Squeezing the most out of eigenvalue solvers on high-performance computers
type: Item
instance of: scholarly article
title: Squeezing the most out of eigenvalue solvers on high-performance computers
zbMATH Open document ID: 0587.65027
DOI: 10.1016/0024-3795(86)90164-3
author: Jack Dongarra
author: Linda Kaufman
author: S. Hammarling
published in: Linear Algebra and its Applications
publication date: 1986-01-01T00:00:00Z
review text: This paper describes modifications to many of the standard algorithms used in computing eigenvalues and eigenvectors of matrices. These modifications can dramatically increase the performance of the underlying software on high-performance computers without resorting to assembler language, without significantly influencing the floating-point operation count, and without affecting the roundoff-error properties of the algorithms. The techniques are applied to a wide variety of algoritms and are beneficial in various architectural settings.
Mathematics Subject Classification ID: 65F15
zbMATH DE Number: 3942912
zbMATH Keywords: high-performance vector computers
zbMATH Keywords: eigenvalues
zbMATH Keywords: eigenvectors
describes a project that uses: EISPACK
MaRDI profile type: Publication
full work available at URL: 0024-3795(86)90164-3
OpenAlex ID: W2002991695
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description: scientific article; zbMATH DE number 3942912