Pattern-based Instruction Selection

Pattern-Based Instruction Selection is a method within the field of code generation that uses predefined syntactic and semantic patterns to match intermediate representations to target machine instructions, distinguishing itself by systematically leveraging pattern-matching rules to optimize instruction selection in compilers.

13

Publications

409

Citations

27

Authors

11

Institutions

Publications per year

2017–2026

1

Authors

27

  1. RR
    Robert R. Henry

    University of California, Berkeley, United States

    2 publications · 45 citations

    2

    h-index

  2. RA
    Robert A. Schulman

    University of California, Berkeley, United States

    2 publications · 45 citations

    2

    h-index

  3. SL
    Susan L. Graham

    University of California, Berkeley, United States

    2 publications · 45 citations

    2

    h-index

  4. TW
    T.C. Wilson

    University of Guelph, Canada

    1 publications · 13 citations

    1

    h-index

  5. EC
    Emmanuel Casseau

    Institut de Recherche en Informatique et Systèmes Aléatoires, France

    1 publications · 11 citations

    1

    h-index

1–5 of 27

Venues

  1. ACM SIGPLAN Notices

    1 publications · 10 citations

    1

    h-index

  2. 1

    h-index

  3. Instructional Science

    1 publications · 20 citations

    1

    h-index

1–3