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Computing and Visualization in Science

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06.10.2017 | Original Article

Multigrid methods with space–time concurrency

verfasst von: R. D. Falgout, S. Friedhoff, Tz. V. Kolev, S. P. MacLachlan, J. B. Schroder, S. Vandewalle

Erschienen in: Computing and Visualization in Science | Ausgabe 4-5/2017

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Abstract

We consider the comparison of multigrid methods for parabolic partial differential equations that allow space–time concurrency. With current trends in computer architectures leading towards systems with more, but not faster, processors, space–time concurrency is crucial for speeding up time-integration simulations. In contrast, traditional time-integration techniques impose serious limitations on parallel performance due to the sequential nature of the time-stepping approach, allowing spatial concurrency only. This paper considers the three basic options of multigrid algorithms on space–time grids that allow parallelism in space and time: coarsening in space and time, semicoarsening in the spatial dimensions, and semicoarsening in the temporal dimension. We develop parallel software and performance models to study the three methods at scales of up to 16K cores and introduce an extension of one of them for handling multistep time integration. We then discuss advantages and disadvantages of the different approaches and their benefit compared to traditional space-parallel algorithms with sequential time stepping on modern architectures.

Vorheriger Artikel On the influence of the wall shear stress vector form on hemodynamic indicators

Nächster Artikel Error analysis in determining the centroids of circular objects in images

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Titel: Multigrid methods with space–time concurrency
verfasst von: R. D. Falgout
S. Friedhoff
Tz. V. Kolev
S. P. MacLachlan
J. B. Schroder
S. Vandewalle
Publikationsdatum: 06.10.2017
Verlag: Springer Berlin Heidelberg
Erschienen in: Computing and Visualization in Science / Ausgabe 4-5/2017
Print ISSN: 1432-9360
Elektronische ISSN: 1433-0369
DOI: https://doi.org/10.1007/s00791-017-0283-9

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