Multilevel Block Factorization Preconditioners


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Multilevel Block Factorization Preconditioners


Multilevel Block Factorization Preconditioners

Author: Panayot S. Vassilevski

language: en

Publisher: Springer Science & Business Media

Release Date: 2008-10-22


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This monograph is the first to provide a comprehensive, self-contained and rigorous presentation of some of the most powerful preconditioning methods for solving finite element equations in a common block-matrix factorization framework. The book covers both algorithms and analysis using a common block-matrix factorization approach which emphasizes its unique feature. Topics covered include the classical incomplete block-factorization preconditioners, the most efficient methods such as the multigrid, algebraic multigrid, and domain decomposition. This text can serve as an indispensable reference for researchers, graduate students, and practitioners. It can also be used as a supplementary text for a topics course in preconditioning and/or multigrid methods at the graduate level.

Efficient Preconditioned Solution Methods for Elliptic Partial Differential Equations


Efficient Preconditioned Solution Methods for Elliptic Partial Differential Equations

Author: Owe Axelsson

language: en

Publisher: Bentham Science Publishers

Release Date: 2011


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This e-book presents several research areas of elliptical problems solved by differential equations. The mathematical models explained in this e-book have been contributed by experts in the field and can be applied to a wide range of real life examples. M

Preconditioning and the Conjugate Gradient Method in the Context of Solving PDEs


Preconditioning and the Conjugate Gradient Method in the Context of Solving PDEs

Author: Josef Malek

language: en

Publisher: SIAM

Release Date: 2014-12-22


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Preconditioning and the Conjugate Gradient Method in the Context of Solving PDEs is about the interplay between modeling, analysis, discretization, matrix computation, and model reduction. The authors link PDE analysis, functional analysis, and calculus of variations with matrix iterative computation using Krylov subspace methods and address the challenges that arise during formulation of the mathematical model through to efficient numerical solution of the algebraic problem. The book?s central concept, preconditioning of the conjugate gradient method, is traditionally developed algebraically using the preconditioned finite-dimensional algebraic system. In this text, however, preconditioning is connected to the PDE analysis, and the infinite-dimensional formulation of the conjugate gradient method and its discretization and preconditioning are linked together. This text challenges commonly held views, addresses widespread misunderstandings, and formulates thought-provoking open questions for further research.