NONLINEAR BDDC METHODS WITH APPROXIMATE SOLVERS - Kölner UniversitätsPublikationsServer

Klawonn, Axel ORCID: 0000-0003-4765-7387, Lanser, Martin and Rheinbach, Oliver ORCID: 0000-0002-9310-8533 (2018). NONLINEAR BDDC METHODS WITH APPROXIMATE SOLVERS. Electron. Trans. Numer. Anal., 49. S. 244 - 274. KENT: KENT STATE UNIVERSITY. ISSN 1068-9613

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DOI:10.1553/etna_vol49s244

Abstract

New nonlinear BDDC (Balancing Domain Decomposition by Constraints) domain decomposition methods using inexact solvers for the subdomains and the coarse problem are proposed. In nonlinear domain decomposition methods, the nonlinear problem is decomposed before linearization to improve concurrency and robustness. For linear problems, the new methods are equivalent to known inexact BDDC methods. The new approaches are therefore discussed in the context of other known inexact BDDC methods for linear problems. Relations are pointed out, and the advantages of the approaches chosen here are highlighted. For the new approaches, using an algebraic multigrid method as a building block, parallel scalability is shown for more than half a million (524 288) MPI ranks on the JUQUEEN IBM BG/Q supercomputer (JSC Julich, Germany) and on up to 193 600 cores of the Theta Xeon Phi supercomputer (ALCF, Argonne National Laboratory, USA), which is based on the recent Intel Knights Landing (KNL) many-core architecture. One of our nonlinear inexact BDDC domain decomposition methods is also applied to three-dimensional plasticity problems. Comparisons to standard Newton-Krylov-BDDC methods are provided.

Item Type:

Journal Article

Creators:

Creators	Email	ORCID	ORCID Put Code
Klawonn, Axel	UNSPECIFIED	orcid.org/0000-0003-4765-7387	UNSPECIFIED
Lanser, Martin	UNSPECIFIED	UNSPECIFIED	UNSPECIFIED
Rheinbach, Oliver	UNSPECIFIED	orcid.org/0000-0002-9310-8533	UNSPECIFIED