Dataflow Operators

Dataflow Operators is a computational construct within dataflow modeling that represents elementary functions or transformations which process incoming data tokens and produce outgoing data tokens, distinguished by their role in defining the operational semantics of a dataflow graph through explicit input-output dependencies.

94

Publications

4.2K

Citations

273

Authors

100

Institutions

Publications per year

2017–2026

21

Authors

273

  1. SS
    Shuvra S. Bhattacharyya

    University of Maryland, College Park, United States

    7 publications · 119 citations

    7

    h-index

  2. AA
    Arvind Arvind

    Massachusetts Institute of Technology, United States

    5 publications · 174 citations

    5

    h-index

  3. MG
    Michael Gubanov

    The University of Texas at San Antonio, United States

    4 publications · 112 citations

    4

    h-index

  4. CJ
    Christopher Jermaine

    University of Florida, United States

    4 publications · 112 citations

    4

    h-index

  5. LL
    Luis L. Perez

    Rice University, United States

    4 publications · 112 citations

    4

    h-index

1–5 of 273

Venues

  1. Journal of Signal Processing Systems

    4 publications · 56 citations

    4

    h-index

  2. Journal of Parallel and Distributed Computing

    3 publications · 69 citations

    3

    h-index

  3. Proceedings of the VLDB Endowment

    PVLDB · 3 publications · 95 citations

    3

    h-index

  4. ACM SIGMOD Record

    2 publications · 40 citations

    2

    h-index

  5. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 2 publications · 421 citations

    2

    h-index

1–5