Solution of Nonsymmetric Systems of Equations on a Multiprocessor
Kamath, Chandrika
This item is only available for download by members of the University of Illinois community. Students, faculty, and staff at the U of I may log in with your NetID and password to view the item. If you are trying to access an Illinois-restricted dissertation or thesis, you can request a copy through your library's Inter-Library Loan office or purchase a copy directly from ProQuest.
Permalink
https://hdl.handle.net/2142/69560
Description
Title
Solution of Nonsymmetric Systems of Equations on a Multiprocessor
Author(s)
Kamath, Chandrika
Issue Date
1986
Department of Study
Computer Science
Discipline
Computer Science
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Computer Science
Abstract
We consider the iterative solution of large sparse linear systems of equations arising from elliptic and parabolic partial differential equations in two and three space dimensions. Specifically, we focus our attention on non-symmetric systems of equations whose eigenvalues lie on both sides of the imaginary axis, or whose symmetric part is not positive definite. This system of equations is solved using the projection methods with conjugate gradient acceleration. The algorithm has been designed with special emphasis on its suitability for multiprocessors.
In the first part of the thesis, we study the numerical properties of the algorithm and compare its performance with other algorithms such as the conjugate gradient method on the normal equations, the Chebyshev method, Orthomin(k), GCR(k) and GMRES(k). We also study the effect of various preconditioners on these methods. In the second part of the thesis, we implement our algorithm on the CRAY X-MP/48 multiprocessor and study its behavior as the number of processors is increased.
Use this login method if you
don't
have an
@illinois.edu
email address.
(Oops, I do have one)
IDEALS migrated to a new platform on June 23, 2022. If you created
your account prior to this date, you will have to reset your password
using the forgot-password link below.