An evaluation of reordering algorithms to reduce the computational cost of the incomplete Cholesky-conjugate gradient method

被引:18
|
作者
Gonzaga de Oliveira, Sanderson L. [1 ]
Bernardes, J. A. B. [1 ]
Chagas, G. O. [1 ]
机构
[1] Univ Fed Lavras, Lavras, Brazil
来源
COMPUTATIONAL & APPLIED MATHEMATICS | 2018年 / 37卷 / 03期
关键词
Bandwidth reduction; Profile reduction; Combinatorial optimization; Heuristics; Metaheuristics; Reordering algorithms; Sparse matrices; Renumbering; Ordering; Graph labeling; Conjugate gradient method; Graph algorithm; Sparse symmetric positive-definite linear systems; Incomplete Cholesky factorization; ICCG METHOD; PROFILE; BANDWIDTH; FACTORIZATION; PERFORMANCE; MATRICES; IMPLEMENTATION; PRECONDITIONER; ORDERINGS; EQUATIONS;
D O I
10.1007/s40314-017-0490-5
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
This paper is concerned with applying bandwidth and profile reduction reordering algorithms prior to computing an incomplete Cholesky factorization and using this as a preconditioner for the conjugate gradient method. Hundreds of reordering algorithms have been proposed to solve the problems of bandwidth and profile reductions since the mid-1960s. In previous publications, a large range of heuristics for bandwidth and/or profile reductions was reviewed. Based on this experience, 13 heuristics were selected as the most promising methods. These are evaluated in this paper along with a variant of the breadth-first search procedure that is proposed. Numerical results confirm the effectiveness of this modified reordering algorithm for linear systems derived from specific application areas. Moreover, the most promising heuristics for several application areas are identified when reducing the computational cost of the incomplete Cholesky-conjugate gradient method.
引用
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页码:2965 / 3004
页数:40
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