Refined saddle-point preconditioners for discretized Stokes problems

This paper is concerned with the implementation of efficient solution algorithms for elliptic problems with constraints. We establish theory which shows that including a simple scaling within well-established block diagonal preconditioners for Stokes problems can result in significantly faster conve...

Descripción completa

Detalles Bibliográficos
Autores principales: Pearson, John W., Pestana, Jennifer, Silvester, David J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2017
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5775988/
https://www.ncbi.nlm.nih.gov/pubmed/29391651
http://dx.doi.org/10.1007/s00211-017-0908-4
_version_ 1783294001712988160
author Pearson, John W.
Pestana, Jennifer
Silvester, David J.
author_facet Pearson, John W.
Pestana, Jennifer
Silvester, David J.
author_sort Pearson, John W.
collection PubMed
description This paper is concerned with the implementation of efficient solution algorithms for elliptic problems with constraints. We establish theory which shows that including a simple scaling within well-established block diagonal preconditioners for Stokes problems can result in significantly faster convergence when applying the preconditioned MINRES method. The codes used in the numerical studies are available online.
format Online
Article
Text
id pubmed-5775988
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher Springer Berlin Heidelberg
record_format MEDLINE/PubMed
spelling pubmed-57759882018-01-30 Refined saddle-point preconditioners for discretized Stokes problems Pearson, John W. Pestana, Jennifer Silvester, David J. Numer Math (Heidelb) Article This paper is concerned with the implementation of efficient solution algorithms for elliptic problems with constraints. We establish theory which shows that including a simple scaling within well-established block diagonal preconditioners for Stokes problems can result in significantly faster convergence when applying the preconditioned MINRES method. The codes used in the numerical studies are available online. Springer Berlin Heidelberg 2017-07-25 2018 /pmc/articles/PMC5775988/ /pubmed/29391651 http://dx.doi.org/10.1007/s00211-017-0908-4 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Article
Pearson, John W.
Pestana, Jennifer
Silvester, David J.
Refined saddle-point preconditioners for discretized Stokes problems
title Refined saddle-point preconditioners for discretized Stokes problems
title_full Refined saddle-point preconditioners for discretized Stokes problems
title_fullStr Refined saddle-point preconditioners for discretized Stokes problems
title_full_unstemmed Refined saddle-point preconditioners for discretized Stokes problems
title_short Refined saddle-point preconditioners for discretized Stokes problems
title_sort refined saddle-point preconditioners for discretized stokes problems
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5775988/
https://www.ncbi.nlm.nih.gov/pubmed/29391651
http://dx.doi.org/10.1007/s00211-017-0908-4
work_keys_str_mv AT pearsonjohnw refinedsaddlepointpreconditionersfordiscretizedstokesproblems
AT pestanajennifer refinedsaddlepointpreconditionersfordiscretizedstokesproblems
AT silvesterdavidj refinedsaddlepointpreconditionersfordiscretizedstokesproblems

Ejemplares similares