Performance of parallel-in-time integration for Rayleigh Bénard convection

Media type: E-Article
Title: Performance of parallel-in-time integration for Rayleigh Bénard convection
Contributor: Clarke, Andrew T. [Author]; Davies, Christopher J. [Author]; Ruprecht, Daniel [Author]; Tobias, Steven M. [Author]; Oishi, Jeffrey S. [Author]
Corporation: Technische Universität Hamburg ; Technische Universität Hamburg, Institut für Mathematik
Published: 23 September 2020
Published in: Computing and visualization in science ; 23 (2020), 1-4, Article number 10, insgesamt 13 Seiten
Language: English
DOI: 10.15480/882.3048; 10.1007/s00791-020-00332-3
Identifier:

Keywords: Parallel-in-time ; Parareal ; Rayleigh–Bénard
Origination:
Footnote: Sonstige Körperschaft: Technische Universität Hamburg
Sonstige Körperschaft: Technische Universität Hamburg, Institut für Mathematik
Description: © 2020, The Author(s). Rayleigh–Bénard convection (RBC) is a fundamental problem of fluid dynamics, with many applications to geophysical, astrophysical, and industrial flows. Understanding RBC at parameter regimes of interest requires complex physical or numerical experiments. Numerical simulations require large amounts of computational resources; in order to more efficiently use the large numbers of processors now available in large high performance computing clusters, novel parallelisation strategies are required. To this end, we investigate the performance of the parallel-in-time algorithm Parareal when used in numerical simulations of RBC. We present the first parallel-in-time speedups for RBC simulations at finite Prandtl number. We also investigate the problem of convergence of Parareal with respect to statistical numerical quantities, such as the Nusselt number, and discuss the importance of reliable online stopping criteria in these cases.
Access State: Open Access
Rights information: Attribution (CC BY)

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