On "Optimal" h-Independent Convergence of Parareal and MGRIT using Runge-Kutta Time Integration
Stephanie Friedhoff, Ben S. Southworth

TL;DR
This paper analyzes the convergence properties of Parareal and MGRIT algorithms with Runge-Kutta methods, establishing conditions for optimality and demonstrating the impact of different schemes on convergence rates for linear PDEs.
Contribution
It provides a theoretical framework for understanding $h$-independent convergence of Parareal and MGRIT with Runge-Kutta schemes, including analysis of modified algorithms and operator types.
Findings
L-stable Runge-Kutta schemes yield better convergence.
Not all schemes achieve $h$-independent convergence.
Numerical results validate theoretical predictions.
Abstract
Although convergence of the Parareal and multigrid-reduction-in-time (MGRIT) parallel-in-time algorithms is well studied, results on their optimality is limited. Appealling to recently derived tight bounds of two-level Parareal and MGRIT convergence, this paper proves (or disproves) - and -independent convergence of two-level Parareal and MGRIT, for linear problems of the form , where is symmetric positive definite and Runge-Kutta time integration is used. The theory presented in this paper also encompasses analysis of some modified Parareal algorithms, such as the -Parareal method, and shows that not all Runge-Kutta schemes are equal from the perspective of parallel-in-time. Some schemes, particularly L-stable methods, offer significantly better convergence than others as they are guaranteed to converge…
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Taxonomy
TopicsNumerical methods for differential equations · Advanced Numerical Methods in Computational Mathematics · Matrix Theory and Algorithms
