The impact of parallel architectures on the solution of eigenvalue problems

Ilse C.F. Ipsen, Youcef Saad

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

This paper presents a short survey of recent work on parallel implementations of Numerical Linear Algebra algorithms with emphasis on those relating to the solution of the symmetric eigenvalue problem on loosely coupled multiprocessor architectures. The vital operations in the formulation of most eigenvalue algorithms are matrix vector multiplication, matrix transposition, and linear system solution. Their implementations on several representative multiprocessor systems will be described, as well as parallel implementations of the following classes of eigenvalue methods : QR, bisection, divide-and-conquer, and Lanczos algorithm.

Original languageEnglish (US)
Pages (from-to)37-49
Number of pages13
JournalNorth-Holland Mathematics Studies
Volume127
Issue numberC
DOIs
StatePublished - Jan 1986

Bibliographical note

Funding Information:
The work presented in this paper was supported by the Office of Naval Research under contracts N000014-82-K-0184 and N00014-85-K-0461.

Fingerprint

Dive into the research topics of 'The impact of parallel architectures on the solution of eigenvalue problems'. Together they form a unique fingerprint.

Cite this