Task Parallelism In Distributed Memory Systems

Task Parallelism in Distributed Memory Systems is a computational paradigm that allocates independent tasks to distinct processors in a distributed memory environment, where each processor executes its assigned task on locally stored data without shared memory access, thereby emphasizing inter-process communication for coordination and data exchange.

43

Publications

4K

Citations

106

Authors

44

Institutions

Publications per year

2017–2026

1

Authors

106

  1. TY
    Tao Yang

    University of California, Santa Barbara, United States

    6 publications · 225 citations

    6

    h-index

  2. CF
    Cong Fu

    Zhejiang University, China

    4 publications · 75 citations

    4

    h-index

  3. LT
    Leonard Truong

    Intel (United States), United States

    2 publications · 62 citations

    2

    h-index

  4. RB
    Rajkishore Barik

    Intel (United States), United States

    2 publications · 62 citations

    2

    h-index

  5. AF
    Armando Fox

    University of California, Berkeley, United States

    2 publications · 62 citations

    2

    h-index

1–5 of 106

Venues

  1. Journal of Parallel and Distributed Computing

    4 publications · 97 citations

    4

    h-index

  2. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 3 publications · 176 citations

    3

    h-index

  3. Parallel Computing

    2 publications · 74 citations

    2

    h-index

  4. ACM SIGPLAN Notices

    2 publications · 35 citations

    2

    h-index

  5. Fundamenta Informaticae

    1 publications · 38 citations

    1

    h-index

1–5