Solving Large-Scale Eigenvalue Problems on Vector Parallel Processors

Solving Large-Scale Eigenvalue Problems on Vector Parallel Processors

We consider the development and implementation of eigensolvers on distributed memory parallel arrays of vector processors and show that the concomitant requirements for vectorisation and parallelisation lead both to novel algorithms and novel implementation techniques. Performance results are given...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Harrar, David L., Osborne, Michael R.
Format: Buchkapitel
Sprache:eng
Schlagworte:
Applied sciences
Arnoldi Method
Computer science
control theory
systems
Eigenvalue Problem
Exact sciences and technology
Inverse Iteration
Simulation
Software
Tridiagonal Matrix
Vector Length
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:We consider the development and implementation of eigensolvers on distributed memory parallel arrays of vector processors and show that the concomitant requirements for vectorisation and parallelisation lead both to novel algorithms and novel implementation techniques. Performance results are given for several large-scale applications and some performance comparisons made with LAPACK and ScaLAPACK.
ISSN:0302-9743
1611-3349
DOI:10.1007/10703040_9