Population Annealing and Large Scale Simulations in Statistical Mechanics

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

doi:10.1007/978-3-030-05807-4_30

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 proceeding › Conference proceeding › peer-review

3 Citations (Scopus)

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 language	English
Title of host publication	Supercomputing. RuSCDays 2018.
Place of Publication	Cham
Publisher	Springer
Pages	354-366
Number of pages	13
Volume	965
ISBN (Electronic)	978-3-030-05807-4
ISBN (Print)	978-3-030-05806-7
DOIs	https://doi.org/10.1007/978-3-030-05807-4_30
Publication status	Published - 24 Nov 2018
Event	Russian Supercomputing Days - Moscow, Russian Federation Duration: 24 Sept 2018 → 25 Sept 2018

Publication series

Name	Communications in Computer and Information Science
Volume	965

Conference

Conference	Russian Supercomputing Days
Abbreviated title	RuSCDays
Country/Territory	Russian Federation
City	Moscow
Period	24/09/18 → 25/09/18

Keywords

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

Access to Document

10.1007/978-3-030-05807-4_30

https://link.springer.com/chapter/10.1007/978-3-030-05807-4_30

Cite this

Population Annealing and Large Scale Simulations in Statistical Mechanics. / Shchur, Lev N.; Barash, Lev Yu; Weigel, Martin et al.
Supercomputing. RuSCDays 2018. . Vol. 965 Cham: Springer, 2018. p. 354-366 (Communications in Computer and Information Science; Vol. 965).

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding › peer-review

Shchur, LN, Barash, LY, Weigel, M & Janke, W 2018, Population Annealing and Large Scale Simulations in Statistical Mechanics. in Supercomputing. RuSCDays 2018. . vol. 965, Communications in Computer and Information Science, vol. 965, Springer, Cham, pp. 354-366, Russian Supercomputing Days, Moscow, Russian Federation, 24/09/18. https://doi.org/10.1007/978-3-030-05807-4_30

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N2 - 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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KW - Parallel algorithms

KW - Scalability

KW - Statistical mechanics

KW - Population annealing

KW - Markov Chain Monte Carlo

KW - Sequential Monte Carlo

KW - Hybrid computing architecture CPU+GPGPU

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T3 - Communications in Computer and Information Science

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CY - Cham

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Y2 - 24 September 2018 through 25 September 2018

ER -

Population Annealing and Large Scale Simulations in Statistical Mechanics

Abstract

Publication series

Conference

Keywords

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Cite this