graph based noise generation library using SIMD, C++17 and templates

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# FastNoise2

WIP successor to [FastNoiseSIMD](https://github.com/Auburn/FastNoiseSIMD)

Modular node based noise generation library using SIMD, modern C++17 and templates

FastNoise2 is a fully featured noise generation library which aims to meet all your coherent noise needs while being extremely fast

Uses FastSIMD to compile classes with multiple SIMD types and selects the fastest supported SIMD level at runtime
- Scalar (non-SIMD)
- SSE2
- SSE4.1
- AVX2
- AVX512
- NEON

Supports:
- 32/64 bit
- Windows
- Linux
- Android
- MacOS x86/ARM
- MSVC
- Clang
- GCC

Bindings:
- [C#](https://github.com/Auburn/FastNoise2Bindings)
- [Unreal Engine CMake](https://github.com/caseymcc/UE4_FastNoise2)
- [Unreal Engine Blueprint](https://github.com/DoubleDeez/UnrealFastNoise2)
- [Rust](https://github.com/Lemonzyy/fastnoise2-rs)
- [Java](https://github.com/CoolLoong/FastNoise2Bindings-Java)

Roadmap:
- [Vague collection of ideas](https://github.com/users/Auburn/projects/1)

## Noise Tool

The FastNoise2 noise tool provides a node graph editor to create trees of FastNoise2 nodes. Node trees can be exported as serialised strings and loaded into the FastNoise2 library in your own code. The noise tool has 2D and 3D previews for the node graph output, see screenshots below for examples.

Check the [Releases](https://github.com/Auburn/FastNoise2/releases/latest) for compiled NoiseTool binaries

![NoiseTool](https://user-images.githubusercontent.com/1349548/90967950-4e8da600-e4de-11ea-902a-94e72cb86481.png)

## Performance

FastNoise2 has continuous benchmarking to track of performance for each node type across commits

Results can be found here: https://auburn.github.io/fastnoise2benchmarking/

### Library Comparisons

Benchmarked using [NoiseBenchmarking](https://github.com/Auburn/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)

| 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 |
| FastNoise2 (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 |
| FastNoise2 (AVX2) | 776.33 | 624.27 | 466.03 | 194.30 |

# Getting Started

See [documentation](https://github.com/Auburn/FastNoise2/wiki)