Title
Implicit-Factorization Preconditioning and Iterative Solvers for Regularized Saddle-Point Systems
Abstract
We consider conjugate-gradient like methods for solving block symmetric indefinite linear systems that arise from saddle-point problems or, in particular, regularizations thereof. Such methods require preconditioners that preserve certain sub-blocks from the original systems but allow considerable flexibility for the remaining blocks. We construct a number of families of implicit factorizations that are capable of reproducing the required sub-blocks and (some) of the remainder. These generalize known implicit factorizations for the unregularized case. Improved eigenvalue clustering is possible if additionally some of the noncrucial blocks are reproduced. Numerical experiments confirm that these implicit-factorization preconditioners can be very effective in practice.
Year
DOI
Venue
2006
10.1137/05063427X
SIAM J. Matrix Analysis Applications
Keywords
Field
DocType
regularized saddle-point systems,implicit-factorization preconditioners,implicit factorization,indefinite linear system,certain sub-blocks,block symmetric,implicit-factorization preconditioning,iterative solvers,numerical experiment,noncrucial block,required sub-blocks,improved eigenvalue clustering,considerable flexibility,eigenvalues,conjugate gradient,linear system,saddle point
Conjugate gradient method,Saddle,Mathematical optimization,Saddle point,Linear system,Iterative method,Symmetric matrix,Factorization,Block matrix,Mathematics
Journal
Volume
Issue
ISSN
28
1
0895-4798
Citations 
PageRank 
References 
23
1.58
20
Authors
4
Name
Order
Citations
PageRank
H. Sue Dollar1985.43
Nicholas I. M. Gould21445123.86
Wil H. A. Schilders3597.00
Andrew J. Wathen479665.47