Title
Generalized Filtering Decomposition
Abstract
This paper introduces a new preconditioning technique that is suitable for matrices arising from the discretization of a system of PDEs on unstructured grids. The preconditioner satisfies a so-called filtering property, which ensures that the input matrix is identical with the preconditioner on a given filtering vector. This vector is chosen to alleviate the effect of low frequency modes on convergence and so decrease or eliminate the plateau which is often observed in the convergence of iterative methods. In particular, the paper presents a general approach that allows to ensure that the filtering condition is satisfied in a matrix decomposition. The input matrix can have an arbitrary sparse structure. Hence, it can be reordered using nested dissection, to allow a parallel computation of the preconditioner and of the iterative process.
Year
Venue
Keywords
2011
Clinical Orthopaedics and Related Research
low frequency,satisfiability,matrix decomposition,numerical analysis,parallel computer,iteration method,unstructured grid,preconditioning
Field
DocType
Volume
Discrete mathematics,Discretization,Mathematical optimization,Preconditioner,Iterative method,Matrix (mathematics),Matrix decomposition,Filter (signal processing),Nested dissection,Generalized filtering,Mathematics
Journal
abs/1103.3
Citations 
PageRank 
References 
0
0.34
2
Authors
2
Name
Order
Citations
PageRank
Laura Grigori136834.76
Frédéric Nataf224829.13