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Parallel Algorithms for Matrix Computations

Parallel Algorithms for Matrix Computations PDF Author: K. Gallivan
Publisher: SIAM
ISBN: 9781611971705
Category : Mathematics
Languages : en
Pages : 207

Book Description
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 Matrix Computations

Parallel Algorithms for Matrix Computations PDF Author: K. Gallivan
Publisher: SIAM
ISBN: 9781611971705
Category : Mathematics
Languages : en
Pages : 207

Book Description
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.

Parallelism in Matrix Computations

Parallelism in Matrix Computations PDF Author: Efstratios Gallopoulos
Publisher: Springer
ISBN: 940177188X
Category : Technology & Engineering
Languages : en
Pages : 489

Book Description
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.

Parallel Algorithms for Matrix Computations

Parallel Algorithms for Matrix Computations PDF Author:
Publisher:
ISBN:
Category : Algorithms
Languages : en
Pages : 197

Book Description


Parallel Algorithms and Matrix Computation

Parallel Algorithms and Matrix Computation PDF Author: Jagdish J. Modi
Publisher: Oxford University Press, USA
ISBN:
Category : Computers
Languages : en
Pages : 278

Book Description
An introduction to parallel computation and the application of parallel algorithms to numerical linear algebra, based on a lecture course at the University of Cambridge. The emphasis is on the design and analysis of algorithms which are of importance to industrial and academic research.

Parallel Algorithms and Matrix Computation

Parallel Algorithms and Matrix Computation PDF Author: Jagdish J. Modi
Publisher: Oxford University Press, USA
ISBN: 9780198596707
Category : Family & Relationships
Languages : en
Pages : 260

Book Description
One of the first textbooks on the topic, this book brings together and further articulates the fundamental concepts in parallel computing. It covers the application of parallel algorithms to numerical linear algebra, with an emphasis on the design and analysis of algorithms that are of particular importance in both industrial and academic research. The first part is devoted to a discussion of the general principles and techniques involved, and is illustrated by numerous examples. Dr. Modi goes on to describe some key areas of application, such as sorting, linear systems, partial differential equations, singular-value decomposition, and eigenvalue analysis. Based on a lecture course at the University of Cambridge, the text will appeal to those with an interest in the design and implementations of algorithms in parallel computing.

Matrix Computations

Matrix Computations PDF Author: Gene Howard Golub
Publisher:
ISBN: 9780801837395
Category : Matrices
Languages : en
Pages : 694

Book Description
Revised and updated, the third edition of Golub and Van Loan's classic text in computer science provides essential information about the mathematical background and algorithmic skills required for the production of numerical software. This new edition includes thoroughly revised chapters on matrix multiplication problems and parallel matrix computations, expanded treatment of CS decomposition, an updated overview of floating point arithmetic, a more accurate rendition of the modified Gram-Schmidt process, and new material devoted to GMRES, QMR, and other methods designed to handle the sparse unsymmetric linear system problem.

Parallel Algorithms in Computational Science and Engineering

Parallel Algorithms in Computational Science and Engineering PDF Author: Ananth Grama
Publisher: Springer Nature
ISBN: 3030437361
Category : Computers
Languages : en
Pages : 421

Book Description
This contributed volume highlights two areas of fundamental interest in high-performance computing: core algorithms for important kernels and computationally demanding applications. The first few chapters explore algorithms, numerical techniques, and their parallel formulations for a variety of kernels that arise in applications. The rest of the volume focuses on state-of-the-art applications from diverse domains. By structuring the volume around these two areas, it presents a comprehensive view of the application landscape for high-performance computing, while also enabling readers to develop new applications using the kernels. Readers will learn how to choose the most suitable parallel algorithms for any given application, ensuring that theory and practicality are clearly connected. Applications using these techniques are illustrated in detail, including: Computational materials science and engineering Computational cardiovascular analysis Multiscale analysis of wind turbines and turbomachinery Weather forecasting Machine learning techniques Parallel Algorithms in Computational Science and Engineering will be an ideal reference for applied mathematicians, engineers, computer scientists, and other researchers who utilize high-performance computing in their work.

Matrix Computations

Matrix Computations PDF Author: Gene H. Golub
Publisher: JHU Press
ISBN: 9780801854149
Category : Mathematics
Languages : en
Pages : 734

Book Description
Revised and updated, the third edition of Golub and Van Loan's classic text in computer science provides essential information about the mathematical background and algorithmic skills required for the production of numerical software. This new edition includes thoroughly revised chapters on matrix multiplication problems and parallel matrix computations, expanded treatment of CS decomposition, an updated overview of floating point arithmetic, a more accurate rendition of the modified Gram-Schmidt process, and new material devoted to GMRES, QMR, and other methods designed to handle the sparse unsymmetric linear system problem.

Parallel Algorithms for Regular Architectures

Parallel Algorithms for Regular Architectures PDF Author: Russ Miller
Publisher: MIT Press
ISBN: 9780262132336
Category : Architecture
Languages : en
Pages : 336

Book Description
Parallel-Algorithms for Regular Architectures is the first book to concentrate exclusively on algorithms and paradigms for programming parallel computers such as the hypercube, mesh, pyramid, and mesh-of-trees.

Parallel Scientific Computing and Optimization

Parallel Scientific Computing and Optimization PDF Author: Raimondas Ciegis
Publisher: Springer Science & Business Media
ISBN: 0387097074
Category : Mathematics
Languages : en
Pages : 287

Book Description
Parallel Scientific Computing and Optimization introduces new developments in the construction, analysis, and implementation of parallel computing algorithms. This book presents 23 self-contained chapters, including survey chapters and surveys, written by distinguished researchers in the field of parallel computing. Each chapter is devoted to some aspects of the subject: parallel algorithms for matrix computations, parallel optimization, management of parallel programming models and data, with the largest focus on parallel scientific computing in industrial applications. This volume is intended for scientists and graduate students specializing in computer science and applied mathematics who are engaged in parallel scientific computing.