Parallel Algorithms For Numerical Linear Algebra

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Parallel Algorithms For Numerical Linear Algebra

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Author : H. van der Vorst
language : en
Publisher: Elsevier
Release Date : 2014-06-28

Parallel Algorithms For Numerical Linear Algebra written by H. van der Vorst and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-28 with Computers categories.

This is the first in a new series of books presenting research results and developments concerning the theory and applications of parallel computers, including vector, pipeline, array, fifth/future generation computers, and neural computers.All aspects of high-speed computing fall within the scope of the series, e.g. algorithm design, applications, software engineering, networking, taxonomy, models and architectural trends, performance, peripheral devices.Papers in Volume One cover the main streams of parallel linear algebra: systolic array algorithms, message-passing systems, algorithms for parallel shared-memory systems, and the design of fast algorithms and implementations for vector supercomputers.

Numerical Linear Algebra Digital Signal Processing And Parallel Algorithms

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Author : Gene H. Golub
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Numerical Linear Algebra Digital Signal Processing And Parallel Algorithms written by Gene H. Golub and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.

Numerical linear algebra, digital signal processing, and parallel algorithms are three disciplines with a great deal of activity in the last few years. The interaction between them has been growing to a level that merits an Advanced Study Institute dedicated to the three areas together. This volume gives an account of the main results in this interdisciplinary field. The following topics emerged as major themes of the meeting: - Singular value and eigenvalue decompositions, including applications, - Toeplitz matrices, including special algorithms and architectures, - Recursive least squares in linear algebra, digital signal processing and control, - Updating and downdating techniques in linear algebra and signal processing, - Stability and sensitivity analysis of special recursive least squares problems, - Special architectures for linear algebra and signal processing. This book contains tutorials on these topics given by leading scientists in each of the three areas. A consider- able number of new research results are presented in contributed papers. The tutorials and papers will be of value to anyone interested in the three disciplines.

Special Issue On Parallel Algorithms For Numerical Linear Algebra

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Author :
language : en
Publisher:
Release Date : 1989

Special Issue On Parallel Algorithms For Numerical Linear Algebra written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1989 with Algebras, Linear categories.

Parallel Algorithms For Matrix Computations

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Author : K. Gallivan
language : en
Publisher: SIAM
Release Date : 1990-01-01

Parallel Algorithms For Matrix Computations written by K. Gallivan and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990-01-01 with Mathematics categories.

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.

Parallel Algorithms For Numerical Linear Algebra On A Shared Memory Multiprocessor

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Author : Dogan Kaya
language : en
Publisher:
Release Date : 1995

Parallel Algorithms For Numerical Linear Algebra On A Shared Memory Multiprocessor written by Dogan Kaya and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with categories.

Parallel Numerical Linear Algebra

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Author : J. J. Dongarra
language : en
Publisher: Nova Science Publishers
Release Date : 2001

Parallel Numerical Linear Algebra written by J. J. Dongarra and has been published by Nova Science Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Computers categories.

Contents: A Java-Based Distributed Debugger Supporting MPI and PVM; On Encoding Neural Networks to Estimate the Atmospheric Point Spread Function in a Parallel Environment; A Comparison of Parallel Solvers for Diagonally Dominant and General Narrow-Banded Linear Systems; Mapping Strategies in Data Parallel Programming Models; the Projection Methods; Parallel Multiplication of a Vector by a Kronecker Product of Matrices; Parallel Sparse Matrix Algorithms for Air Pollution Models; Band Preconditioners -- Application to Preconditioned Conjugate Gradient Methods on Parallel Computers.

A Survey Of Parallel Algorithms In Numerical Linear Algebra

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Author : Don Heller
language : en
Publisher:
Release Date : 1976

A Survey Of Parallel Algorithms In Numerical Linear Algebra written by Don Heller and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1976 with Algebras, Linear categories.

The existence of parallel and pipeline computers has inspired a new approach to algorithmic analysis. Classical numerical methods are generally unable to exploit multiple processors and powerful vector-oriented hardware. Efficient parallel algorithms can be created by reformulating familiar algorithms or by discovering new ones, and the results are often surprising. A comprehensive survey of parallel techniques for problems in linear algebra is given. Specific topics include: relevant computer models and their consequences, evaluation of ubiquitous arithmetic expressions, solution of linear systems of equations, and computation of eigenvalues.

