Data Flow Scheduling

Data Flow Scheduling is a microarchitectural optimization technique that determines the order of instruction execution based on the availability of input operands rather than program order, thereby enabling parallelism through dynamic dependency resolution.

163

Publications

6.6K

Citations

342

Authors

161

Institutions

Publications per year

2017–2026

14

Variants

Dataflow Scheduling

Authors

342

  1. SS
    Shuvra S. Bhattacharyya

    University of Maryland, College Park, United States

    11 publications · 416 citations

    11

    h-index

  2. EH
    Edwin H.‐M. Sha

    Chongqing University, China

    8 publications · 367 citations

    8

    h-index

  3. KK
    Keshab K. Parhi

    University of Minnesota, United States

    8 publications · 531 citations

    8

    h-index

  4. EA
    Edward A. Lee

    University of California, Berkeley, United States

    7 publications · 782 citations

    7

    h-index

  5. SH
    Soonhoi Ha

    Seoul National University, South Korea

    7 publications · 208 citations

    7

    h-index

1–5 of 342

Venues

  1. 6

    h-index

  2. IEEE Transactions on Computers

    5 publications · 525 citations

    5

    h-index

  3. 4

    h-index

  4. Proceedings of the International Conference on Parallel Processing

    Conference · 3 publications · 51 citations

    3

    h-index

  5. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 3 publications · 230 citations

    3

    h-index

1–5