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Massively parallel simulations for disordered systems

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Abstract

Simulations of systems with quenched disorder are extremely demanding, suffering from the combined effect of slow relaxation and the need of performing the disorder average. As a consequence, new algorithms and improved implementations in combination with alternative and even purpose-built hardware are often instrumental for conducting meaningful studies of such systems. The ensuing demands regarding hardware availability and code complexity are substantial and sometimes prohibitive. We demonstrate how with a moderate coding effort leaving the overall structure of the simulation code unaltered as compared to a CPU implementation, very significant speed-ups can be achieved from a parallel code on GPU by mainly exploiting the trivial parallelism of the disorder samples and the near-trivial parallelism of the parallel tempering replicas. A combination of this massively parallel implementation with a careful choice of the temperature protocol for parallel tempering as well as efficient cluster updates allows us to equilibrate comparatively large systems with moderate computational resources.

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Authors and Affiliations

  1. Institut für Theoretische Physik, Universität Leipzig, IPF 231101, 04081, Leipzig, Germany

    Ravinder Kumar, Jonathan Gross & Wolfhard Janke

  2. Centre for Fluid and Complex Systems, Coventry University, Coventry, CV1 5FB, UK

    Ravinder Kumar & Martin Weigel

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  1. Ravinder Kumar
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  2. Jonathan Gross
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Correspondence to Martin Weigel.

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Contribution to the Topical Issue “Recent Advances in the Theory of Disordered Systems”, edited by Ferenc Iglói and Heiko Rieger.

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Kumar, R., Gross, J., Janke, W. et al. Massively parallel simulations for disordered systems. Eur. Phys. J. B 93, 79 (2020). https://doi.org/10.1140/epjb/e2020-100535-0

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