A GPU-based Large-scale Monte Carlo Simulation Method for Systems with Long-range Interactions
Institute of Natural Sciences and Department of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai, 200240 China
arXiv:1602.05716 [physics.comp-ph], (18 Feb 2016)
@article{liang2016gpubased,
title={A GPU-based Large-scale Monte Carlo Simulation Method for Systems with Long-range Interactions},
author={Liang, Yihao and Xing, Xiangjun and Li, Yaohang},
year={2016},
month={feb},
archivePrefix={"arXiv"},
primaryClass={physics.comp-ph}
}
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.
February 19, 2016 by hgpu