Parallel Algorithms For Linear Models

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Author : Erricos Kontoghiorghes
language : en
Publisher: Springer Science & Business Media
Release Date : 2000-01-31

Parallel Algorithms For Linear Models written by Erricos Kontoghiorghes and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-01-31 with Business & Economics categories.

Parallel Algorithms for Linear Models provides a complete and detailed account of the design, analysis and implementation of parallel algorithms for solving large-scale linear models. It investigates and presents efficient, numerically stable algorithms for computing the least-squares estimators and other quantities of interest on massively parallel systems. The monograph is in two parts. The first part consists of four chapters and deals with the computational aspects for solving linear models that have applicability in diverse areas. The remaining two chapters form the second part, which concentrates on numerical and computational methods for solving various problems associated with seemingly unrelated regression equations (SURE) and simultaneous equations models. The practical issues of the parallel algorithms and the theoretical aspects of the numerical methods will be of interest to a broad range of researchers working in the areas of numerical and computational methods in statistics and econometrics, parallel numerical algorithms, parallel computing and numerical linear algebra. The aim of this monograph is to promote research in the interface of econometrics, computational statistics, numerical linear algebra and parallelism.

Introduction To Parallel Algorithms

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Author : C. Xavier
language : en
Publisher: John Wiley & Sons
Release Date : 1998-08-05

Introduction To Parallel Algorithms written by C. Xavier and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-08-05 with Computers categories.

Parallel algorithms Made Easy The complexity of today's applications coupled with the widespread use of parallel computing has made the design and analysis of parallel algorithms topics of growing interest. This volume fills a need in the field for an introductory treatment of parallel algorithms-appropriate even at the undergraduate level, where no other textbooks on the subject exist. It features a systematic approach to the latest design techniques, providing analysis and implementation details for each parallel algorithm described in the book. Introduction to Parallel Algorithms covers foundations of parallel computing; parallel algorithms for trees and graphs; parallel algorithms for sorting, searching, and merging; and numerical algorithms. This remarkable book: * Presents basic concepts in clear and simple terms * Incorporates numerous examples to enhance students' understanding * Shows how to develop parallel algorithms for all classical problems in computer science, mathematics, and engineering * Employs extensive illustrations of new design techniques * Discusses parallel algorithms in the context of PRAM model * Includes end-of-chapter exercises and detailed references on parallel computing. This book enables universities to offer parallel algorithm courses at the senior undergraduate level in computer science and engineering. It is also an invaluable text/reference for graduate students, scientists, and engineers in computer science, mathematics, and engineering.

Parallelism In Matrix Computations

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Author : Efstratios Gallopoulos
language : en
Publisher: Springer
Release Date : 2015-07-25

Parallelism In Matrix Computations written by Efstratios Gallopoulos and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07-25 with Technology & Engineering categories.

This book is primarily intended as a research monograph that could also be used in graduate courses for the design of parallel algorithms in matrix computations. It assumes general but not extensive knowledge of numerical linear algebra, parallel architectures, and parallel programming paradigms. The book consists of four parts: (I) Basics; (II) Dense and Special Matrix Computations; (III) Sparse Matrix Computations; and (IV) Matrix functions and characteristics. Part I deals with parallel programming paradigms and fundamental kernels, including reordering schemes for sparse matrices. Part II is devoted to dense matrix computations such as parallel algorithms for solving linear systems, linear least squares, the symmetric algebraic eigenvalue problem, and the singular-value decomposition. It also deals with the development of parallel algorithms for special linear systems such as banded ,Vandermonde ,Toeplitz ,and block Toeplitz systems. Part III addresses sparse matrix computations: (a) the development of parallel iterative linear system solvers with emphasis on scalable preconditioners, (b) parallel schemes for obtaining a few of the extreme eigenpairs or those contained in a given interval in the spectrum of a standard or generalized symmetric eigenvalue problem, and (c) parallel methods for computing a few of the extreme singular triplets. Part IV focuses on the development of parallel algorithms for matrix functions and special characteristics such as the matrix pseudospectrum and the determinant. The book also reviews the theoretical and practical background necessary when designing these algorithms and includes an extensive bibliography that will be useful to researchers and students alike. The book brings together many existing algorithms for the fundamental matrix computations that have a proven track record of efficient implementation in terms of data locality and data transfer on state-of-the-art systems, as well as several algorithms that are presented for the first time, focusing on the opportunities for parallelism and algorithm robustness.