A class of incomplete orthogonal factorization methods. I: Methods and theories

被引:40
作者
Bai, ZZ
Duff, IS
Wathen, AJ
机构
[1] Chinese Acad Sci, State Key Lab Sci Engn Comp, Inst Computat Math & Sci Engn Comp, Beijing 100080, Peoples R China
[2] Rutherford Appleton Lab, Atlas Ctr, Chilton OX11 0QD, Oxon, England
[3] Univ Oxford, Comp Lab, Oxford OX1 3QD, England
来源
BIT | 2001年 / 41卷 / 01期
基金
中国国家自然科学基金; 英国工程与自然科学研究理事会;
关键词
preconditioning; linear systems; sparse least squares; modified Gram-Schmidt orthogonalization; Givens rotations; incomplete orthogonal factorizations;
D O I
10.1023/A:1021913700691
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
We present a class of incomplete orthogonal factorization methods based on Givens rotations for large sparse unsymmetric matrices. These methods include: Incomplete Givens Orthogonalization (IGO-method) and its generalisation (GIGO-method), which drop entries from the incomplete orthogonal and upper triangular factors by position; Threshold Incomplete Givens Orthogonalization (TIGO(tau)-method), which drops entries dynamically by their magnitudes; and its generalisation (GTIGO(tau; p)-method), which drops entries dynamically by both their magnitudes and positions. Theoretical analyses show that these methods can produce a nonsingular sparse incomplete upper triangular factor and either a complete orthogonal factor or a sparse nonsingular incomplete orthogonal factor for a general nonsingular matrix. Therefore, these methods can potentially generate efficient preconditioners for Krylov subspace methods for solving large sparse systems of linear equations. Moreover, the upper triangular factor is an incomplete Cholesky factorization preconditioner for the normal equations matrix from least-squares problems.
引用
收藏
页码:53 / 70
页数:18
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