Title
A comparison of preconditioned nonsymmetric Krylov methods on a large-scale MIMD machine
Abstract
Many complex physical processes are modeled by coupled systems of partial differential equations (PDEs). Often, the numerical approximation of these PDEs requires the solution of large sparse nonsymmetric systems of equations. In this paper the authors compare the parallel performance of a number of preconditioned Krylov subspace methods on a large-scale multiple instruction multiple data (MIMD) machine. These methods are among the most robust and efficient iterative algorithms tor the solution of large sparse linear systems. In this comparison, the focus is on parallel issues associated with preconditioners within the generalized minimum residual (GMRES). conjugate gradient squared (CGS), biconjugate gradient stabilized (Bi-CGSTAB), and quasi-minimal residual CGS (QMRCGS) methods. Conclusions are drawn on the effectiveness of the different schemes based on results obtained from a 1024 processor nCUBE 2 hypercube.
Year
DOI
Venue
1994
10.1137/0915030
SIAM Journal on Scientific Computing
Keywords
Field
DocType
LINEAR SYSTEMS,NONSYMMETRIC,PARALLEL ALGORITHMS,KRYLOV METHODS,PRECONDITIONERS,MULTILEVEL METHODS,MIMD
Krylov subspace,Mathematical optimization,Generalized minimal residual method,Biconjugate gradient stabilized method,Linear system,System of linear equations,Parallel algorithm,Iterative method,Computer science,MIMD
Journal
Volume
Issue
ISSN
15
2
1064-8275
Citations 
PageRank 
References 
10
2.42
7
Authors
2
Name
Order
Citations
PageRank
John N. Shadid125932.24
Ray S. Tuminaro244738.09