Profile-guided Optimization

Profile-Guided Optimization is a compiler optimization technique that uses runtime profiling data to guide the optimization process, distinguishing itself from static optimization methods by leveraging dynamically collected information about program behavior to improve code performance.

131

Publications

11.2K

Citations

317

Authors

99

Institutions

Publications per year

2017–2026

21

Authors

317

  1. WH
    Wen‐mei Hwu

    University of Illinois Urbana-Champaign, United States

    7 publications · 597 citations

    7

    h-index

  2. PK
    P.M.W. Knijnenburg

    Leiden University, Netherlands

    7 publications · 476 citations

    7

    h-index

  3. TK
    T. Kisuki

    Leiden University, Netherlands

    5 publications · 363 citations

    5

    h-index

  4. RB
    Rastislav Bodík

    University of California, Berkeley, United States

    5 publications · 328 citations

    5

    h-index

  5. GO
    Guilherme Ottoni

    Princeton University, United States

    5 publications · 237 citations

    5

    h-index

1–5 of 317

Venues

  1. ACM SIGPLAN Notices

    11 publications · 660 citations

    10

    h-index

  2. Software Practice and Experience

    3 publications · 518 citations

    3

    h-index

  3. IEEE Transactions on Software Engineering

    TSE · 2 publications · 49 citations

    2

    h-index

  4. Symposium on Code Generation and Optimization

    Conference · 2 publications · 31 citations

    2

    h-index

  5. IEEE Transactions on Computers

    2 publications · 43 citations

    2

    h-index

1–5