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Graph Theory and Sparse Matrix Computation

2012-12-06 Mathematics
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Release : 2012-12-06
Genre : Mathematics
Kind : eBook
Book Rating : 692/5 ( reviews)

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Book Synopsis Graph Theory and Sparse Matrix Computation by : Alan George

Download or read book Graph Theory and Sparse Matrix Computation written by Alan George. This book was released on 2012-12-06. Available in PDF, EPUB and Kindle. Book excerpt: When reality is modeled by computation, matrices are often the connection between the continuous physical world and the finite algorithmic one. Usually, the more detailed the model, the bigger the matrix, the better the answer, however, efficiency demands that every possible advantage be exploited. The articles in this volume are based on recent research on sparse matrix computations. This volume looks at graph theory as it connects to linear algebra, parallel computing, data structures, geometry, and both numerical and discrete algorithms. The articles are grouped into three general categories: graph models of symmetric matrices and factorizations, graph models of algorithms on nonsymmetric matrices, and parallel sparse matrix algorithms. This book will be a resource for the researcher or advanced student of either graphs or sparse matrices; it will be useful to mathematicians, numerical analysts and theoretical computer scientists alike.

Graph Theory and Sparse Matrix Computation

1993-10-22 Mathematics
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Release : 1993-10-22
Genre : Mathematics
Kind : eBook
Book Rating : 318/5 ( reviews)

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Book Synopsis Graph Theory and Sparse Matrix Computation by : Alan George

Download or read book Graph Theory and Sparse Matrix Computation written by Alan George. This book was released on 1993-10-22. Available in PDF, EPUB and Kindle. Book excerpt: When reality is modeled by computation, matrices are often the connection between the continuous physical world and the finite algorithmic one. Usually, the more detailed the model, the bigger the matrix, the better the answer, however, efficiency demands that every possible advantage be exploited. The articles in this volume are based on recent research on sparse matrix computations. This volume looks at graph theory as it connects to linear algebra, parallel computing, data structures, geometry, and both numerical and discrete algorithms. The articles are grouped into three general categories: graph models of symmetric matrices and factorizations, graph models of algorithms on nonsymmetric matrices, and parallel sparse matrix algorithms. This book will be a resource for the researcher or advanced student of either graphs or sparse matrices; it will be useful to mathematicians, numerical analysts and theoretical computer scientists alike.

Graph Algorithms in the Language of Linear Algebra

2011-01-01 Mathematics
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Release : 2011-01-01
Genre : Mathematics
Kind : eBook
Book Rating : 918/5 ( reviews)

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Book Synopsis Graph Algorithms in the Language of Linear Algebra by : Jeremy Kepner

Download or read book Graph Algorithms in the Language of Linear Algebra written by Jeremy Kepner. This book was released on 2011-01-01. Available in PDF, EPUB and Kindle. Book excerpt: The current exponential growth in graph data has forced a shift to parallel computing for executing graph algorithms. Implementing parallel graph algorithms and achieving good parallel performance have proven difficult. This book addresses these challenges by exploiting the well-known duality between a canonical representation of graphs as abstract collections of vertices and edges and a sparse adjacency matrix representation. This linear algebraic approach is widely accessible to scientists and engineers who may not be formally trained in computer science. The authors show how to leverage existing parallel matrix computation techniques and the large amount of software infrastructure that exists for these computations to implement efficient and scalable parallel graph algorithms. The benefits of this approach are reduced algorithmic complexity, ease of implementation, and improved performance.

Computer Solution of Large Sparse Positive Definite Systems

1981 Mathematics
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Release : 1981
Genre : Mathematics
Kind : eBook
Book Rating : /5 ( reviews)

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Book Synopsis Computer Solution of Large Sparse Positive Definite Systems by : Alan George

Download or read book Computer Solution of Large Sparse Positive Definite Systems written by Alan George. This book was released on 1981. Available in PDF, EPUB and Kindle. Book excerpt:

Direct Methods for Sparse Linear Systems

2006-09-01 Computers
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Release : 2006-09-01
Genre : Computers
Kind : eBook
Book Rating : 136/5 ( reviews)

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Book Synopsis Direct Methods for Sparse Linear Systems by : Timothy A. Davis

Download or read book Direct Methods for Sparse Linear Systems written by Timothy A. Davis. This book was released on 2006-09-01. Available in PDF, EPUB and Kindle. Book excerpt: The sparse backslash book. Everything you wanted to know but never dared to ask about modern direct linear solvers. Chen Greif, Assistant Professor, Department of Computer Science, University of British Columbia.Overall, the book is magnificent. It fills a long-felt need for an accessible textbook on modern sparse direct methods. Its choice of scope is excellent John Gilbert, Professor, Department of Computer Science, University of California, Santa Barbara.Computational scientists often encounter problems requiring the solution of sparse systems of linear equations. Attacking these problems efficiently requires an in-depth knowledge of the underlying theory, algorithms, and data structures found in sparse matrix software libraries. Here, Davis presents the fundamentals of sparse matrix algorithms to provide the requisite background. The book includes CSparse, a concise downloadable sparse matrix package that illustrates the algorithms and theorems presented in the book and equips readers with the tools necessary to understand larger and more complex software packages.With a strong emphasis on MATLAB and the C programming language, Direct Methods for Sparse Linear Systems equips readers with the working knowledge required to use sparse solver packages and write code to interface applications to those packages. The book also explains how MATLAB performs its sparse matrix computations.Audience This invaluable book is essential to computational scientists and software developers who want to understand the theory and algorithms behind modern techniques used to solve large sparse linear systems. The book also serves as an excellent practical resource for students with an interest in combinatorial scientific computing.Preface; Chapter 1: Introduction; Chapter 2: Basic algorithms; Chapter 3: Solving triangular systems; Chapter 4: Cholesky factorization; Chapter 5: Orthogonal methods; Chapter 6: LU factorization; Chapter 7: Fill-reducing orderings; Chapter 8: Solving sparse linear systems; Chapter 9: CSparse; Chapter 10: Sparse matrices in MATLAB; Appendix: Basics of the C programming language; Bibliography; Index.

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