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An Adaptive Multilevel Factorized Sparse Approximate Inverse Preconditioning

SYSNO ASEP	0473670
Document Type	J - Journal Article
R&D Document Type	Journal Article
Subsidiary J	Článek ve WOS
Title	An Adaptive Multilevel Factorized Sparse Approximate Inverse Preconditioning
Author(s)	Kopal, Jiří (UIVT-O)_{RID, SAI} Rozložník, Miroslav (UIVT-O)_{SAI, RID, ORCID} Tůma, Miroslav (UIVT-O)_{SAI, RID, ORCID}
Source Title	Advances in Engineering Software. - : Elsevier - ISSN 0965-9978 Roč. 113, November (2017), s. 19-24
Number of pages	6 s.
Language	eng - English
Country	NL - Netherlands
Keywords	approximate inverse ; Gram–Schmidt orthogonalization ; incomplete factorization ; multilevel methods ; preconditioned conjugate gradient method
Subject RIV	BA - General Mathematics
OECD category	Applied mathematics
R&D Projects	GA13-06684S GA ČR - Czech Science Foundation (CSF)
Institutional support	UIVT-O - RVO:67985807
UT WOS	000413675600004
EID SCOPUS	85002488023
DOI	10.1016/j.advengsoft.2016.10.005
Annotation	This paper deals with adaptively preconditioned iterative methods for solving large and sparse systems of linear equations. In particular, the paper discusses preconditioning where adaptive dropping reflects the quality of preserving the relation UZ=I, where U and Z are the triangular factors of A and its inverse, respectively. The proposed strategy significantly extends and refines the previously developed approach, by using a specific multilevel framework. Numerical experiments with two levels demonstrate that the new preconditioning strategy is very promising. Namely, we show a surprising fact that in our approach the Schur complement is better to form in a more sophisticated way than by a standard sparse matrix-matrix multiplication.
Workplace	Institute of Computer Science
Contact	Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800
Year of Publishing	2018

Number of the records: 1