Matrix Computations
Matrix Computations

Author: Gene H. Golub

Publisher: JHU Press

Published: 2013-02-15

Total Pages: 781

ISBN-13: 1421408597

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A comprehensive treatment of numerical linear algebra from the standpoint of both theory and practice. The fourth edition of Gene H. Golub and Charles F. Van Loan's classic is an essential reference for computational scientists and engineers in addition to researchers in the numerical linear algebra community. Anyone whose work requires the solution to a matrix problem and an appreciation of its mathematical properties will find this book to be an indispensible tool. This revision is a cover-to-cover expansion and renovation of the third edition. It now includes an introduction to tensor computations and brand new sections on • fast transforms • parallel LU • discrete Poisson solvers • pseudospectra • structured linear equation problems • structured eigenvalue problems • large-scale SVD methods • polynomial eigenvalue problems Matrix Computations is packed with challenging problems, insightful derivations, and pointers to the literature—everything needed to become a matrix-savvy developer of numerical methods and software. The second most cited math book of 2012 according to MathSciNet, the book has placed in the top 10 for since 2005.

Computer Solution of Large Linear Systems
Computer Solution of Large Linear Systems

Author: Gerard Meurant

Publisher: Elsevier

Published: 1999-06-16

Total Pages: 777

ISBN-13: 0080529518

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This book deals with numerical methods for solving large sparse linear systems of equations, particularly those arising from the discretization of partial differential equations. It covers both direct and iterative methods. Direct methods which are considered are variants of Gaussian elimination and fast solvers for separable partial differential equations in rectangular domains. The book reviews the classical iterative methods like Jacobi, Gauss-Seidel and alternating directions algorithms. A particular emphasis is put on the conjugate gradient as well as conjugate gradient -like methods for non symmetric problems. Most efficient preconditioners used to speed up convergence are studied. A chapter is devoted to the multigrid method and the book ends with domain decomposition algorithms that are well suited for solving linear systems on parallel computers.

Numerical Linear Algebra for High-performance Computers
Numerical Linear Algebra for High-performance Computers

Author: Jack J. Dongarra

Publisher: SIAM

Published: 1998-01-01

Total Pages: 360

ISBN-13: 9780898719611

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This book presents a unified treatment of recently developed techniques and current understanding about solving systems of linear equations and large scale eigenvalue problems on high-performance computers. It provides a rapid introduction to the world of vector and parallel processing for these linear algebra applications. Topics include major elements of advanced-architecture computers and their performance, recent algorithmic development, and software for direct solution of dense matrix problems, direct solution of sparse systems of equations, iterative solution of sparse systems of equations, and solution of large sparse eigenvalue problems.

Templates for the Solution of Linear Systems
Templates for the Solution of Linear Systems

Author: Richard Barrett

Publisher: SIAM

Published: 1994-01-01

Total Pages: 141

ISBN-13: 9781611971538

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In this book, which focuses on the use of iterative methods for solving large sparse systems of linear equations, templates are introduced to meet the needs of both the traditional user and the high-performance specialist. Templates, a description of a general algorithm rather than the executable object or source code more commonly found in a conventional software library, offer whatever degree of customization the user may desire. Templates offer three distinct advantages: they are general and reusable; they are not language specific; and they exploit the expertise of both the numerical analyst, who creates a template reflecting in-depth knowledge of a specific numerical technique, and the computational scientist, who then provides "value-added" capability to the general template description, customizing it for specific needs. For each template that is presented, the authors provide: a mathematical description of the flow of algorithm; discussion of convergence and stopping criteria to use in the iteration; suggestions for applying a method to special matrix types; advice for tuning the template; tips on parallel implementations; and hints as to when and why a method is useful.

Iterative Methods for Sparse Linear Systems
Iterative Methods for Sparse Linear Systems

Author: Yousef Saad

Publisher: SIAM

Published: 2003-01-01

Total Pages: 546

ISBN-13: 9780898718003

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Since the first edition of this book was published in 1996, 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 the new generation of linear and nonlinear systems arising in typical applications has grown. Solving the three-dimensional models of these problems using direct solvers is no longer effective. At the same time, parallel computing has penetrated these application areas as it became less expensive and standardized. Iterative methods are easier than direct solvers to implement on parallel computers but require approaches and solution algorithms that are different from classical methods. Iterative Methods for Sparse Linear Systems, Second Edition gives an in-depth, up-to-date view of practical algorithms for solving large-scale linear systems of equations. These equations can number in the millions and are sparse in the sense that each involves only a small number of unknowns. The methods described are iterative, i.e., they provide sequences of approximations that will converge to the solution.

Parallel Algorithms for Matrix Computations
Parallel Algorithms for Matrix Computations

Author: K. Gallivan

Publisher: SIAM

Published: 1990-01-01

Total Pages: 207

ISBN-13: 9781611971705

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Describes a selection of important parallel algorithms for matrix computations. Reviews the current status and provides an overall perspective of parallel algorithms for solving problems arising in the major areas of numerical linear algebra, including (1) direct solution of dense, structured, or sparse linear systems, (2) dense or structured least squares computations, (3) dense or structured eigenvaluen and singular value computations, and (4) rapid elliptic solvers. The book emphasizes computational primitives whose efficient execution on parallel and vector computers is essential to obtain high performance algorithms. Consists of two comprehensive survey papers on important parallel algorithms for solving problems arising in the major areas of numerical linear algebra--direct solution of linear systems, least squares computations, eigenvalue and singular value computations, and rapid elliptic solvers, plus an extensive up-to-date bibliography (2,000 items) on related research.

High Performance Computing for Computational Science - VECPAR 2002
High Performance Computing for Computational Science - VECPAR 2002

Author: José M.L.M. Palma

Publisher: Springer

Published: 2003-08-03

Total Pages: 732

ISBN-13: 3540365699

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The 5th edition of the VECPAR series of conferences marked a change of the conference title. The full conference title now reads VECPAR 2002 — 5th Int- national Conference on High Performance Computing for Computational S- ence. This re?ects more accurately what has been the main emphasis of the conference since its early days in 1993 – the use of computers for solving pr- lems in science and engineering. The present postconference book includes the best papers and invited talks presented during the three days of the conference, held at the Faculty of Engineering of the University of Porto (Portugal), June 26–28 2002. The book is organized into 8 chapters, which as a whole appeal to a wide research community, from those involved in the engineering applications to those interested in the actual details of the hardware or software implementation, in line with what, in these days, tends to be considered as Computational Science and Engineering (CSE). The book comprises a total of 49 papers, with a prominent position reserved for the four invited talks and the two ?rst prizes of the best student paper competition.