Distributed Reduction Operations

Distributed Reduction Operations is a collective communication pattern in distributed memory parallelism that combines data from multiple processing nodes using an associative operator, where the result is made available on a single designated node, distinguished by its coordination of partial results across physically separated memory spaces to achieve global computation efficiently.

21

Publications

679

Citations

74

Authors

32

Institutions

Publications per year

2017–2026

3

Authors

74

  1. DK
    Dhabaleswar K. Panda

    The Ohio State University, United States

    5 publications · 119 citations

    5

    h-index

  2. RL
    Richard L. Graham

    Oak Ridge National Laboratory, United States

    3 publications · 169 citations

    3

    h-index

  3. JB
    Jehoshua Bruck

    California Institute of Technology, United States

    2 publications · 30 citations

    2

    h-index

  4. TR
    Tamir Ronen

    Mellanox Technologies (Israel), Israel

    2 publications · 153 citations

    2

    h-index

  5. MB
    Mohammadreza Bayatpour

    The Ohio State University, United States

    2 publications · 56 citations

    2

    h-index

1–5 of 74

Venues

  1. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 2 publications · 50 citations

    2

    h-index

  2. Workshop on Parallel and Distributed Simulation

    Conference · 1 publications · 37 citations

    1

    h-index

  3. Procedia Computer Science

    1 publications · 13 citations

    1

    h-index

  4. Data Archiving and Networked Services (DANS)

    Repository · 1 publications · 27 citations

    1

    h-index

  5. IEEE Transactions on Computers

    1 publications · 36 citations

    1

    h-index

1–5