Suppressing correlations in massively parallel simulations of lattice models

Jeffrey Kelling, G. Ódor, Sibylle Gemming

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

For lattice Monte Carlo simulations parallelization is crucial to make studies of large systems and long simulation time feasible, while sequential simulations remain the gold-standard for correlation-free dynamics. Here, various domain decomposition schemes are compared, concluding with one which delivers virtually correlation-free simulations on GPUs. Extensive simulations of the octahedron model for 2+1 dimensional Kardar–Parisi–Zhang surface growth, which is very sensitive to correlation in the site-selection dynamics, were performed to show self-consistency of the parallel runs and agreement with the sequential algorithm. We present a GPU implementation providing a speedup of about 30× over a parallel CPU implementation on a single socket and at least 180× with respect to the sequential reference.

Original languageEnglish
Pages (from-to)205-211
Number of pages7
JournalComputer Physics Communications
Volume220
DOIs
Publication statusPublished - Nov 1 2017

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Keywords

  • Autocorrelation
  • GPU
  • Kardar–Parisi–Zhang
  • Lattice Monte Carlo

ASJC Scopus subject areas

  • Physics and Astronomy(all)
  • Hardware and Architecture

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