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Massive Graph Analytics, 2022
- David A. Bader:
Massive Graph Analytics. Chapman and Hall/CRC 2022, ISBN 9781003033707 - Charles E. Leiserson, Tao B. Schardl:
A Work-Efficient Parallel Breadth-First Search Algorithm (or How To Cope With the Nondeterminism of Reducers). 3-33 - Stephan Erb, Moritz Kobitzsch, Lawrence Mandow, Peter Sanders:
Multi-Objective Shortest Paths. 35-59 - George M. Slota, Sivasankaran Rajamanickam, Kamesh Madduri:
Multicore Algorithms for Graph Connectivity Problems. 63-84 - Md. Maksudul Alam, Shaikh Arifuzzaman, Md Hasanuzzaman Bhuiyan, Maleq Khan, V. S. Anil Kumar, Madhav V. Marathe:
Distributed Memory Parallel Algorithms for Massive Graphs. 85-107 - Fredrik Manne, Md. Mostofa Ali Patwary:
Efficient Multi-core Algorithms for Computing Spanning Forests and Connected Components. 109-125 - Geoffrey Sanders, Roger Pearce, Benjamin W. Priest, Trevor Steil:
Massive-Scale Distributed Triangle Computation and Applications. 127-158 - Eugenio Angriman, Patrick Bisenius, Elisabetta Bergamini, Henning Meyerhenke:
Computing Top-k Closeness Centrality in Fully Dynamic Graphs. 161-192 - William Hasenplaugh, Tim Kaler, Tao B. Schardl, Charles E. Leiserson:
Ordering Heuristics for Parallel Graph Coloring. 193-221 - George M. Slota, Karen D. Devine, Kamesh Madduri, Sivasankaran Rajamanickam:
Partitioning Trillion-Edge Graphs. 223-240 - Jeremy Kepner, Kenjiro Cho, kc claffy
, Vijay Gadepally, Sarah McGuire, Lauren Milechin, William Arcand, David Bestor, William Bergeron, Chansup Byun, Matthew Hubbell, Michael Houle, Michael Jones, Andrew Prout, Albert Reuther, Antonio Rosa, Siddharth Samsi, Charles Yee, Peter Michaleas:
New Phenomena in Large-Scale Internet Traffic. 241-285 - Jessica Shi, Julian Shun:
Parallel Algorithms for Butterfly Computations. 287-330 - Manuel Penschuck, Ulrik Brandes, Michael Hamann, Sebastian Lamm, Ulrich Meyer, Ilya Safro, Peter Sanders, Christian Schulz:
Recent Advances in Scalable Network Generation1. 333-376 - Ajitesh Srivastava, Charalampos Chelmis, Viktor K. Prasanna:
Computational Models for Cascades in Massive Graphs. 377-395 - Tim Kaler, William Hasenplaugh, Tao B. Schardl, Charles E. Leiserson:
Executing Dynamic Data-Graph Computations Deterministically Using Chromatic Scheduling. 397-429 - Amy E. Hodler, Mark Needham:
Graph Data Science Using Neo4j. 433-457 - Nicholas Gerard Edmonds, Andrew Lumsdaine:
The Parallel Boost Graph Library 2.0. 459-481 - Alexandre Fender, Brad Rees, Joe Eaton:
RAPIDS cuGraph. 483-493 - Paul Burkhardt, Christopher A. Waring:
A Cloud-Based Approach to Big Graphs. 495-506 - Jeremy Kepner, Peter Aaltonen, David A. Bader, Aydin Buluç, Franz Franchetti, John Gilbert, Shana Hutchison, Manoj Kumar, Andrew Lumsdaine, Henning Meyerhenke, Scott McMillan, José E. Moreira, John D. Owens, Carl Yang, Marcin Zalewski, Timothy G. Mattson:
Introduction to GraphBLAS. 507-524 - Lauren Milechin, Shana Hutchison, Hayden Jananthan, Jeremy Kepner, Benjamin A. Miller, Andrew Prout, Siddharth Samsi, Charles Yee, Vijay Gadepally:
Graphulo: Linear Algebra Graph Kernels. 525-548 - Zhihui Du, Oliver Alvarado Rodriguez, Joseph Patchett, David A. Bader:
Interactive Graph Analytics at Scale in Arkouda. 549-589
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