Population Annealing and Large Scale Simulations in Statistical Mechanics

Lev N. Shchur, Lev Yu Barash, Martin Weigel, Wolfhard Janke

    Research output: Chapter in Book/Report/Conference proceedingConference proceeding

    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.
    Original languageEnglish
    Title of host publicationSupercomputing. RuSCDays 2018.
    Place of PublicationCham
    PublisherSpringer
    Pages354-366
    Number of pages13
    Volume965
    ISBN (Electronic)978-3-030-05807-4
    ISBN (Print)978-3-030-05806-7
    DOIs
    Publication statusPublished - 24 Nov 2018
    EventRussian Supercomputing Days - Moscow, Russian Federation
    Duration: 24 Sep 201825 Sep 2018

    Publication series

    NameCommunications in Computer and Information Science
    Volume965

    Conference

    ConferenceRussian Supercomputing Days
    Abbreviated titleRuSCDays
    CountryRussian Federation
    CityMoscow
    Period24/09/1825/09/18

    Keywords

    • Parallel algorithms
    • Scalability
    • Statistical mechanics
    • Population annealing
    • Markov Chain Monte Carlo
    • Sequential Monte Carlo
    • Hybrid computing architecture CPU+GPGPU

    Fingerprint Dive into the research topics of 'Population Annealing and Large Scale Simulations in Statistical Mechanics'. Together they form a unique fingerprint.

    Cite this