School of Mathematics and Physics, University of Surrey, Guildford, GU2 7XH, UK
Lawrence Mitchell
independent researcher: Edinburgh, UK
Colin Cotter
Department of Mathematics, Imperial College London, London SW7 2AZ, UK
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Total article views: 3,194 (including HTML, PDF, and XML)
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3,194
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Cumulative views and downloads
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Total article views: 2,883 (including HTML, PDF, and XML)
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2,651
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2,883
61
105
HTML: 2,651
PDF: 181
XML: 51
Total: 2,883
BibTeX: 61
EndNote: 105
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Cumulative views and downloads
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Total article views: 311 (including HTML, PDF, and XML)
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302
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311
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Total: 311
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Cumulative views and downloads
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Viewed (geographical distribution)
Since the preprint corresponding to this journal article was posted outside of Copernicus Publications, the preprint-related metrics are limited to HTML views.
Total article views: 3,194 (including HTML, PDF, and XML)
Thereof 3,082 with geography defined
and 112 with unknown origin.
Total article views: 2,883 (including HTML, PDF, and XML)
Thereof 2,789 with geography defined
and 94 with unknown origin.
Total article views: 311 (including HTML, PDF, and XML)
Thereof 293 with geography defined
and 18 with unknown origin.
Parallelization is important for speeding up complex geoscientific
models. In addition to spatial parallelization, several parallel-in-time
(PinT) methods have been developed. This paper introduces the reader to
PinT methods for hyperbolic and geophysical models, and it presents the
asQ library which facilitates the implementation of
diagonalization-based (ParaDiag) methods.
Parallelization is important for speeding up complex geoscientific
models. In addition to...
Effectively using modern supercomputers requires massively parallel algorithms. Time-parallel algorithms calculate the system state (e.g. the atmosphere) at multiple times simultaneously and have exciting potential but are tricky to implement and still require development. We have developed software to simplify implementing and testing the ParaDiag algorithm on supercomputers. We show that for some atmospheric problems it can enable faster or more accurate solutions than traditional techniques.
Effectively using modern supercomputers requires massively parallel algorithms. Time-parallel...