Dynamic Random Access Memory Modeling

Dynamic Random Access Memory Modeling is a computational framework that formally characterizes the behavior, performance, and reliability of dynamic random access memory systems by integrating temporal dynamics, charge leakage effects, and access patterns into predictive models for memory operation and optimization.

43

Publications

2.8K

Citations

164

Authors

42

Institutions

Publications per year

2017–2026

11

Variants

Dram Modeling

Authors

164

  1. MJ
    Matthias Jung

    University of Kaiserslautern, Germany

    5 publications · 109 citations

    5

    h-index

  2. NW
    Norbert Wehn

    University of Kaiserslautern, Germany

    5 publications · 109 citations

    5

    h-index

  3. CW
    Christian Weis

    University of Kaiserslautern, Germany

    4 publications · 94 citations

    4

    h-index

  4. DM
    Deepak M. Mathew

    University of Kaiserslautern, Germany

    3 publications · 62 citations

    3

    h-index

  5. AH
    Atsushi Hiraiwa

    Waseda University, Japan

    2 publications · 57 citations

    2

    h-index

1–5 of 164

Venues

  1. IEEE Electron Device Letters

    2 publications · 37 citations

    2

    h-index

  2. IEEE Transactions on Nuclear Science

    2 publications · 1.2K citations

    2

    h-index

  3. 1

    h-index

  4. Solid-State Electronics

    1 publications · 12 citations

    1

    h-index

  5. Strategic Management Journal

    SMJ · 1 publications · 379 citations

    1

    h-index

1–5