Efficient multigrid reduction-in-time for method-of-lines discretizations of linear advection

TL;DR

This paper analyzes the performance of multigrid reduction-in-time (MGRIT) for linear advection problems, identifies convergence issues with standard coarse-grid approaches, and proposes an improved method that achieves faster convergence and parallel speed-up.

Contribution

The paper introduces a new coarse-grid operator for MGRIT that improves convergence for advection problems, addressing limitations of standard rediscretization methods.

Findings

Standard coarse-grid approach fails to ensure robust convergence.

The proposed semi-Lagrangian coarse-grid operator improves convergence.

Numerical experiments show substantial parallel speed-up.

Abstract

Parallel-in-time methods for partial differential equations (PDEs) have been the subject of intense development over recent decades, particularly for diffusion-dominated problems. It has been widely reported in the literature, however, that many of these methods perform quite poorly for advection-dominated problems. Here we analyze the particular iterative parallel-in-time algorithm of multigrid reduction-in-time (MGRIT) for discretizations of constant-wave-speed linear advection problems. We focus on common method-of-lines discretizations that employ upwind finite differences in space and Runge-Kutta methods in time. Using a convergence framework we developed in previous work, we prove for a subclass of these discretizations that, if using the standard approach of rediscretizing the fine-grid problem on the coarse grid, robust MGRIT convergence with respect to CFL number and coarsening factor is not possible. This poor convergence and non-robustness is caused, at least in part, by an inadequate coarse-grid correction for smooth Fourier modes known as characteristic components.We propose an alternative coarse-grid that provides a better correction of these modes. This coarse-grid operator is related to previous work and uses a semi-Lagrangian discretization combined with an implicitly treated truncation error correction. Theory and numerical experiments show the coarse-grid operator yields fast MGRIT convergence for many of the method-of-lines discretizations considered, including for both implicit and explicit discretizations of high order. Parallel results demonstrate substantial speed-up over sequential time-stepping.