A GPU-based Large-scale Monte Carlo Simulation Method for Systems with Long-range Interactions

TL;DR

This paper introduces a GPU-accelerated Monte Carlo simulation method for Coulomb systems, achieving significant speedup and enabling precise analysis of electrolyte properties beyond classical theories.

Contribution

The work presents a GPU-based implementation of Monte Carlo simulation for long-range interacting systems, with no energy approximation and high computational efficiency.

Findings

Achieved 440-fold speedup over CPU implementation.

Precisely measured ion-ion correlation functions at high concentrations.

Identified physics beyond classical Poisson-Boltzmann theory.

Abstract

In this work we present an efficient implementation of Canonical Monte Carlo simulation for Coulomb many body systems on graphics processing units (GPU). Our method takes advantage of the GPU Single Instruction, Multiple Data (SIMD) architectures. It adopts the sequential updating scheme of Metropolis algorithm, and makes no approximation in the computation of energy. It reaches a remarkable 440-fold speedup, compared with the serial implementation on CPU. We use this method to simulate primitive model electrolytes. We measure very precisely all ion-ion pair correlation functions at high concentrations, and extract renormalized Debye length, renormalized valences of constituent ions, and renormalized dielectric constants. These results demonstrate unequivocally physics beyond the classical Poisson-Boltzmann theory.