Parallel spectral division using the matrix sign function for the generalized eigenproblem
Publication
, Journal Article
Huss-Lederman, S; Quintana-ORTÍ, ES; Sun, X; Wu, YJY
Published in: International Journal of High Speed Computing
December 1, 2000
In this paper we demonstrate the parallelism of the spectral division using the matrix sign function for the generalized nonsymmetric eigenproblem. We employ the so-called generalized Newton iterative scheme in order to compute the sign function of the matrix pair. A recent study showed a considerable reduction (by 75%) in the computational cost of this iteration, making this approach competitive when compared to the traditional QZ algorithm. The experimental results on an IBM SP3 multicomputer report the parallel performance (efficiency around 60-80%) and scalability of this approach.
Duke Scholars
Published In
International Journal of High Speed Computing
DOI
ISSN
0129-0533
Publication Date
December 1, 2000
Volume
11
Issue
1
Start / End Page
1 / 14
Related Subject Headings
- Distributed Computing
- 4606 Distributed computing and systems software
- 0805 Distributed Computing
Citation
APA
Chicago
ICMJE
MLA
NLM
Huss-Lederman, S., Quintana-ORTÍ, E. S., Sun, X., & Wu, Y. J. Y. (2000). Parallel spectral division using the matrix sign function for the generalized eigenproblem. International Journal of High Speed Computing, 11(1), 1–14. https://doi.org/10.1142/S0129053300000084
Huss-Lederman, S., E. S. Quintana-ORTÍ, X. Sun, and Y. J. Y. Wu. “Parallel spectral division using the matrix sign function for the generalized eigenproblem.” International Journal of High Speed Computing 11, no. 1 (December 1, 2000): 1–14. https://doi.org/10.1142/S0129053300000084.
Huss-Lederman S, Quintana-ORTÍ ES, Sun X, Wu YJY. Parallel spectral division using the matrix sign function for the generalized eigenproblem. International Journal of High Speed Computing. 2000 Dec 1;11(1):1–14.
Huss-Lederman, S., et al. “Parallel spectral division using the matrix sign function for the generalized eigenproblem.” International Journal of High Speed Computing, vol. 11, no. 1, Dec. 2000, pp. 1–14. Scopus, doi:10.1142/S0129053300000084.
Huss-Lederman S, Quintana-ORTÍ ES, Sun X, Wu YJY. Parallel spectral division using the matrix sign function for the generalized eigenproblem. International Journal of High Speed Computing. 2000 Dec 1;11(1):1–14.
Published In
International Journal of High Speed Computing
DOI
ISSN
0129-0533
Publication Date
December 1, 2000
Volume
11
Issue
1
Start / End Page
1 / 14
Related Subject Headings
- Distributed Computing
- 4606 Distributed computing and systems software
- 0805 Distributed Computing