Description

Book Synopsis

This book describes, in a basic way, the most useful and effective iterative solvers and appropriate preconditioning techniques for some of the most important classes of large and sparse linear systems.

The solution of large and sparse linear systems is the most time-consuming part for most of the scientific computing simulations. Indeed, mathematical models become more and more accurate by including a greater volume of data, but this requires the solution of larger and harder algebraic systems. In recent years, research has focused on the efficient solution of large sparse and/or structured systems generated by the discretization of numerical models by using iterative solvers.



Trade Review

The book can be used for a Master and/or Ph.D. level graduate course in science and engineering and can be useful to researchers from any eld of engineering, health, physical, chemical and biological sciences.

-Constantin Popa, Zentralblatt MATH



Table of Contents

Introduction and Motivations; Some iterative algorithms for linear systems; General purpose preconditioning strategies; Preconditioners for some structured linear systems; Appendix A: A Review of Numerical Linear Algebra; Appendix B: Data sets and software codes

Iterative Methods and Preconditioning for Large

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    A Hardback by Daniele Bertaccini, Fabio Durastante

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      Book details

      Publisher Taylor & Francis Inc
      Published 1/28/2018 12:02:00 AM
      ISBN-13 9781498764162
      978-1498764162
      ISBN-10 1498764169
      Also in:
      Algebra Applied mathematics

      Description

      Book Synopsis

      This book describes, in a basic way, the most useful and effective iterative solvers and appropriate preconditioning techniques for some of the most important classes of large and sparse linear systems.

      The solution of large and sparse linear systems is the most time-consuming part for most of the scientific computing simulations. Indeed, mathematical models become more and more accurate by including a greater volume of data, but this requires the solution of larger and harder algebraic systems. In recent years, research has focused on the efficient solution of large sparse and/or structured systems generated by the discretization of numerical models by using iterative solvers.



      Trade Review

      The book can be used for a Master and/or Ph.D. level graduate course in science and engineering and can be useful to researchers from any eld of engineering, health, physical, chemical and biological sciences.

      -Constantin Popa, Zentralblatt MATH



      Table of Contents

      Introduction and Motivations; Some iterative algorithms for linear systems; General purpose preconditioning strategies; Preconditioners for some structured linear systems; Appendix A: A Review of Numerical Linear Algebra; Appendix B: Data sets and software codes

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