English

Parallel performance of shared memory parallel spectral deferred corrections

Computational Engineering, Finance, and Science 2026-03-04 v3 Distributed, Parallel, and Cluster Computing Numerical Analysis Numerical Analysis

Abstract

We investigate the parallel performance of Parallel Spectral Deferred corrections, a numerical approach that provides small-scale parallelism for the numerical solution of initial value problems. The scheme is applied to the shallow-water equation and uses an implicit-explicit splitting that, in order to be efficient, integrates fast modes implicitly and slow modes explicitly. We describe parallel \OpenMP-based implementations of parallel Spectral Deferred Corrections for two well established simulation codes: the finite volume based operational ocean model \ICON and the spherical harmonics based research code \SWEET. We also develop a performance model and benchmark our implementations on a single node of the JUSUF (\SWEET) and JUWELS (\ICON) system at J\"ulich Supercomputing Centre. A reduction of time-to-solution across a range of accuracies is demonstrated. For \ICON, we show speedup over the currently used Adams--Bashforth-2 integrator with \OpenMP loop parallelization. For \SWEET, we show speedup over serial Spectral Deferred Corrections and a second order implicit-explicit integrator.

Keywords

Cite

@article{arxiv.2403.20135,
  title  = {Parallel performance of shared memory parallel spectral deferred corrections},
  author = {Philip Freese and Sebastian Götschel and Thibaut Lunet and Daniel Ruprecht and Martin Schreiber},
  journal= {arXiv preprint arXiv:2403.20135},
  year   = {2026}
}

Comments

21 pages, 5 figures

R2 v1 2026-06-28T15:38:15.982Z