Git Product home page Git Product logo

rust-simd-noise's Introduction

SIMDNoise

Super fast SIMD noise library for Rust. PRs welcome!

Features

  • Gradient Noise (Simplex aka Perlin) 1D,2D,3D,4D
  • Fractal Brownian Motion, Ridge, and Turbulence
  • Cellular Noise (aka Voroni) 2D, 3D
  • SSE2, SSE41, and AVX2 instruction sets, along with non SIMD fallback
  • AVX2 version also leverages FMA3
  • Runtime detection picks the best available instruction set
  • Provide a seed value to randomize your noise result

Benchmarks

Intel(R) Core(TM) i7-6700 CPU @ 3.40GHz Single Threaded using Criterion.rs

2D 4k (3840 × 2160) Fbm Noise, 3 Octaves

SIMD Set Time
scalar 888 ms
sse2 225 ms
sse41 186 ms
avx2 108 ms

3D 128 × 128 x 128 Cell Noise

SIMD Set Time
scalar 1,400 ms
sse2 128 ms
sse41 94 ms
avx2 47 ms

Todo

  • AVX512 support
  • ARM NEON support
  • Other noise types

Get a block of noise with runtime SIMD detection

The library will, at runtime, pick the fastest available options between SSE2, SSE41, and AVX2.

// Get a block of 2d fbm noise with default settings, 100 x 100, with values scaled to the range [0,1]
let noise = NoiseBuilder::fbm_2d(100, 100).generate_scaled(0.0, 1.0);

// Get a block of 3d ridge noise, custom settings, 32x32x32 unscaled
let (noise, min, max) = NoiseBuilder::ridge_3d(32, 32, 32)
    .with_freq(0.05)
    .with_octaves(5)
    .with_gain(2.0)
    .with_seed(1337)
    .with_lacunarity(0.5)
    .generate();

Call noise functions directly

Sometimes you need something other than a block, like the points on the surface of a sphere. Sometimes you may want to use SSE41 even with AVX2 is available.

let noise_setting = NoiseBuilder::ridge_3d(32, 32, 32)
    .with_freq(0.05)
    .with_octaves(5)
    .with_gain(2.0)
    .with_lacunarity(0.5)
    .wrap();

// get a block of noise with the sse41 version, using the above settings
let (noise, min, max) = unsafe { simdnoise::sse41::get_2d_noise(&noise_setting) };

// send your own SIMD x,y values to the noise functions directly
unsafe {
    // sse2 simplex noise
    let x = _mm_set1_ps(5.0);
    let y = _mm_set1_ps(10.0);
    let f: __m128 = simdnoise::sse2::simplex_2d(x, y);

    // avx2 turbulence
    let x = _mm256_set1_ps(5.0);
    let y = _mm256_set1_ps(10.0);
    let freq = _mm256_set1_ps(1.0);
    let lacunarity = _mm256_set1_ps(0.5);
    let gain = _mm256_set1_ps(2.0);
    let octaves = 3;
    let f_turbulence: __m256 = simdnoise::avx2::turbulence_2d(x, y, lacunarity, gain, octaves);
};

rust-simd-noise's People

Contributors

jackmott avatar danieledapo avatar trevors avatar

Watchers

James Cloos avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.