Parallel performance of an iterative solver based on the golub-kahan bidiagonalization

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Abstract

We present an iterative method based on a generalization of the Golub-Kahan bidiagonalization for solving indefinite matrices with a 2×2 block structure. We focus in particular on our recent implementation of the algorithm using the parallel numerical library PETSc. Since the algorithm is a nested solver, we investigate different choices for parallel inner solvers and show its strong scalability for two Stokes test problems. The algorithm is found to be scalable for large sparse problems.

Original languageEnglish
Title of host publicationParallel Processing and Applied Mathematics - 13th International Conference, PPAM 2019, Revised Selected Papers
EditorsRoman Wyrzykowski, Konrad Karczewski, Ewa Deelman, Jack Dongarra
PublisherSpringer
Pages104-116
Number of pages13
ISBN (Print)9783030432287
DOIs
Publication statusPublished - 1 Jan 2020
Externally publishedYes
Event13th International Conference on Parallel Processing and Applied Mathematics, PPAM 2019 - Bialystok, Poland
Duration: 8 Sept 201911 Sept 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12043 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference13th International Conference on Parallel Processing and Applied Mathematics, PPAM 2019
Country/TerritoryPoland
CityBialystok
Period8/09/1911/09/19

Keywords

  • Golub-Kahan bidiagonalization
  • Iterative solver
  • PETSc
  • Parallel performance

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