A transformation approach that makes SPAI, PSAI and RSAI procedures efficient for large double irregular nonsymmetric sparse linear systems
A transformation approach that makes SPAI, PSAI and RSAI procedures efficient for large double irregular nonsymmetric sparse linear systems
复制标题
一种使 SPAI、PSAI 和 RSAI 过程对于大型双不规则非对称稀疏线性系统有效的变换方法
DOI:
10.1016/j.cam.2018.08.033
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发表时间:
2015-12
影响因子:
2.4
通讯作者:
Kang Wenjie
中科院分区:
文献类型:
--
作者:
Jia Zhongxiao;Kang Wenjie
A sparse matrix is called double irregular sparse if it has at least one relatively dense column and row, and it is double regular sparse if all the columns and rows of it are sparse. The sparse approximate inverse preconditioning procedures SPAI, PSAI (t o l) and RSAI (t o l) are costly and even impractical to construct preconditioners for a large sparse nonsymmetric linear system with the coefficient matrix being double irregular sparse, but they are efficient for double regular sparse problems. Double irregular sparse linear systems have a wide range of applications, and 24.4% of the nonsymmetric matrices in the Florida University collection are double irregular sparse. For this class of problems, we propose a transformation approach, which consists of four steps:(i) transform a given double irregular sparse problem into a small number of double regular sparse ones with the same coefficient matrix A ˆ,(ii) use SPAI, PSAI (t o l) and RSAI (t o l) to construct sparse approximate inverses M of A ˆ,(iii) solve the preconditioned double regular sparse linear systems by Krylov solvers, and (iv) recover an approximate solution of the original problem with a prescribed accuracy from those of the double regular sparse ones. A number of theoretical and practical issues are considered on the transformation approach. Numerical experiments on a number of real-world problems confirm the very sharp superiority of the transformation approach to the standard approach that preconditions the original double irregular sparse problem by SPAI, PSAI (t o l) or RSAI (t o l) and solves the resulting preconditioned system by Krylov solvers.
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DOI:
10.1137/120900800
发表时间:
2012-11
期刊:
SIAM J. Sci. Comput.
影响因子:
--
作者:
Zhongxiao Jia;Qian Zhang
通讯作者:
Zhongxiao Jia;Qian Zhang
DOI:
10.1137/s1064827595294691
发表时间:
1998-05
期刊:
SIAM J. Sci. Comput.
影响因子:
--
作者:
M. Benzi;M. Tuma
通讯作者:
M. Benzi;M. Tuma
影响因子:
3.1
作者:
José MarÍn José Mas Rafael Bru-José-MarÍn-José-Mas-Rafael-Bru-102872903;M. T. Uring;Ma
通讯作者:
José MarÍn José Mas Rafael Bru-José-MarÍn-José-Mas-Rafael-Bru-102872903;M. T. Uring;Ma
影响因子:
1.8
作者:
M. Benson;J. Krettmann;M. Wright
通讯作者:
M. Benson;J. Krettmann;M. Wright
DOI:
--
发表时间:
1999
期刊:
--
影响因子:
--
作者:
S. Barnard;M. Grote
通讯作者:
S. Barnard;M. Grote