Computational Science Technical Note CSTN-146

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High Performance Monte Carlo and Time-Stepping Dynamics for the Classical Spin Heisenberg Model on GPUs

K.A. Hawick and D.P. Playne

Archived February 2011

Abstract

The Heisenberg model of classical spins makes use of both Monte Carlo stochastic dynamics as well as time-integration of its equation of motion. These two schemes have different parallelisation strategies and tradeoffs. We implement both algorithms using a data-parallel approach for Graphical Processing Units (GPUs) and we discuss the resulting performance on various combinations of single and multiple GPU. In addition to studying Metropolis, Glauber and Wolff Monte Carlo dynamical update schemes, we use our fast simulation code to explore the scaling and time correlations of a large-scale Heisenberg model system using a high-order numerical integration algorithm, which enables study of accurate spin wave phenomena.

Keywords: Heisenberg model; classical spin; Monte Carlo dynamics; time-integration dynamics.

Full Document Text: PDF version.

Citation Information: BiBTeX database for CSTN Notes.

BiBTeX reference:

@INPROCEEDINGS{CSTN-146,
  author = {K. A. Hawick and D. P. Playne},
  title = {High Performance Monte Carlo and Time-Stepping Dynamics for the Classical
	Spin Heisenberg Model on GPUs,},
  booktitle = {Proc. Int. Conf. on Modelling, Simulation and Visualiztion Methods
	(MSV'12)},
  year = {2012},
  pages = {87-93},
  address = {Las Vegas, USA},
  month = {16-19 July},
  publisher = {CSREA},
  institution = {Computer Science, Massey University},
  timestamp = {2012.05.03}
}


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