Performance Prediction

Performance Prediction is a methodological framework within Parallel Performance Analysis that estimates the execution behavior of parallel systems or algorithms under varying conditions by modeling performance metrics such as speedup, scalability, and resource utilization based on architectural, algorithmic, and workload-specific parameters.

3.5K

Publications

162.1K

Citations

10.7K

Authors

2.6K

Institutions

Publications per year

2017–2026

1.4K

Authors

10.7K

  1. SK
    Samuel Kounev

    University of Würzburg, Germany

    15 publications · 692 citations

    13

    h-index

  2. GN
    G.R. Nudd

    University of Warwick, United Kingdom

    13 publications · 1.1K citations

    12

    h-index

  3. DJ
    Darren J. Kerbyson

    Los Alamos National Laboratory, United States

    12 publications · 950 citations

    12

    h-index

  4. SA
    Stephen A. Jarvis

    University of Warwick, United Kingdom

    11 publications · 903 citations

    11

    h-index

  5. JR
    Jamal Rostami

    Colorado School of Mines, United States

    11 publications · 1.5K citations

    11

    h-index

1–5 of 10.7K

Venues

  1. Energy

    39 publications · 2.3K citations

    25

    h-index

  2. Applied Thermal Engineering

    38 publications · 1.7K citations

    25

    h-index

  3. IEEE Access

    31 publications · 1.3K citations

    23

    h-index

  4. Energy Conversion and Management

    32 publications · 1.6K citations

    23

    h-index

  5. Applied Energy

    26 publications · 2K citations

    23

    h-index

1–5