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You searched IISERK - Subject: Netherlands National Research Programme on Global Air Pollution and Climate Change Congresses.
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Call Number
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511/.6
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Title
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Graph algorithms in the language of linear algebra [electronic resource] / edited by Jeremy Kepner, John Gilbert.
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Publication
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Philadelphia, Pa. : Society for Industrial and Applied Mathematics (SIAM, 3600 Market Street, Floor 6, Philadelphia, PA 19104), c2011.
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Material Info.
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1 electronic text (xxviii, 361 p.) : ill., digital file.
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Series
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Software, environments, and tools ; 22
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Series
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Software, environments, tools ; 22.
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Summary Note
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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.
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Notes
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Includes bibliographical references and index.
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Notes
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List of figures -- List of tables -- List of algorithms -- Preface -- Acknowledgments --
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Notes
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Part I. Algorithms. Chapter 1. Graphs and matrices -- Chapter 2. Linear algebraic notation and definitions -- Chapter 3. Connected components and minimum paths -- Chapter 4. Some graph algorithms in an array-based language -- Chapter 5. Fundamental graph algorithms -- Chapter 6. Complex graph algorithms -- Chapter 7. Multilinear algebra for analyzing data with multiple linkages -- Chapter 8. Subgraph detection --
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Notes
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Part II. Data. Chapter 9. Kronecker graphs -- Chapter 10. The Kronecker theory of power law graphs -- Chapter 11. Visualizing large Kronecker graphs --
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Notes
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Part III. Computation Chapter 12. Large-scale network analysis -- Chapter 13. Implementing sparse matrices for graph algorithms -- Chapter 14. New ideas in sparse matrix-matrix multiplication -- Chapter 15. Parallel mapping of sparse computations -- Chapter 16. Fundamental questions in the analysis of large graphs -- Index.
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ISBN
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9780898719918 (electronic bk.)
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Subject
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Graph algorithms.
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Subject
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Algebras, Linear.
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Subject
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Graph algorithms
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Subject
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Network analysis
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Subject
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Adjacency matrix
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Subject
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Sparse matrixes
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Subject
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Parallel programming
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Subject
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Combinatorial scientific computing
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Added Entry
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Kepner, Jeremy V., 1969-
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Added Entry
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Gilbert, J. R. (John R.), 1953-
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Added Entry
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Society for Industrial and Applied Mathematics.
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Date
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Year, Month, Day:01405141
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Link
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SIAM
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