Title
Performance modeling of multishift QR algorithms for the parallel solution of symmetric tridiagonal eigenvalue problems
Abstract
Multishift QR algorithms are efficient for solving the symmetric tridiagonal eigenvalue problem on a parallel computer. In this paper, we focus on three variants of the multishift QR algorithm, namely, the conventional multishift QR algorithm, the deferred shift QR algorithm and the fully pipelined multishift QR algorithm, and construct performance models for them. Our models are designed for shared-memory parallel machines, and given the basic performance characteristics of the target machine and the problem size, predict the execution time of these algorithms. Experimental results show that our models can predict the relative performance of these algorithms to the accuracy of 10% in many cases. Thus our models are useful for choosing the best algorithm to solve a given problem in a specified computational environment, as well as for finding the best value of the performance parameters.
Year
DOI
Venue
2010
10.1007/978-3-642-13136-3_41
ICA3PP (2)
Keywords
Field
DocType
symmetric tridiagonal eigenvalue problem,problem size,conventional multishift qr algorithm,performance modeling,relative performance,best algorithm,multishift qr algorithm,parallel solution,performance parameter,performance model,deferred shift qr algorithm,basic performance characteristic,shared memory,parallel computer
Tridiagonal matrix,Computer science,Parallel computing,Algorithm,Execution time,Divide-and-conquer eigenvalue algorithm,Eigenvalues and eigenvectors,QR algorithm
Conference
Volume
ISSN
ISBN
6082
0302-9743
3-642-13135-2
Citations 
PageRank 
References 
0
0.34
5
Authors
3
Name
Order
Citations
PageRank
Takafumi Miyata111.39
Yusaku Yamamoto25220.61
Shao-Liang Zhang39219.06