"This book is concerned with solving very large sets of linear equations, where each equation involves only a small number of variables. Many applications involve equations of this kind and they often need to be solved repeatedly as their entries change.Very special methods are needed to make these calculations feasible. The authors have been involved in designing special algorithms and writing codes to implement them for over 40 years. This book aims to describe in a clear and simple way those algorithms that have stood the test of time, as well as those that have been developed recently to enable the efficient solution of far larger systems and to take advantage hardware"--
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I. S. (Iain) Duff is an STFC Senior Fellow in the Scientific Computing Department at the STFC Rutherford Appleton Laboratory in Oxfordshire, England. He is also the Scientific Advisor for the Parallel Algorithms Group at CERFACS in Toulouse and is a Visiting Professor of Mathematics at the University of Strathclyde. A. M. (Al) Erisman is the Executive in Residence in the School of Business, Government, and Economics at Seattle Pacific University and is executive editor of Ethix magazine (http://www.ethix.org), which he co-founded with a colleague in 1998. Over the past 15 years he has lectured on five continents in areas of business, technology, mathematics, ethics, faith, and economic development. J. K. (John) Reid is an Honorary Scientist at the STFC Rutherford Appleton Laboratory in Oxfordshire, England. He is also a Visiting Professor at the Shrivenham Campus of Cranfield University and is Convener of the ISO/IEC Fortran Committee.
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Hardcover. Condition: new. Hardcover. 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 thefirst 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 adaptingalgorithms 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, newcombinatorial 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 theauthors and colleagues. This includes a discussion of techniques for exploiting parallel architectures and new work for indefinite and unsymmetric systems. 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 book provides both insight and answers for those attempting to solve these problems. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9780198508380
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