Task Parallelism

Task Parallelism is a form of parallel computation in which a program is decomposed into multiple concurrent tasks (such as threads or processes) that may execute different operations on the same or different data and are scheduled to run in parallel on multiple processing elements, in contrast to data parallelism where identical operations are applied in parallel to disjoint data partitions.

1.4K

Publications

89.3K

Citations

3.2K

Authors

911

Institutions

Publications per year

2017–2026

200

Authors

3.2K

  1. IF
    Ian Foster

    Argonne National Laboratory, United States

    16 publications · 1.4K citations

    16

    h-index

  2. VS
    Vivek Sarkar

    Rice University, United States

    20 publications · 1.5K citations

    14

    h-index

  3. EA
    Eduard Ayguadé

    Universitat Politècnica de Catalunya, Spain

    14 publications · 969 citations

    13

    h-index

  4. JL
    Jesús Labarta

    Universitat Politècnica de Catalunya, Spain

    14 publications · 1.1K citations

    13

    h-index

  5. TR
    Thomas Rauber

    University of Bayreuth, Germany

    10 publications · 231 citations

    10

    h-index

1–5 of 3.2K

Venues

  1. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 30 publications · 2.5K citations

    24

    h-index

  2. Journal of Parallel and Distributed Computing

    33 publications · 1.8K citations

    22

    h-index

  3. 19

    h-index

  4. IEEE Transactions on Computers

    19 publications · 2.2K citations

    15

    h-index

  5. Parallel Computing

    19 publications · 508 citations

    13

    h-index

1–5