Dataflow Optimization

Dataflow Optimization is a methodological framework within dataflow modeling that systematically enhances the efficiency, performance, or resource utilization of data processing systems by transforming and reorganizing dataflow representations according to specified optimization criteria.

152

Publications

7.4K

Citations

509

Authors

182

Institutions

Publications per year

2017–2026

46

Authors

509

  1. SS
    Shuvra S. Bhattacharyya

    University of Maryland, College Park, United States

    7 publications · 224 citations

    7

    h-index

  2. MM
    Marco Mattavelli

    École Polytechnique Fédérale de Lausanne, Switzerland

    6 publications · 105 citations

    6

    h-index

  3. GR
    Guang R. Gao

    University of Delaware, United States

    4 publications · 135 citations

    4

    h-index

  4. SI
    Stylianos I. Venieris

    Samsung (United Kingdom), United Kingdom

    4 publications · 220 citations

    4

    h-index

  5. CB
    Christos-Savvas Bouganis

    Imperial College London, United Kingdom

    4 publications · 220 citations

    4

    h-index

1–5 of 509

Venues

  1. ACM SIGARCH Computer Architecture News

    5 publications · 276 citations

    5

    h-index

  2. Proceedings of the VLDB Endowment

    PVLDB · 5 publications · 970 citations

    5

    h-index

  3. Future Generation Computer Systems

    FGCS · 4 publications · 56 citations

    4

    h-index

  4. IEEE Transactions on Computers

    3 publications · 53 citations

    3

    h-index

  5. Journal of Parallel and Distributed Computing

    3 publications · 59 citations

    3

    h-index

1–5