Parallel Performance Debugging

Parallel Performance Debugging is a systematic method for identifying and resolving performance bottlenecks in parallel computing systems by analyzing deviations from expected execution behavior, resource utilization, and scalability patterns.

37

Publications

1.1K

Citations

110

Authors

42

Institutions

Publications per year

2017–2026

1

Authors

110

  1. MS
    Martin Schulz

    Lawrence Livermore National Laboratory, United States

    7 publications · 165 citations

    7

    h-index

  2. BR
    Bronis R. de Supinski

    Lawrence Livermore National Laboratory, United States

    5 publications · 167 citations

    5

    h-index

  3. DH
    Dong H. Ahn

    Lawrence Livermore National Laboratory, United States

    5 publications · 120 citations

    5

    h-index

  4. TG
    Todd Gamblin

    Lawrence Livermore National Laboratory, United States

    5 publications · 115 citations

    5

    h-index

  5. IL
    Ignacio Laguna

    Lawrence Livermore National Laboratory, United States

    4 publications · 103 citations

    4

    h-index

1–5 of 110

Venues

  1. ACM SIGPLAN Notices

    3 publications · 41 citations

    3

    h-index

  2. Journal of Parallel and Distributed Computing

    3 publications · 66 citations

    3

    h-index

  3. 2

    h-index

  4. Proceedings of the International Conference on Parallel Processing

    Conference · 1 publications · 10 citations

    1

    h-index

  5. IEEE Transactions on Software Engineering

    TSE · 1 publications · 14 citations

    1

    h-index

1–5