Parallel Geometric Data Structures is a computational framework that organizes geometric data to enable concurrent access and modification, distinguished by its design to support efficient parallel execution of geometric algorithms through spatial decomposition and synchronization-optimized data organization.
76
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2.9K
Citations
187
Authors
104
Institutions
Publications per year
2017–2026
11
Publications
76
Parallel computational geometry
Alok Aggarwal, Bernard Chazelle, Leonidas Guibas et al. · Algorithmica · 1988 · 216 citations
1–5 of 76
Authors
187
- MJ
4
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- FD
3
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- HS
3
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- AR
3
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- VK
3
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1–5 of 187
Institutions
104
University of Maryland, College Park
College Park, United States
8 h-index
12 publications
238 citations
Purdue University West Lafayette
West Lafayette, United States
5 h-index
11 publications
385 citations
New York University
New York, United States
4 h-index
7 publications
605 citations
Carleton University
Ottawa, Canada
3 h-index
6 publications
198 citations
The Ohio State University
Columbus, United States
3 h-index
6 publications
144 citations
IBM Research - Thomas J. Watson Research Center
Yorktown Heights, United States
3 h-index
3 publications
310 citations
IBM (United States)
Armonk, United States
3 h-index
7 publications
369 citations
Massachusetts Institute of Technology
Cambridge, United States
3 h-index
3 publications
115 citations
1–8 of 104
Venues
- Algorithmica
5 publications · 307 citations
5
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- Journal of Parallel and Distributed Computing
4 publications · 163 citations
4
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- Parallel Computing
3 publications · 118 citations
3
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- Proceedings of the International Conference on Parallel Processing
Conference · 3 publications · 84 citations
3
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- International Journal of Computational Geometry & Applications
IJCGA · 3 publications · 113 citations
3
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1–5