Parallel Processing for Scientific Computing

Parallel Processing for Scientific Computing

Author: Michael A. Heroux

Publisher: SIAM

Published: 2006-01-01

Total Pages: 421

ISBN-13: 9780898718133

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Parallel processing has been an enabling technology in scientific computing for more than 20 years. This book is the first in-depth discussion of parallel computing in 10 years; it reflects the mix of topics that mathematicians, computer scientists, and computational scientists focus on to make parallel processing effective for scientific problems. Presently, the impact of parallel processing on scientific computing varies greatly across disciplines, but it plays a vital role in most problem domains and is absolutely essential in many of them. Parallel Processing for Scientific Computing is divided into four parts: The first concerns performance modeling, analysis, and optimization; the second focuses on parallel algorithms and software for an array of problems common to many modeling and simulation applications; the third emphasizes tools and environments that can ease and enhance the process of application development; and the fourth provides a sampling of applications that require parallel computing for scaling to solve larger and realistic models that can advance science and engineering.


Recent Advances in Total Least Squares Techniques and Errors-in-variables Modeling

Recent Advances in Total Least Squares Techniques and Errors-in-variables Modeling

Author: Sabine van Huffel

Publisher: SIAM

Published: 1997-01-01

Total Pages: 404

ISBN-13: 9780898713930

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An overview of the computational issues; statistical, numerical, and algebraic properties, and new generalizations and applications of advances on TLS and EIV models. Experts from several disciplines prepared overview papers which were presented at the conference and are included in this book.


Complementarity and Variational Problems

Complementarity and Variational Problems

Author: Michael C. Ferris

Publisher: SIAM

Published: 1997-01-01

Total Pages: 494

ISBN-13: 9780898713916

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After more than three decades of research, the subject of complementarity problems and its numerous extensions has become a well-established and fruitful discipline within mathematical programming and applied mathematics. Sources of these problems are diverse and span numerous areas in engineering, economics, and the sciences. Includes refereed articles.


Advances in Multi-fluid Flows

Advances in Multi-fluid Flows

Author: Yuriko Y. Renardy

Publisher: SIAM

Published: 1996-01-01

Total Pages: 452

ISBN-13: 9780898713770

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The papers from this conference deal with multi-fluid flows and interfacial instabilities. Papers on multiple-layer convection, wave dynamics in viscous flows, stability of viscoelastic flows, numberical computation of bubbles, and solidification are included.


Computational Information Retrieval

Computational Information Retrieval

Author: Michael W. Berry

Publisher: SIAM

Published: 2001-01-01

Total Pages: 206

ISBN-13: 9780898715002

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This volume contains selected papers that focus on the use of linear algebra, computational statistics, and computer science in the development of algorithms and software systems for text retrieval. Experts in information modeling and retrieval share their perspectives on the design of scalable but precise text retrieval systems, revealing many of the challenges and obstacles that mathematical and statistical models must overcome to be viable for automated text processing. This very useful proceedings is an excellent companion for courses in information retrieval, applied linear algebra, and applied statistics.


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.