High-throughput Computing

High-Throughput Computing is a computational paradigm within distributed computing that emphasizes the efficient execution of a large number of computational tasks over extended periods, distinguished from high-performance computing by its focus on maximizing aggregate task throughput rather than minimizing the execution time of individual tasks.

862

Publications

45.9K

Citations

3.4K

Authors

718

Institutions

Publications per year

2017–2026

310

Authors

3.4K

  1. PD
    Pradeep Dubey

    Intel (United States), United States

    10 publications · 1.3K citations

    10

    h-index

  2. ED
    Ewa Deelman

    University of Southern California, United States

    10 publications · 309 citations

    10

    h-index

  3. VK
    Viktor K. Prasanna

    University of Southern California, United States

    10 publications · 319 citations

    10

    h-index

  4. IF
    Ian Foster

    Argonne National Laboratory, United States

    10 publications · 829 citations

    10

    h-index

  5. ML
    Miron Livny

    University of Wisconsin–Madison, United States

    9 publications · 1.2K citations

    9

    h-index

1–5 of 3.4K

Venues

  1. arXiv (Cornell University)

    Repository · 27 publications · 859 citations

    19

    h-index

  2. Proceedings of the VLDB Endowment

    PVLDB · 18 publications · 1.5K citations

    16

    h-index

  3. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 18 publications · 670 citations

    16

    h-index

  4. 11

    h-index

  5. IEEE Transactions on Computers

    10 publications · 520 citations

    11

    h-index

1–5