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Population Annealing and Large Scale Simulations in Statistical Mechanics

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 965))

Abstract

Population annealing is a novel Monte Carlo algorithm designed for simulations of systems of statistical mechanics with rugged free-energy landscapes. We discuss a realization of the algorithm for the use on a hybrid computing architecture combining CPUs and GPGPUs. The particular advantage of this approach is that it is fully scalable up to many thousands of threads. We report on applications of the developed realization to several interesting problems, in particular the Ising and Potts models, and review applications of population annealing to further systems.

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Acknowledgment

This work was partially supported by the grant 14-21-00158 from the Russian Science Foundation and by the Landau Institute for Theoretical Physics in the framework of the tasks from the Federal Agency of Scientific Organizations. The authors acknowledge support from the European Commission through the IRSES network DIONICOS under Contract No. PIRSES-GA-2013-612707.

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Correspondence to Lev Shchur .

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Shchur, L., Barash, L., Weigel, M., Janke, W. (2019). Population Annealing and Large Scale Simulations in Statistical Mechanics. In: Voevodin, V., Sobolev, S. (eds) Supercomputing. RuSCDays 2018. Communications in Computer and Information Science, vol 965. Springer, Cham. https://doi.org/10.1007/978-3-030-05807-4_30

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  • DOI: https://doi.org/10.1007/978-3-030-05807-4_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-05806-7

  • Online ISBN: 978-3-030-05807-4

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