Paper Info
Title
Algorithms for Hessenberg-Triangular Reduction of Fiedler Linearization of Matrix Polynomials
Abstract
Small- to medium-sized polynomial eigenvalue problems can be solved by linearizing the matrix polynomial and solving the resulting generalized eigenvalue problem using the QZ algorithm. The QZ algorithm, in turn, requires an initial reduction of a matrix pair to Hessenberg-triangular (HT) form. In this paper, we discuss the design and evaluation of high-performance parallel algorithms and software for HT reduction of a specific linearization of matrix polynomials of arbitrary degree. The proposed algorithm exploits the sparsity structure of the linearization to reduce the number of operations and improve the cache reuse compared to existing algorithms for unstructured inputs. Experiments on both a workstation and a high-performance computing system demonstrate that our structure-exploiting parallel implementation can outperform both the general LAPACK routine DGGHRD and the prototype implementation DGGHR3 of a general blocked algorithm.
Year
DOI
Venue
2015
10.1137/140970458
SIAM JOURNAL ON SCIENTIFIC COMPUTING
Keywords
DocType
Volume
Hessenberg-triangular reduction,polynomial eigenvalue problem,linearization,blocked algorithm,parallelization
Journal
37
Issue
ISSN
Citations 
3
1064-8275
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Lars Karlsson1515.16
Françoise Tisseur245558.80