Synopses & Reviews
This book provides practical approaches to the efficient use of sparsity--a key to solving large problems in many fields, including computational science and engineering, where mathematical models give rise to very large systems of linear equations. The emphasis is on practicality, with conclusions based on concrete experience. Non-numeric computing techniques have been included as well as frequent illustrations in an attempt to bridge the gap between the written word and the working computer code. Exercises have been included to strengthen understanding of the material as well as to extend it for students and researchers in engineering, mathematics, and computer science.
Includes bibliographical references (p. -326).
Table of Contents
2. Sparse Matrices: Storage Schemes and Simple Operations
3. Gaussian Elimination for Dense Matrices: The Algebraic Approach
4. Gaussian Elimination for Dense Matrices: Numerical Considerations
5. Gaussian Elimination for Sparse Matrices: An Introduction
6. Reduction to Block Triangular Form
7. Local Pivotal Strategies for Sparse Matrices
8. Ordering Sparse Matrices to Special Forms
9. Implementing Gaussian Elimination: ANALYSE with Numerical Values
10. Implementing Gaussian Elimination with Symbolic ANALYSE
11. Partitioning, Matrix Modification, and Tearing
12. Other Sparsity-Oriented Issues