Data Movement Optimization

Data Movement Optimization is a computational strategy within heterogeneous computing that minimizes latency and energy overhead by orchestrating the transfer of data between heterogeneous processing units and memory hierarchies through scheduling, placement, and access pattern refinement.

492

Publications

27.2K

Citations

1.6K

Authors

384

Institutions

Publications per year

2017–2026

215

Authors

1.6K

  1. OM
    Onur Mutlu

    Carnegie Mellon University, United States

    18 publications · 1.4K citations

    16

    h-index

  2. JG
    Juan Gómez-Luna

    ETH Zurich, Switzerland

    12 publications · 696 citations

    12

    h-index

  3. SG
    Saugata Ghose

    Carnegie Mellon University, United States

    9 publications · 991 citations

    9

    h-index

  4. MK
    Mahmut Kandemir

    Pennsylvania State University, United States

    9 publications · 536 citations

    9

    h-index

  5. XM
    Xiaosong Ma

    North Carolina State University, United States

    8 publications · 240 citations

    8

    h-index

1–5 of 1.6K

Venues

  1. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 15 publications · 430 citations

    14

    h-index

  2. IEEE Transactions on Computers

    11 publications · 452 citations

    11

    h-index

  3. arXiv (Cornell University)

    Repository · 14 publications · 348 citations

    11

    h-index

  4. ACM SIGPLAN Notices

    7 publications · 580 citations

    7

    h-index

  5. IEEE Micro

    5 publications · 291 citations

    5

    h-index

1–5