Massively parallelized replica-exchange simulations of polymers on GPUs

TL;DR

This paper demonstrates how leveraging GPU multithreading significantly accelerates replica-exchange Monte Carlo simulations of polymers, enabling more efficient sampling of conformations for statistical analysis.

Contribution

It introduces a GPU-based parallelization approach for replica-exchange simulations of polymers, showing substantial performance improvements over CPU implementations.

Findings

GPU implementation yields faster simulation times

Parallelization enhances sampling efficiency

Significant speedup compared to CPU code

Abstract

We discuss the advantages of parallelization by multithreading on graphics processing units (GPUs) for parallel tempering Monte Carlo computer simulations of an exemplified bead-spring model for homopolymers. Since the sampling of a large ensemble of conformations is a prerequisite for the precise estimation of statistical quantities such as typical indicators for conformational transitions like the peak structure of the specific heat, the advantage of a strong increase in performance of Monte Carlo simulations cannot be overestimated. Employing multithreading and utilizing the massive power of the large number of cores on GPUs, being available in modern but standard graphics cards, we find a rapid increase in efficiency when porting parts of the code from the central processing unit (CPU) to the GPU.