This article surveys preconditioning techniques for the iterative solution of large linear
systems, with a focus on algebraic methods suitable for general sparse matrices. Covered …

The general method of graph coarsening or graph reduction has been a remarkably useful
and ubiquitous tool in scientific computing and it is now just starting to have a similar impact …

The aim of this book is to investigate the spectral properties of random matrices (RM) when
their dimensions tend to infinity. All classical limiting theorems in statistics are under the …

The idea for this book came from the time the authors spent at the Statistics and Applied
Mathematical Sciences Institute (SAMSI) in Research Triangle Park in North Carolina …

In the? rst edition of this book (publishedby Kluwer Academic in November 2000) the
methodology of dynamical systems theory was introduced and appli-cations of this theory to …

The solution of large sparse linear systems arises in many applications, such as
computational fluid dynamics and oil reservoir simulation. In realistic cases the matrices are …

Oceanic variability on interannual, interdecadal, and longer timescales plays a key role in
climate variability and climate change. Paleoclimatic records suggest major changes in the …

This chapter surveys the techniques that are necessary for constructing computationally
efficient parallel multigrid solvers. Both geometric and algebraic methods are considered …

We introduce block versions of the multielimination incomplete LU (ILUM) factorization
preconditioning technique for solving general sparse unstructured linear systems. These …

This paper describes a domain-based multilevel block ILU preconditioner (BILUTM) for
solving general sparse linear systems. This preconditioner combines a high accuracy …