Massive graph analytics / edited by David A. Bader.

Format:

Book

Contributor:

Bader, David A., 1969- editor.

Series:

Chapman & Hall/CRC data science series.

Chapman & Hall/CRC data science series

Language:

English

Subjects (All):

Graph theory--Data processing.

Graph theory.

Physical Description:

1 online resource (xxv, 603 pages) : illustrations.

Edition:

First edition.

Place of Publication:

Boca Raton, Florida : CRC Press, [2022]

Summary:

Expertise in massive scale graph analytics is key for solving real-world grand challenges from health to sustainability to detecting insider threats, cyber defense, and more. Massive Graph Analytics provides a comprehensive introduction to massive graph analytics, featuring contributions from thought leaders across academia, industry, and government. The book will be beneficial to students, researchers and practitioners, in academia, national laboratories, and industry, who wish to learn about the state-of-the-art algorithms, models, frameworks, and software in massive scale graph analytics.

Contents:

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

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

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

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

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, Scott McMillian, 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, David A. Bader, Michael Merrill and William Reus.

Notes:

Includes bibliographical references and index.

Description based on print version record.

Other Format:

Print version:

ISBN:

1-00-303370-9

1-000-53869-9

1-000-53861-3

1-003-03370-9

9781003033707

OCLC:

1273728002