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A parallel software package for solving linear systems

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4 Author(s)
Scarbnick, C.D. ; San Diego Supercomput. Center, CA, USA ; Chang, M.C. ; Schultz, M.H. ; Sherman, A.B.

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

Published in:

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

Date of Conference:

19-21 Oct 1992

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