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

Authors

22

  1. QF
    Quentin F. Stout

    University of Michigan, United States

    2 publications · 38 citations

    2

    h-index

  2. UV
    Uzi Vishkin

    University of Maryland, College Park, United States

    2 publications · 161 citations

    2

    h-index

  3. BS
    Baruch Schieber

    IBM Research - Thomas J. Watson Research Center, United States

    2 publications · 161 citations

    2

    h-index

  4. AE
    Ahmed Eldawy

    University of Minnesota, United States

    1 publications · 86 citations

    1

    h-index

  5. YW
    Yiqiu Wang

    Rice University, United States

    1 publications · 33 citations

    1

    h-index

1–5 of 22

Venues

  1. Journal of Algorithms

    2 publications · 151 citations

    2

    h-index

  2. 2

    h-index

  3. Parallel and Distributed Processing Techniques and Applications

    Conference · 1 publications · 24 citations

    1

    h-index

  4. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 1 publications · 10 citations

    1

    h-index

  5. Discrete Applied Mathematics

    1 publications · 21 citations

    1

    h-index

1–5