Loop Parallelization

Loop Parallelization is a parallel programming technique that decomposes iterations of a loop into concurrently executable tasks, enabling simultaneous execution across multiple processing units to improve computational performance.

425

Publications

21.7K

Citations

825

Authors

274

Institutions

Publications per year

2017–2026

34

Authors

825

  1. LR
    Lawrence Rauchwerger

    Texas A&M University, United States

    18 publications · 1.2K citations

    17

    h-index

  2. KK
    Ken Kennedy

    Rice University, United States

    12 publications · 1.5K citations

    12

    h-index

  3. DP
    David Padua

    University of Illinois Urbana-Champaign, United States

    11 publications · 1K citations

    11

    h-index

  4. AC
    Albert Cohen

    Institut national de recherche en sciences et technologies du numérique, France

    10 publications · 697 citations

    10

    h-index

  5. PY
    Pen-Chung Yew

    University of Minnesota, United States

    11 publications · 435 citations

    10

    h-index

1–5 of 825

Venues

  1. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 24 publications · 2.2K citations

    18

    h-index

  2. ACM SIGPLAN Notices

    21 publications · 1.3K citations

    16

    h-index

  3. IEEE Transactions on Computers

    14 publications · 1.3K citations

    13

    h-index

  4. ACM Transactions on Architecture and Code Optimization

    TACO · 8 publications · 125 citations

    8

    h-index

  5. Parallel Computing

    7 publications · 430 citations

    7

    h-index

1–5