Householder transformation for the regularized least square problem on iPSC/860

Author

Zhu, Jianping

Author_Institution

Eng. Res. Center for Comput. Field Simulations, Mississippi State Univ., MS, USA

fYear

1992

fDate

23-26 Mar 1992

Firstpage

433

Lastpage

436

Abstract

Discusses a householder factorization algorithm for a special type of matrix arising from the application of the Tikhnov regularization method to an ill-conditioned least square problem. The matrix involved is half dense and half sparse. The algorithm has been implemented on iPSC/860 hypercubes. By overlapping communications with computations, the code has been optimized to take advantage of the special structure of the matrix and minimize inter-node communications. Super-linear speed-up was observed in the numerical experiment for large problems. The algorithm has been used as a core routine in the program solving parameter identification problems in reservoir simulations

Keywords

least squares approximations; matrix algebra; parallel algorithms; Tikhnov regularization method; half dense matrix; half sparse matrix; householder factorization algorithm; householder transformation; iPSC/860 hypercubes; ill-conditioned least square problem; parameter identification; regularized least square problem; reservoir simulations; super linear speed up; Computational modeling; Concurrent computing; Distributed computing; Equations; Hypercubes; Least squares methods; Numerical stability; Parameter estimation; Reservoirs; Sparse matrices;

fLanguage

English

Publisher

ieee

Conference_Titel

Parallel Processing Symposium, 1992. Proceedings., Sixth International

Conference_Location

Beverly Hills, CA

Print_ISBN

0-8186-2672-0

Type

conf

DOI

10.1109/IPPS.1992.223007

Filename

223007