Thread Parallelism

Thread Parallelism is a computational concurrency model in GPU computing where multiple threads execute the same instruction across different data elements simultaneously, distinguished by its fine-grained parallel execution managed at the hardware level through thread scheduling and resource partitioning.

480

Publications

28.1K

Citations

1.4K

Authors

352

Institutions

Publications per year

2017–2026

81

Authors

1.4K

  1. DM
    Dean M. Tullsen

    University of California San Diego, United States

    13 publications · 3.2K citations

    12

    h-index

  2. AG
    Antonio González

    Universitat Politècnica de Catalunya, Spain

    10 publications · 646 citations

    10

    h-index

  3. TM
    Trevor Mudge

    University of Michigan, United States

    9 publications · 542 citations

    9

    h-index

  4. MA
    Murali Annavaram

    University of Southern California, United States

    9 publications · 511 citations

    9

    h-index

  5. WW
    Won Woo Ro

    Yonsei University, South Korea

    9 publications · 408 citations

    9

    h-index

1–5 of 1.4K

Venues

  1. ACM SIGARCH Computer Architecture News

    20 publications · 1.5K citations

    15

    h-index

  2. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 14 publications · 617 citations

    12

    h-index

  3. ACM SIGPLAN Notices

    9 publications · 338 citations

    9

    h-index

  4. IEEE Transactions on Computers

    5 publications · 456 citations

    5

    h-index

  5. IEEE Micro

    4 publications · 1.2K citations

    4

    h-index

1–5