PCG reference manual: A package for the iterative solution of large sparse linear systems on parallel computers. Version 1.0
Author(s) -
Wayne Joubert,
Graham F. Carey,
Himani Kohli,
Alfred Lorber,
Robert McLay,
Yishan Shen,
N.A. Berner,
A. Kalhan
Publication year - 1995
Publication title -
osti oai (u.s. department of energy office of scientific and technical information)
Language(s) - English
Resource type - Reports
DOI - 10.2172/409864
Subject(s) - conjugate gradient method , computer science , linear system , matrix free methods , system of linear equations , discretization , code (set theory) , iterative method , sparse matrix , computational science , biconjugate gradient method , linear algebra , linear equation , partial differential equation , parallel computing , matrix (chemical analysis) , algorithm , conjugate residual method , mathematics , programming language , artificial intelligence , set (abstract data type) , mathematical analysis , physics , geometry , materials science , quantum mechanics , gradient descent , artificial neural network , composite material , gaussian
PCG (Preconditioned Conjugate Gradient package) is a system for solving linear equations of the form Au = b, for A a given matrix and b and u vectors. PCG, employing various gradient-type iterative methods coupled with preconditioners, is designed for general linear systems, with emphasis on sparse systems such as these arising from discretization of partial differential equations arising from physical applications. It can be used to solve linear equations efficiently on parallel computer architectures. Much of the code is reusable across architectures and the package is portable across different systems; the machines that are currently supported is listed. This manual is intended to be the general-purpose reference describing all features of the package accessible to the user; suggestions are also given regarding which methods to use for a given problem
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