Parallel-in-Time Solver for the All-at-Once Runge–Kutta Discretization

In this article, we derive fast and robust preconditioned iterative methods for the all-at-once linear systems arising upon discretization of time-dependent PDEs. The discretization we employ is based on a Runge--Kutta method in time, for which the development of robust solvers is an emerging research area in the literature of numerical methods for time-dependent PDEs. By making use of classical theory of block matrices, one is able to derive a preconditioner for the systems considered. An approximate inverse of the preconditioner so derived consists in a fixed number of linear solves for the system of the stages of the method. We thus propose a preconditioner for the latter system based on a singular value decomposition (SVD) of the (real) Runge--Kutta matrix $A_{\mathrm{RK}} = U \Sigma V^\top$. Supposing $A_{\mathrm{RK}}$ is invertible, we prove that the spectrum of the system for the stages preconditioned by our SVD-based preconditioner is contained within the right-half of the unit circle, under suitable assumptions on the matrix $U^\top V$ (which is well defined due to the polar decomposition of $A_{\mathrm{RK}}$). We show the numerical efficiency of our SVD-based preconditioner by solving the system of the stages arising from the discretization of the heat equation and the Stokes equations, with sequential time-stepping. Finally, we provide numerical results of the all-at-once approach for both problems.

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Publication Details

Journal
SIAM Journal on Matrix Analysis and Applications
Published
2024-10-14
DOI
https://doi.org/10.1137/23m1567862
Citations
7
Primary Topic
Numerical methods for differential equations
Type
article
Field-Weighted Citation Impact
5.13

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article

Parallel-in-Time Solver for the All-at-Once Runge–Kutta Discretization

John W. Pearson, Ángeles Martínez, Santolo Leveque, Luca Bergamaschi
7 citations
SIAM Journal on Matrix Analysis and Applications
Numerical methods for differential equations
5.13
article

Parallel-in-Time Solver for the All-at-Once Runge–Kutta Discretization

John W. Pearson, Ángeles Martínez, Santolo Leveque, Luca Bergamaschi
article en
7 citations

Abstract

In this article, we derive fast and robust preconditioned iterative methods for the all-at-once linear systems arising upon discretization of time-dependent PDEs. The discretization we employ is based on a Runge--Kutta method in time, for which the development of robust solvers is an emerging research area in the literature of numerical methods for time-dependent PDEs. By making use of classical theory of block matrices, one is able to derive a preconditioner for the systems considered. An approximate inverse of the preconditioner so derived consists in a fixed number of linear solves for the system of the stages of the method. We thus propose a preconditioner for the latter system based on a singular value decomposition (SVD) of the (real) Runge--Kutta matrix $A_{\mathrm{RK}} = U \Sigma V^\top$. Supposing $A_{\mathrm{RK}}$ is invertible, we prove that the spectrum of the system for the stages preconditioned by our SVD-based preconditioner is contained within the right-half of the unit circle, under suitable assumptions on the matrix $U^\top V$ (which is well defined due to the polar decomposition of $A_{\mathrm{RK}}$). We show the numerical efficiency of our SVD-based preconditioner by solving the system of the stages arising from the discretization of the heat equation and the Stokes equations, with sequential time-stepping. Finally, we provide numerical results of the all-at-once approach for both problems.

SIAM Journal on Matrix Analysis and ApplicationsVol. 45(4)
University of Padua (IT), University of Trieste (IT), Scuola Normale Superiore (IT), Maxwell Institute for Mathematical Sciences (GB)
Istituto Nazionale di Alta Matematica "Francesco Severi", Horizon 2020 Framework Programme, Gruppo Nazionale per il Calcolo Scientifico, Engineering and Physical Sciences Research Council
Openalex Percentile: Top 4%
Numerical methods for differential equations
5.13
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