Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 18, issue 14
Articles | Volume 18, issue 14
https://doi.org/10.5194/gmd-18-4535-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-18-4535-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18, issue 14
Model description paper
 | Highlight paper
 | 
25 Jul 2025
Model description paper | Highlight paper |  | 25 Jul 2025

asQ: parallel-in-time finite element simulations using ParaDiag for geoscientific models and beyond

Joshua Hope-Collins, Abdalaziz Hamdan, Werner Bauer, Lawrence Mitchell, and Colin Cotter

Viewed

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: 1,168 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,105 39 24 1,168 22 30
  • HTML: 1,105
  • PDF: 39
  • XML: 24
  • Total: 1,168
  • BibTeX: 22
  • EndNote: 30
Views and downloads (calculated since 09 Dec 2024)
Cumulative views and downloads (calculated since 09 Dec 2024)

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: 1,168 (including HTML, PDF, and XML) Thereof 1,168 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 09 Sep 2025
Download
Executive editor
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.
Read more
Short summary
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.
Read more
Share