Parallel Graph Search
Parallel Graph Search is a computational framework within parallel algorithms that systematically explores graph structures concurrently across multiple processing units to accelerate the discovery of paths, nodes, or solutions, distinguished from sequential graph search by its simultaneous execution of search operations on distributed or shared-memory architectures.
102
Publications
5.7K
Citations
292
Authors
147
Institutions
Publications per year
2017–2026
23
Parents
102
Scalable Graph Exploration on Multicore Processors
Virat Agarwal, Fabrizio Petrini, Davide Pasetto et al. · 2010 · 227 citations
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147
IBM (United States)
Armonk, United States
6 h-index
8 publications
1.1K citations
Tokyo Institute of Technology
Tokyo, Japan
4 h-index
8 publications
242 citations
National University of Singapore
Singapore, Singapore
4 h-index
12 publications
580 citations
University of California, Berkeley
Berkeley, United States
4 h-index
10 publications
1.5K citations
Kyushu University
Fukuoka, Japan
3 h-index
4 publications
111 citations
Carnegie Mellon University
Pittsburgh, United States
3 h-index
4 publications
206 citations

University of Minnesota
Minneapolis, United States
3 h-index
3 publications
144 citations
IBM Research - Thomas J. Watson Research Center
Yorktown Heights, United States
3 h-index
4 publications
749 citations
1–8 of 147
6 publications · 387 citations
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TPDS · 5 publications · 167 citations
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TKDE · 3 publications · 150 citations
3
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Repository · 2 publications · 86 citations
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2 publications · 474 citations
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