Preprints
https://doi.org/https://doi.org/10.48550/arXiv.2409.18792
https://doi.org/https://doi.org/10.48550/arXiv.2409.18792
09 Dec 2024
 | 09 Dec 2024
Status: this preprint is open for discussion.

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

Abstract. Modern high performance computers are massively parallel; for many PDE applications spatial parallelism saturates long before the computer’s capability is reached. Parallel-in-time methods enable further speedup beyond spatial saturation by solving multiple timesteps simultaneously to expose additional parallelism. ParaDiag is a particular approach to parallel-in-time based on preconditioning the simultaneous timestep system with a perturbation that allows block diagonalisation via a Fourier transform in time. In this article, we introduce asQ, a new library for implementing ParaDiag parallel-in-time methods, with a focus on applications in the geosciences, especially weather and climate. asQ is built on Firedrake, a library for the automated solution of finite element models, and the PETSc library of scalable linear and nonlinear solvers. This enables asQ to build ParaDiag solvers for general finite element models and provide a range of solution strategies, making testing a wide array of problems straightforward. We use a quasi-Newton formulation that encompasses a range of ParaDiag methods, and expose building blocks for constructing more complex methods. The performance and flexibility of asQ is demonstrated on a hierarchy of linear and nonlinear atmospheric flow models. We show that ParaDiag can offer promising speedups and that asQ is a productive testbed for further developing these methods.

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

Status: open (until 03 Feb 2025)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
Joshua Hope-Collins, Abdalaziz Hamdan, Werner Bauer, Lawrence Mitchell, and Colin Cotter

Model code and software

Python scripts for "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 https://doi.org/10.5281/zenodo.14198293

Singularity container for "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 https://doi.org/10.5281/zenodo.14198328

Software used in `asQ: parallel-in-time finite element simulations using ParaDiag for geoscientific models and beyond' Firedrake team https://doi.org/10.5281/zenodo.14205088

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: 37 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
37 0 0 37 0 0
  • HTML: 37
  • PDF: 0
  • XML: 0
  • Total: 37
  • BibTeX: 0
  • EndNote: 0
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: 33 (including HTML, PDF, and XML) Thereof 33 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 13 Dec 2024
Download
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.