Probabilistic Power Estimation

Probabilistic Power Estimation is a power estimation method that characterizes energy consumption in computing systems by modeling input workloads and circuit behaviors as stochastic processes to quantify power consumption through probability distributions rather than deterministic point values.

111

Publications

4.8K

Citations

259

Authors

125

Institutions

Publications per year

2017–2026

19

Authors

259

  1. MP
    Massoud Pedram

    University of Southern California, United States

    13 publications · 573 citations

    13

    h-index

  2. KR
    Kaushik Roy

    Purdue University West Lafayette, United States

    6 publications · 138 citations

    6

    h-index

  3. TC
    Tan‐Li Chou

    Purdue University West Lafayette, United States

    6 publications · 150 citations

    6

    h-index

  4. DM
    Diana Marculescu

    Carnegie Mellon University, United States

    5 publications · 236 citations

    5

    h-index

  5. RM
    Radu Mărculescu

    Carnegie Mellon University, United States

    5 publications · 236 citations

    5

    h-index

1–5 of 259

Venues

  1. 5

    h-index

  2. IEEE Transactions on Power Systems

    3 publications · 89 citations

    4

    h-index

  3. 4

    h-index

  4. IEEE Transactions on Mobile Computing

    TMCCI · 2 publications · 81 citations

    2

    h-index

  5. IEEE/ACM International Conference on Computer-Aided Design

    Conference · 2 publications · 118 citations

    2

    h-index

1–5