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We present a case-study on the utility of graphics cards to perform massively parallel simulation of advanced Monte Carlo methods. Graphics cards, containing multiple Graphics Processing Units (GPUs), are self-contained parallel…

Computation · Statistics 2015-05-05 Anthony Lee , Christopher Yau , Michael B. Giles , Arnaud Doucet , Christopher C. Holmes

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…

Computational Physics · Physics 2013-03-06 R. D. Schram

We consider Monte Carlo simulations of classical spin models of statistical mechanics using the massively parallel architecture provided by graphics processing units (GPUs). We discuss simulations of models with discrete and continuous…

Computational Physics · Physics 2012-07-20 Martin Weigel , Taras Yavors'kii

The Monte Carlo method is a powerful technique for computing thermodynamic magnetic states of otherwise unsolvable spin Hamiltonians, but the method becomes computationally prohibitive with increasing number of spins and the simulation of…

Computational Physics · Physics 2021-06-22 Michalis Charilaou

Implementation of basic local Monte-Carlo algorithms on ATI Graphics Processing Units (GPU) is investigated. The Ising model and pure SU(2) gluodynamics simulations are realized with the Compute Abstraction Layer (CAL) of ATI Stream…

High Energy Physics - Lattice · Physics 2009-03-30 Vadim Demchik , Alexei Strelchenko

Generalized-ensemble Monte Carlo simulations such as the multicanonical method and similar techniques are among the most efficient approaches for simulations of systems undergoing discontinuous phase transitions or with rugged free- energy…

Computational Physics · Physics 2018-02-06 Jonathan Gross , Johannes Zierenberg , Martin Weigel , Wolfhard Janke

We present a scheme for the parallelization of quantum Monte Carlo on graphical processing units, focusing on bosonic systems and variational Monte Carlo. We use asynchronous execution schemes with shared memory persistence, and obtain an…

Computational Physics · Physics 2014-12-10 Y. Lutsyshyn

Current trends in parallel processors call for the design of efficient massively parallel algorithms for scientific computing. Parallel algorithms for Monte Carlo simulations of thermodynamic ensembles of particles have received little…

Computational Physics · Physics 2013-08-26 Joshua A. Anderson , Eric Jankowski , Thomas L. Grubb , Michael Engel , Sharon C. Glotzer

This paper introduces novel method of simulation of lipid biomembranes based on Metropolis Hastings algorithm and Graphic Processing Unit computational power. Method gives up to 55 times computational boost in comparison to classical…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-09-18 M. Lis , L. Pintal

We perform large-scale Monte Carlo simulations of the classical XY model on a three-dimensional $L\times L \times L$ cubic lattice using the graphics processing unit (GPU). By the combination of Metropolis single-spin flip, over-relaxation…

Statistical Mechanics · Physics 2012-11-06 Ti-Yen Lan , Yun-Da Hsieh , Ying-Jer Kao

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…

Computational Physics · Physics 2015-05-28 Jonathan Groß , Wolfhard Janke , Michael Bachmann

The answers to data assimilation questions can be expressed as path integrals over all possible state and parameter histories. We show how these path integrals can be evaluated numerically using a Markov Chain Monte Carlo method designed to…

Computational Physics · Physics 2015-05-27 John C. Quinn , Henry D. I. Abarbanel

Graphics processing units (GPUs) are recently being used to an increasing degree for general computational purposes. This development is motivated by their theoretical peak performance, which significantly exceeds that of broadly available…

Computational Physics · Physics 2015-03-17 Martin Weigel

GPU computing has become popular in computational finance and many financial institutions are moving their CPU based applications to the GPU platform. Since most Monte Carlo algorithms are embarrassingly parallel, they benefit greatly from…

Computational Finance · Quantitative Finance 2014-08-26 Linlin Xu , Giray Ökten

We discuss the efficiency of parallelization on graphical processing units (GPUs) for the simulation of the one dimensional Potts model with long range interactions via parallel tempering. We investigate the behaviour of some thermodynamic…

Statistical Mechanics · Physics 2015-06-17 A. Boer

Artifacts arise in the simulations of electrolytes using periodic boundary conditions (PBC). We show the origin of these artifacts are the periodic image charges and the constraint of charge neutrality inside the simulation box, both of…

Soft Condensed Matter · Physics 2015-09-30 Yihao Liang , Zhenli Xu , Xiangjun Xing

Molecular simulations in an open environment, involving ion exchange, are necessary to study various systems, from biosystems to confined electrolytes. However, grand-canonical simulations are often computationally demanding in condensed…

Chemical Physics · Physics 2023-11-13 Jeongmi Kim , Luc Belloni , Benjamin Rotenberg

This paper is devoted to computational algorithms designed to describe the classical Ising magnet in some specific cases when an additional macroscopic restriction in form of constant charge density exists in the system. We developed and…

Computational Physics · Physics 2023-01-30 K. S. Budrin , V. A. Ulitko , A. A. Chikov , Yu. D. Panov , A. S. Moskvin

Purpose: Very fast Monte Carlo (MC) simulations of proton transport have been implemented recently on GPUs. However, these usually use simplified models for non-elastic (NE) proton-nucleus interactions. Our primary goal is to build a…

Medical Physics · Physics 2015-06-11 H. Wan Chan Tseung , J. Ma , C. Beltran

We outline how auxiliary-field quantum Monte Carlo (AFQMC) can leverage graphical processing units (GPUs) to accelerate the simulation of solid state sytems. By exploiting conservation of crystal momentum in the one- and two-electron…

Computational Physics · Physics 2020-08-21 Fionn D. Malone , Shuai Zhang , Miguel A. Morales
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