Kernel Optimization

Kernel Optimization is a methodological contribution in GPU computing that systematically enhances the performance of parallel computational kernels by minimizing execution time, resource usage, or energy consumption through architecture-aware refinements in thread organization, memory access patterns, and instruction-level parallelism.

742

Publications

43.4K

Citations

2.3K

Authors

629

Institutions

Publications per year

2017–2026

259

Authors

2.3K

  1. JD
    Jack Dongarra

    University of Tennessee at Knoxville, United States

    27 publications · 1.8K citations

    18

    h-index

  2. ST
    Stanimire Tomov

    University of Tennessee at Knoxville, United States

    16 publications · 583 citations

    14

    h-index

  3. HA
    Hartwig Anzt

    University of Tennessee at Knoxville, United States

    12 publications · 327 citations

    11

    h-index

  4. GG
    Georgios Goumas

    National Technical University of Athens, Greece

    10 publications · 342 citations

    10

    h-index

  5. RV
    Richard Vuduc

    Georgia Institute of Technology, United States

    9 publications · 1.2K citations

    9

    h-index

1–5 of 2.3K

Venues

  1. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 20 publications · 605 citations

    16

    h-index

  2. arXiv (Cornell University)

    Repository · 21 publications · 2.9K citations

    16

    h-index

  3. Procedia Computer Science

    14 publications · 259 citations

    13

    h-index

  4. ACM SIGPLAN Notices

    13 publications · 400 citations

    12

    h-index

  5. 10

    h-index

1–5