# Implementing Noise with Hash functions for Graphics Processing Units

## TL;DR

This paper introduces a method to generate noise on GPUs using hash functions instead of textures, reducing memory bandwidth at the cost of increased computation, and demonstrates its implementation with several hash functions.

## Contribution

It presents a novel approach to generate Perlin noise using hash functions on GPUs, eliminating the need for texture lookups and enabling efficient noise computation.

## Key findings

- Hash-based noise performs comparably to texture-based methods.
- Modified hash functions enable texture-free noise generation.
- Trade-off between computation and memory bandwidth is demonstrated.

## Abstract

We propose a modification to Perlin noise which use computable hash functions instead of textures as lookup tables. We implemented the FNV1, Jenkins and Murmur hashes on Shader Model 4.0 Graphics Processing Units for noise generation. Modified versions of the FNV1 and Jenkins hashes provide very close performance compared to a texture based Perlin noise implementation. Our noise modification enables noise function evaluation without any texture fetches, trading computational power for memory bandwidth.