205266
20181203023750.0
10.1137/140954817
doi
000346123200025
ISI
ARTICLE
A Parallel QZ Algorithm For Distributed Memory HPC Systems
Philadelphia
2014
Siam Publications
2014
24
Journal Articles
Appearing frequently in applications, generalized eigenvalue problems represent one of the core problems in numerical linear algebra. The QZ algorithm of Moler and Stewart is the most widely used algorithm for addressing such problems. Despite its importance, little attention has been paid to the parallelization of the QZ algorithm. The purpose of this work is to fill this gap. We propose a parallelization of the QZ algorithm that incorporates all modern ingredients of dense eigensolvers, such as multishift and aggressive early deflation techniques. To deal with (possibly many) infinite eigenvalues, a new parallel deflation strategy is developed. Numerical experiments for several random and application examples demonstrate the effectiveness of our algorithm on two different distributed memory HPC systems.
generalized eigenvalue problem
nonsymmetric QZ algorithm
multishift
bulge chasing
infinite eigenvalues
parallel algorithms
level 3 performance
aggressive early deflation
Adlerborn, Bjoern
Umea Univ, Dept Comp Sci, SE-90187 Umea, Sweden
Kagstroem, Bo
Umea Univ, Dept Comp Sci, SE-90187 Umea, Sweden
Kressner, Daniel
213191
246441
C480-C503
5
SIAM Journal On Scientific Computing
36
ANCHP
252494
U12478
oai:infoscience.tind.io:205266
article
SB
213191
EPFL-ARTICLE-205266
EPFL
PUBLISHED
REVIEWED
ARTICLE