Adaptive Partitioning

Adaptive Partitioning is a data partitioning strategy that dynamically adjusts the division of datasets based on evolving data characteristics, system conditions, or workload demands to optimize performance, scalability, or efficiency in distributed computing environments.

198

Publications

12.6K

Citations

616

Authors

301

Institutions

Publications per year

2017–2026

55

Authors

616

  1. AI
    Alexander I. Boldyrev

    Utah State University, United States

    7 publications · 2K citations

    7

    h-index

  2. HL
    Hai Lin

    University of Colorado Denver, United States

    4 publications · 367 citations

    4

    h-index

  3. SM
    Samuel Madden

    Massachusetts Institute of Technology, United States

    3 publications · 105 citations

    3

    h-index

  4. MP
    Marco Pintore

    Université d'Orléans, France

    3 publications · 60 citations

    3

    h-index

  5. SH
    Shi-Sheng Huang

    Tsinghua University, China

    3 publications · 126 citations

    3

    h-index

1–5 of 616

Venues

  1. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 6 publications · 292 citations

    6

    h-index

  2. Journal of Chemical Theory and Computation

    JCTC · 5 publications · 289 citations

    5

    h-index

  3. arXiv (Cornell University)

    Repository · 4 publications · 95 citations

    4

    h-index

  4. Journal of Parallel and Distributed Computing

    3 publications · 44 citations

    3

    h-index

  5. The Journal of Physical Chemistry A

    3 publications · 183 citations

    3

    h-index

1–5