Performance of parallel-in-time integration for Rayleigh Bénard convection
Citation Link: https://doi.org/10.15480/882.3048
Publikationstyp
Journal Article
Date Issued
2020-09-23
Sprache
English
Institut
TORE-DOI
TORE-URI
Volume
23
Issue
1-4
Article Number
10
Citation
Computing and Visualization in Science 1-4 (23): 10 (2020)
Publisher DOI
Scopus ID
Publisher
Springer
© 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.
Subjects
Parallel-in-time
Parareal
Rayleigh–Bénard
DDC Class
510: Mathematik
More Funding Information
Engineering and Physical Sciences Research Council (EPSRC) Centre for Doctoral Training in Fluid Dynamics
Natural Environment Research Council (NERC) Independent Research Fellowship
NASA LWS
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