A Robust Preconditioner With Low Memory
by
Requirements For Large
,
Michele Benzi
BibTeX
@MISC{Large_arobust,
author = {Requirements For Large and Michele Benzi},
title = {A Robust Preconditioner With Low Memory},
year = {}
}
OpenURL
Abstract
We describe a technique for constructing robust preconditioners for the CGNR method applied to the solution of large and sparse least squares problems. Our algorithm computes an incomplete LDL factorization of the normal equations matrix without the need to form the normal matrix itself. The preconditioner is reliable (pivot breakdowns cannot occur) and has low intermediate storage requirements. Numerical experiments illustrating the performance of the preconditioner are presented.







