Local Instruction Selection

Local Instruction Selection is a compiler optimization technique that operates within individual basic blocks to map intermediate code expressions to target machine instructions by leveraging local data-flow and pattern-matching strategies distinct from global or inter-procedural methods.

9

Publications

339

Citations

17

Authors

2

Institutions

Publications per year

2017–2026

0

Authors

17

  1. RR
    Robert R. Henry

    University of California, Berkeley, United States

    2 publications · 45 citations

    2

    h-index

  2. MH
    Martin Hopkins

    IBM Research - Thomas J. Watson Research Center, United States

    2 publications · 136 citations

    2

    h-index

  3. MA
    Marc Auslander

    IBM (United States), United States

    2 publications · 136 citations

    2

    h-index

  4. SL
    Susan L. Graham

    University of California, Berkeley, United States

    2 publications · 45 citations

    2

    h-index

  5. RA
    Robert A. Schulman

    University of California, Berkeley, United States

    2 publications · 45 citations

    2

    h-index

1–5 of 17

Institutions

2

  1. University of California, Berkeley

    Berkeley, United States

    2 h-index

    6 publications

    135 citations

  2. IBM Research - Thomas J. Watson Research Center

    Yorktown Heights, United States

    2 h-index

    4 publications

    272 citations

1–2 of 2

Venues

  1. ACM SIGPLAN Notices

    2 publications · 30 citations

    2

    h-index

  2. Parallel and Distributed Processing Techniques and Applications

    Conference · 1 publications · 16 citations

    1

    h-index

1–2