Loop Structure Optimization

Loop Structure Optimization is a computational method in program optimization that specifically enhances the efficiency of loops by restructuring their control flow and reducing redundant computations through transformations such as loop unrolling, fusion, and invariant code motion.

112

Publications

4.2K

Citations

258

Authors

120

Institutions

Publications per year

2017–2026

12

Authors

258

  1. DM
    Daniel M. Lavery

    University of Illinois Urbana-Champaign, United States

    4 publications · 116 citations

    4

    h-index

  2. WH
    Wen‐mei Hwu

    University of Illinois Urbana-Champaign, United States

    4 publications · 116 citations

    4

    h-index

  3. NM
    Nikolay Mateev

    Cornell University, United States

    3 publications · 146 citations

    3

    h-index

  4. TG
    Tobias Grosser

    ETH Zurich, Switzerland

    3 publications · 45 citations

    3

    h-index

  5. JX
    Jingling Xue

    UNSW Sydney, Australia

    3 publications · 83 citations

    3

    h-index

1–5 of 258

Venues

  1. International Journal of Parallel Programming

    4 publications · 292 citations

    4

    h-index

  2. Parallel Computing

    4 publications · 108 citations

    4

    h-index

  3. ACM SIGPLAN Notices

    4 publications · 47 citations

    4

    h-index

  4. 3

    h-index

  5. Journal of Parallel and Distributed Computing

    3 publications · 98 citations

    3

    h-index

1–5