Scalability Modeling

Scalability Modeling is a formal analytical framework that characterizes the performance behavior of parallel systems under varying scales of workload or resources by quantifying the relationship between system size and efficiency, distinguishing it from general performance models through its explicit focus on growth-oriented predictability and bottleneck identification.

229

Publications

9.6K

Citations

648

Authors

241

Institutions

Publications per year

2017–2026

51

Authors

648

  1. DJ
    Darren J. Kerbyson

    Los Alamos National Laboratory, United States

    7 publications · 714 citations

    7

    h-index

  2. JS
    Jeffrey S. Vetter

    Oak Ridge National Laboratory, United States

    6 publications · 337 citations

    6

    h-index

  3. TH
    Torsten Hoefler

    ETH Zurich, Switzerland

    5 publications · 281 citations

    5

    h-index

  4. AH
    Adolfy Hoisie

    Los Alamos National Laboratory, United States

    5 publications · 332 citations

    5

    h-index

  5. XS
    Xian‐He Sun

    Illinois Institute of Technology, United States

    4 publications · 291 citations

    4

    h-index

1–5 of 648

Venues

  1. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 8 publications · 678 citations

    8

    h-index

  2. Journal of Parallel and Distributed Computing

    5 publications · 174 citations

    5

    h-index

  3. 4

    h-index

  4. Computer

    3 publications · 223 citations

    3

    h-index

  5. ACM SIGMETRICS Performance Evaluation Review

    PER · 2 publications · 120 citations

    2

    h-index

1–5