An Analysis of Reordering Algorithms to Reduce the Computational Cost of the Jacobi-Preconditioned CG Solver Using High-Precision Arithmetic

被引：2

作者：

Gonzaga de Oliveira, Sanderson L. ^{[1
]}

Chagas, Guilherme Oliveira ^{[2
]}

Barreto Bernardes, Junior Assis ^{[1
]}

机构：

[1] Univ Fed Lavras, Lavras, MG, Brazil

[2] Inst Nacl Pesquisas Espaciais, Sao Paulo, Brazil

来源：

COMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2017, PT I | 2017年 / 10404卷

关键词：

Bandwidth reduction; Profile reduction; Conjugate Gradient Method; Graph labeling; Reordering algorithms; Sparse matrices; Graph algorithm; High-precision arithmetic; Ordering; Sparse symmetric positive-definite linear systems; Combinatorial optimization; Heuristics; BANDWIDTH; PROFILE; MATRICES; SEARCH;

D O I：

10.1007/978-3-319-62392-4_1

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Several heuristics for bandwidth and profile reductions have been proposed since the 1960s. In systematic reviews, 133 heuristics applied to these problems have been found. The results of these heuristics have been analyzed so that, among them, 13 were selected in a manner that no simulation or comparison showed that these algorithms could be outperformed by any other algorithm in the publications analyzed, in terms of bandwidth or profile reductions and also considering the computational costs of the heuristics. Therefore, these 13 heuristics were selected as the most promising low-cost methods to solve these problems. Based on this experience, this article reports that in certain cases no heuristic for bandwidth or profile reduction can reduce the computational cost of the Jacobi-preconditioned Conjugate Gradient Method when using high-precision numerical computations.

引用

下载

页码：3 / 19

页数：17