A parallel software package for solving linear systems

Author

Scarbnick, Carl D. ; Chang, Mark C. ; Schultz, Martin H. ; Sherman, Andrew B.

Author_Institution

San Diego Supercomput. Center, CA, USA

fYear

1992

fDate

19-21 Oct 1992

Firstpage

397

Lastpage

401

Abstract

A problem arising in scientific computation is the solution of Ax=b, where A is a large, sparse matrix. One of the most robust algorithms for solving the above equation is the conjugate gradient method, especially when combined with a preconditioner. The authors discuss a new software package, MP-PCGPAK2, that implements a parallel version of the conjugate gradient method for MIMD (multiple-instruction multiple-data), message passing architectures. The parallel implementation is quite general and can be applied to algorithms for nonsymmetric or indefinite systems such as GMRES, Bi-CGSTAB, and QMR. The authors present results on a 1024 processor nCUBE 2, and a 128 processor iPSC/860, for positive definite, symmetric systems ranging from one million to over 11 million variables

Keywords

conjugate gradient methods; mathematics computing; parallel architectures; parallel programming; software packages; Bi-CGSTAB; GMRES; MIMD; MP-PCGPAK2; QMR; conjugate gradient method; iPSC/860; linear systems; message passing architectures; nCUBE 2; parallel software package; preconditioner; scientific computation; sparse matrix; symmetric systems; Computer architecture; Data structures; Finite difference methods; Gradient methods; Linear systems; Packaging; Poisson equations; Scheduling; Software packages; Sparse matrices;

fLanguage

English

Publisher

ieee

Conference_Titel

Frontiers of Massively Parallel Computation, 1992., Fourth Symposium on the

Conference_Location

McLean, VA

Print_ISBN

0-8186-2772-7

Type

conf

DOI

10.1109/FMPC.1992.234934

Filename

234934