Applied Numerical Linear Algebra

James W. Demmel

ISBN 10: 0898713897 / ISBN 13: 9780898713893

Published by Society for Industrial and Applied Mathematics,U.S., US, 1997

About this Item

Designed for first-year graduate students from a variety of engineering and scientific disciplines, this comprehensive textbook covers the solution of linear systems, least squares problems, eigenvalue problems, and the singular value decomposition. The author, who helped design the widely used LAPACK and ScaLAPACK linear algebra libraries, draws on this experience to present state-of-the-art techniques for these problems, including recommending which algorithms to use in various practical situations. Algorithms are derived in a mathematically illuminating way, including condition numbers and error bounds. Direct and iterative algorithms, suitable for dense and sparse matrices, are discussed. Algorithm design for modern computer architectures, where moving data is often more expensive than arithmetic operations, is discussed in detail, using LAPACK as an illustration. There are many numerical examples throughout the text and in the problems at the ends of chapters, most of which are written in MATLAB and are freely available on the Web.

Seller Inventory # LU-9780898713893

Bibliographic Details

• Title: Applied Numerical Linear Algebra
• Publisher: Society for Industrial and Applied Mathematics,U.S., US
• Publication Date: 1997
• Language: English
• ISBN 10: 0898713897
• ISBN 13: 9780898713893
• Binding: Paperback
• Condition: New
• Weight: 856 grams

About this title

Synopsis

Designed for first-year graduate students from a variety of engineering and scientific disciplines, this comprehensive textbook covers the solution of linear systems, least squares problems, eigenvalue problems, and the singular value decomposition. The author, who helped design the widely used LAPACK and ScaLAPACK linear algebra libraries, draws on this experience to present state-of-the-art techniques for these problems, including recommending which algorithms to use in various practical situations. Algorithms are derived in a mathematically illuminating way, including condition numbers and error bounds. Direct and iterative algorithms, suitable for dense and sparse matrices, are discussed. Algorithm design for modern computer architectures, where moving data is often more expensive than arithmetic operations, is discussed in detail, using LAPACK as an illustration. There are many numerical examples throughout the text and in the problems at the ends of chapters, most of which are written in MATLAB and are freely available on the Web.

About the Author

James Demmel is a Professor in the Computer Science Division and Mathematics Department at the University of California, Berkeley. He was elected to the National Academy of Engineering in 1999.