Parallel Closest Pair Computation
Parallel Closest Pair Computation is a parallel algorithmic method that identifies the pair of points with minimal Euclidean distance in a multidimensional space by concurrently processing spatially partitioned subsets of the input point set, thereby accelerating the classical closest pair problem through distributed or shared-memory parallelism.
12
Publications
471
Citations
22
Authors
15
Institutions
Publications per year
2017–2026
1
12
Ahmed Eldawy, Yuan Li, Mohamed F. Mokbel et al. · 2013 · 86 citations
Fast Parallel Algorithms for Euclidean Minimum Spanning Tree and Hierarchical Spatial Clustering
Yiqiu Wang, Shangdi Yu, Yan Gu et al. · 2021 · 33 citations · Full text
1–5 of 12
22
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IBM Research - Thomas J. Watson Research Center, United States
2 publications · 161 citations
2
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1
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1
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1–5 of 22
15
IBM Research - Thomas J. Watson Research Center
Yorktown Heights, United States
2 h-index
4 publications
441 citations

Tel Aviv University
Tel Aviv, Israel
2 h-index
4 publications
441 citations

The King's College
New York, United States
1 h-index
3 publications
420 citations

University of Minnesota
Minneapolis, United States
1 h-index
4 publications
344 citations
Iowa State University
Ames, United States
1 h-index
2 publications
20 citations
University of Michigan
Ann Arbor, United States
1 h-index
2 publications
54 citations
University of Illinois Urbana-Champaign
Urbana, United States
1 h-index
1 publications
11 citations

Johns Hopkins University
Baltimore, United States
1 h-index
1 publications
50 citations
1–8 of 15
2 publications · 151 citations
2
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IJCGA · 2 publications · 39 citations
2
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Conference · 1 publications · 24 citations
1
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TPDS · 1 publications · 10 citations
1
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1 publications · 21 citations
1
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1–5