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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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: 6,173 (including HTML, PDF, and XML)
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5,495
478
200
6,173
193
267
HTML: 5,495
PDF: 478
XML: 200
Total: 6,173
BibTeX: 193
EndNote: 267
Views and downloads (calculated since 09 Dec 2024)
Cumulative views and downloads
(calculated since 09 Dec 2024)
Total article views: 4,652 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
3,995
478
179
4,652
193
267
HTML: 3,995
PDF: 478
XML: 179
Total: 4,652
BibTeX: 193
EndNote: 267
Views and downloads (calculated since 25 Jul 2025)
Cumulative views and downloads
(calculated since 25 Jul 2025)
Total article views: 1,521 (including HTML, PDF, and XML)
HTML
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XML
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BibTeX
EndNote
1,500
0
21
1,521
0
0
HTML: 1,500
PDF: 0
XML: 21
Total: 1,521
BibTeX: 0
EndNote: 0
Views and downloads (calculated since 09 Dec 2024)
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: 6,173 (including HTML, PDF, and XML)
Thereof 6,006 with geography defined
and 167 with unknown origin.
Total article views: 4,652 (including HTML, PDF, and XML)
Thereof 4,489 with geography defined
and 163 with unknown origin.
Total article views: 1,521 (including HTML, PDF, and XML)
Thereof 1,517 with geography defined
and 4 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...