Methods For Increasing Domains Of Convergence In Iterative Linear System Solvers

<p>In this thesis, we introduce and improve various methods for increasing the domains of convergence for iterative linear system solvers. We rely on the following three approaches: making the iteration adaptive, or nesting an inner iteration inside of a previously determined outer iteration; using deflation and projections to manipulate the spectra inherent to the iteration; and/or focusing on reordering schemes. We will analyze a specific combination of these three strategies. In particular, we propose to examine the influence of nesting a Flexible Generalized Minimum Residual algorithm together with an inner Recursive Projection Method using a banded preconditioner resulting from the Fiedler reordering.</p>

Name thesis:degree_name

Doctor of Philosophy (PhD)

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Mathematics

Year

2013

Author dc:creator

• Imberti, David Michael

Contributors dc:contributor

• Ahmed Sameh
• Jianlin Xia
• Zhiqiang Cai
• Bradley Lucier

• pure sciences
• applied sciences
• flexible generalized minimum residual algorithm
• fiedler
• generalized minimum residual algorithm
• nested convergence
• recursive projection method
• Computer Sciences
• Mathematics

Repository record dc:identifier

https://docs.lib.purdue.edu/open_access_dissertations/127

OAI identifier oai:identifier

oai:docs.lib.purdue.edu:open_access_dissertations-1088