Parallel Graph Data Structures
Parallel Graph Data Structures is a class of data organization methods designed to represent graph-theoretic structures in a manner that enables concurrent access and manipulation by multiple computational processes or threads, distinguished by their explicit support for parallelism in operations such as traversal, subgraph extraction, and dynamic updates.
120
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5.8K
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303
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139
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2017–2026
28
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Patrice Godefroid, Michael Y. Levin, Dávid Molnár · Communications of the ACM · 2012 · 562 citations
PT-Scotch: A tool for efficient parallel graph ordering
Parallel Computing · 2007 · 328 citations · Full text
Rong Chen, Jiaxin Shi, Yanzhe Chen et al. · 2015 · 310 citations
PT-Scotch: A tool for efficient parallel graph ordering
2006 · 282 citations · Full text
Mehrzad Samadi, Janghaeng Lee, D. Anoushe Jamshidi et al. · 2013 · 254 citations
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The University of Texas at Austin
Austin, United States
4 h-index
9 publications
351 citations
Brown University
Providence, United States
3 h-index
3 publications
58 citations
IBM Research - Thomas J. Watson Research Center
Yorktown Heights, United States
3 h-index
3 publications
78 citations
Duke University
Durham, United States
3 h-index
3 publications
88 citations
University at Buffalo, State University of New York
Buffalo, United States
3 h-index
3 publications
48 citations

University of Central Florida
Orlando, United States
3 h-index
9 publications
309 citations

Chinese Academy of Sciences
Beijing, China
3 h-index
3 publications
248 citations
The Ohio State University
Columbus, United States
3 h-index
4 publications
163 citations
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4 publications · 215 citations
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4 publications · 163 citations
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3 publications · 107 citations
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3 publications · 62 citations
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2 publications · 609 citations
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