Asymptotic convergence of the parallel full approximation scheme in space and time for linear problems. Issue 6 (14th August 2018)

• Record Type: Journal Article
• Authors: Bolten, Matthias; Moser, Dieter; Speck, Robert
• Other Names: Benner Peter guestEditor.; Faßbender Heike guestEditor.; Grasedyck Lars guestEditor.; Kressner Daniel guestEditor.; Meini Beatrice guestEditor.; Simoncini Valeria guestEditor.
• Is Part Of: Numerical linear algebra with applications. Volume 25:Issue 6(2018)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-08-14
• Subjects: asymptotic convergence -- matrix permutation -- multigrid -- parallel‐in‐time -- PFASST -- smoothing and approximation property; Algebras, Linear -- Periodicals; 512.5
• DOI: 10.1002/nla.2208
• Languages: English
• ISSNs: 1070-5325

Abstract

Summary: For time‐dependent partial differential equations, parallel‐in‐time integration using the "parallel full approximation scheme in space and time" (PFASST) is a promising way to accelerate existing space‐parallel approaches beyond their scaling limits. Inspired by the classical Parareal method and multigrid ideas, PFASST allows to integrate multiple time steps simultaneously using a space–time hierarchy of spectral deferred correction sweeps. While many use cases and benchmarks exist, a solid and reliable mathematical foundation is still missing. Very recently, however, PFASST for linear problems has been identified as a multigrid method. In this paper, we will use this multigrid formulation and, in particular, PFASST's iteration matrix to show that, in the nonstiff and stiff limit, PFASST indeed is a convergent iterative method. We will provide upper bounds for the spectral radius of the iteration matrix and investigate how PFASST performs for increasing numbers of parallel time steps. Finally, we will demonstrate that the results obtained here indeed relate to actual PFASST runs.