Iterative Methods for Sparse Linear Systems

Häftad, Engelska, 2003

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Tremendous progress has been made in the scientific and engineering disciplines regarding the use of iterative methods for linear systems. The size and complexity of linear and nonlinear systems arising in typical applications has grown, meaning that using direct solvers for the three-dimensional models of these problems is no longer effective. At the same time, parallel computing, becoming less expensive and standardized, has penetrated these application areas. Iterative methods are easier than direct solvers to implement on parallel computers but require approaches and solution algorithms that are different from classical methods. This second edition gives an in-depth, up-to-date view of practical algorithms for solving large-scale linear systems of equations, including a wide range of the best methods available today. A new chapter on multigrid techniques has been added, whilst material throughout has been updated, removed or shortened. Numerous exercises have been added, as well as an updated and expanded bibliography.

Produktinformation

Utgivningsdatum2003-04-30
Mått177 x 251 x 30 mm
Vikt943 g
FormatHäftad
SpråkEngelska
Antal sidor546
Upplaga2
FörlagSociety for Industrial & Applied Mathematics,U.S.
ISBN9780898715347

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Yousef Saad joined the University of Minnesota in 1990 as a Professor of Computer Science and a Fellow of the Minnesota Supercomputer Institute. He was head of the Department of Computer Science and Engineering from 1997 to 2000. He received the Doctorat d'Etat from the University of Grenoble (France) in 1983. His current research interests include numerical linear algebra, sparse matrix computations, iterative methods, parallel computing, and numerical methods for eigenvalue problems.

Preface to the Second Edition Preface to the First Edition Chapter 1: Background in Linear Algebra Chapter 2: Discretization of Partial Differential Equations Chapter 3: Sparse Matrices Chapter 4: Basic Iterative Methods Chapter 5: Projection Methods Chapter 6: Krylov Subspace Methods, Part I Chapter 7: Krylov Subspace Methods, Part II Chapter 8: Methods Related to the Normal Equations Chapter 9: Preconditioned Iterations Chapter 10: Preconditioning Techniques Chapter 11: Parallel Implementations Chapter 12: Parallel Preconditioners Chapter 13: Multigrid Methods Chapter 14: Domain Decomposition Methods Bibliography Index