Random Tilings with the GPU

TL;DR

This paper introduces GPU-accelerated algorithms for efficiently sampling complex mathematical models like random tilings, dimers, and the six-vertex model using Markov chain methods.

Contribution

It provides novel GPU implementations that significantly speed up the sampling process for these models compared to traditional CPU methods.

Findings

GPU implementations outperform CPU in sampling speed

Efficient Markov chain algorithms for complex models

Potential applications in statistical physics and combinatorics

Abstract

We present GPU accelerated implementations of Markov chain algorithms to sample random tilings, dimers, and the six-vertex model.