Reaction-diffusion model Monte Carlo simulations on the GPU

TL;DR

This paper introduces a GPU-optimized Monte Carlo simulation algorithm for reaction-diffusion models, achieving significant speed-ups over CPU implementations, exemplified by the pair contact process with diffusion.

Contribution

The paper presents a novel GPU-based algorithm for reaction-diffusion Monte Carlo simulations, combining GPU-specific techniques with multispin methods for enhanced performance.

Findings

GPU algorithm is approximately 4000 times faster than CPU implementation.

Speed-up of about 130x when comparing GPU to CPU.

Demonstrated efficiency on the pair contact process with diffusion.

Abstract

We created an efficient algorithm suitable for graphics processing units (GPUs) to perform Monte Carlo simulations of a subset of reaction-diffusion models. The algorithm uses techniques that are specific to GPU programming, and combines these with the multispin technique known from CPU programming to create one of the fastest algorithms for reaction-diffusion models. As an example, the algorithm is applied to the pair contact process with diffusion (PCPD). Compared to a simple algorithm on the CPU, our GPU algorithm is approximately 4000 times faster. If we compare the performance of the GPU algorithm, between the GPU and CPU, we find a speed-up of about 130x.