Massive graph analytics. (2022)

• Record Type: Book
• Further Information: Note: Edited by David A. Bader.
• Editors: Bader, David A, 1969-
• Contents: About the Editor List of Contributors Introduction Algorithms: Search and Paths A Work-Efficient Parallel Breadth-First Search Algorithm (or How to Cope With the Nondeterminism of Reducers) Charles E. Leiserson and Tao B. Schardl Multi-Objective Shortest Paths Stephan Erb, Moritz Kobitzsch, Lawrence Mandow, and Peter Sanders Algorithms: Structure Multicore Algorithms for Graph Connectivity Problems George M. Slota, Sivasankaran Rajamanickam, and Kamesh Madduri Distributed Memory Parallel Algorithms for Massive Graphs Maksudul Alam, Shaikh Arifuzzaman, Hasanuzzaman Bhuiyan, Maleq Khan, V.S. Anil Kumar, and Madhav Marathe Efficient Multi-core Algorithms for Computing Spanning Forests and Connected Components Fredrik Manne, Md. Mostofa Ali Patwary Massive-Scale Distributed Triangle Computation and Applications Geoffrey Sanders, Roger Pearce, Benjamin W. Priest, Trevor Steil Algorithms and Applications Computing Top-k Closeness Centrality in Fully-dynamic Graphs Eugenio Angriman, Patrick Bisenius, Elisabetta Bergamini, Henning Meyerhenke Ordering Heuristics for Parallel Graph Coloring William Hasenplaugh, Tim Kaler, Tao B. Schardl, and Charles E. Leiserson Partitioning Trillion Edge Graphs George M. Slota, Karen Devine, Sivasankaran Rajamanickam, Kamesh Madduri New Phenomena in Large-Scale Internet Traffic Jeremy Kepner, Kenjiro Cho, KC Claffy, Vijay Gadepally, Sarah McGuire, Peter Michaleas, Lauren Milechin Parallel Algorithms for Butterfly Computations Jessica Shi and Julian Shun Models Recent Advances in Scalable Network Generation Manuel Penschuck, Ulrik Brandes, Michael Hamann, Sebastian Lamm, Ulrich Meyer, Ilya Safro, Peter Sanders, and Christian Schulz Computational Models for Cascades in Massive Graphs: How to Spread a Rumor in Parallel Ajitesh Srivastava, Charalampos Chelmis, Viktor K. Prasanna Executing Dynamic Data-Graph Computations Deterministically Using Chromatic Scheduling Tim Kaler, William Hasenplaugh, Tao B. Schardl, and Charles E. Leiserson Frameworks and Software Graph Data Science Using Neo4j Amy E. Hodler, Mark Needham The Parallel Boost Graph Library 2.0 Nicholas Edmonds and Andrew Lumsdaine RAPIDS cuGraph Alex Fender, Bradley Rees, Joe Eaton A Cloud-based approach to Big Graphs Paul Burkhardt and Christopher A. Waring Introduction to GraphBLAS Jeremy Kepner, Peter Aaltonen, David Bader, Aydin Buluc, Franz Franchetti, John Gilbert, Dylan Hutchinson, Manoj Kumar, Andrew Lumsdaine, Henning Meyerhenke, Scott McMillian, Jose Moreira, John D. Owens, Carl Yang, Marcin Zalewski, and Timothy G. Mattson Graphulo: Linear Algebra Graph Kernels Vijay Gadepally, Jake Bolewski, Daniel Hook, Shana Hutchison, Benjamin A Miller, Jeremy Kepner Interactive Graph Analytics at Scale in Arkouda Zhihui Du, Oliver Alvarado Rodriguez, Joseph Patchett, and David A. Bader
• Edition: 1st
• Publisher Details: Boca Raton : Chapman & Hall/CRC
• Publication Date: 2022
• Extent: 1 online resource, illustrations (black and white)
• Subjects: 511.5; Graph theory -- Data processing; Graph algorithms; Big data; Data mining
• Languages: English
• ISBNs: 9781000538694; 9781000538618; 9781003033707
• Related ISBNs: 9780367464127
• Notes: Note: Includes bibliographical references and index.; Note: Description based on CIP data; resource not viewed.
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.