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Parallel iterative solution of sparse linear systems using orderings from graph coloring heuristics
Author(s) -
Mark T. Jones,
Paul E. Plassmann
Publication year - 1990
Language(s) - English
Resource type - Reports
DOI - 10.2172/10148824
Subject(s) - conjugate gradient method , heuristics , cholesky decomposition , incomplete cholesky factorization , mathematics , combinatorics , graph coloring , conjugate , adjacency matrix , graph , computer science , algorithm , mathematical optimization , mathematical analysis , eigenvalues and eigenvectors , physics , quantum mechanics
The efficiency of a parallel implementation of the conjugate gradient method preconditioned by an incomplete Cholesky factorization can vary dramatically depending on the column ordering chosen. One method to minimize the number of major parallel steps is to choose an ordering based on a coloring of the symmetric graph representing the nonzero adjacency structure of the matrix. In this paper, we compare the performance of the preconditioned conjugate gradient method using these coloring orderings with a number of standard orderings on matrices arising from applications in structural engineering. Because optimal colorings for these systems may not be a priori known: we employ several graph coloring heuristics to obtain consistent colorings. Based on lower bounds obtained from the local structure of these systems, we find that the colorings determined by these heuristics are nearly optimal. For these problems, we find that the increase in parallelism afforded by the coloring-based orderings more than offsets any increase in the number of iterations required for the convergence of the conjugate gradient algorithm.

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