Gshare Prediction

Gshare Prediction is a dynamic branch prediction technique that belongs to the class of two-level adaptive predictors, distinguished by its use of a global history register XORed with the branch address to index a pattern history table, thereby enabling more accurate prediction of correlated branches.

16

Publications

1.1K

Citations

37

Authors

11

Institutions

Publications per year

2017–2026

1

Variants

Gshare Branch Prediction

Authors

37

  1. SM
    Srilatha Manne

    University of Colorado Boulder, United States

    2 publications · 29 citations

    2

    h-index

  2. AE
    A.N. Eden

    University of Michigan, United States

    2 publications · 227 citations

    2

    h-index

  3. AK
    Artur Klauser

    University of Colorado Boulder, United States

    2 publications · 29 citations

    2

    h-index

  4. DG
    Dirk Grunwald

    University of Colorado Boulder, United States

    2 publications · 29 citations

    2

    h-index

  5. TM
    Trevor Mudge

    University of Michigan, United States

    2 publications · 227 citations

    2

    h-index

1–5 of 37

Venues

  1. IEEE Access

    1 publications · 10 citations

    1

    h-index

  2. OpenGrey (Institut de l'Information Scientifique et Technique)

    Repository · 1 publications · 28 citations

    1

    h-index

  3. Defense Technical Information Center (DTIC)

    Repository · 1 publications · 17 citations

    1

    h-index

  4. ACM Transactions on Architecture and Code Optimization

    TACO · 1 publications · 65 citations

    1

    h-index

  5. Ghent University Academic Bibliography (Ghent University)

    Repository · 1 publications · 69 citations

    1

    h-index

1–5