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English ISBN: 2017 451 Pages PDF 6 MB The subject of sparse matrices has its root in such diverse fields as management science, power systems analysis, surveying, circuit theory, and structural analysis. Efficient use of sparsity is a key to solving large problems in many fields.

This second edition is a complete rewrite of the first edition published 30 years ago. Much has changed since that time. Problems have grown greatly in size and complexity; nearly all examples in the first edition were of order less than 5,000 in the first edition, and are often more than a million in the second edition. Computer architectures are now much more complex, requiring new ways of adapting algorithms to parallel environments with memory hierarchies. Because the area is such an important one to all of computational science and engineering, a huge amount of research has been done in the last 30 years, some of it by the authors themselves. This new research is integrated into the text with a clear explanation of the underlying mathematics and algorithms. New research that is described includes new techniques for scaling and error control, new orderings, new combinatorial techniques for partitioning both symmetric and unsymmetric problems, and a detailed description of the multifrontal approach to solving systems that was pioneered by the research of the authors and colleagues.

Bibliographic Information. Book Title: Direct Methods for Sparse Matrices; Authors. Series Title: Lecture Notes in Computer Science; Series Volume: 157; Copyright: 1983; Publisher: Springer-Verlag Berlin Heidelberg; Copyright Holder: Springer-Verlag Berlin Heidelberg. EBook ISBN: 978-3-540-38669-. To implement efficiently on high-performance computers than direct methods. My intention in writing this volume is to provide up-to-date coverage of itera- tive methods for solving large sparse linear systems. I focused the book on practical methods that work for general sparse matrices rather than for any specific class of. Presents the fundamentals of sparse matrix algorithms to provide the requisite background. The book includes CSparse, a concise downloadable sparse matrix package.

Rutherford Appleton Laboratory

This includes a discussion of techniques for exploiting parallel architectures and new work for indefinite and unsymmetric systems.