Graph-based Parallel Programming

Graph-Based Parallel Programming is a parallel programming model that represents computational tasks and their dependencies as a directed graph, where nodes denote tasks and edges represent data or control dependencies, enabling explicit modeling of concurrency and coordination through graph structures.

9

Publications

240

Citations

24

Authors

10

Institutions

Publications per year

2017–2026

1

Authors

24

  1. KZ
    Kang Zhang

    Macquarie University, Australia

    2 publications · 27 citations

    2

    h-index

  2. DA
    Duane A. Bailey

    Williams College, United States

    2 publications · 38 citations

    2

    h-index

  3. JE
    Janice E. Cuny

    University of Oregon, United States

    2 publications · 38 citations

    2

    h-index

  4. NS
    Nenad Stankovic

    Macquarie University, Australia

    2 publications · 27 citations

    2

    h-index

  5. YT
    Yuanyuan Tian

    IBM Research - Almaden, United States

    1 publications · 89 citations

    1

    h-index

1–5 of 24

Venues

  1. Parallel and Distributed Processing Techniques and Applications

    Conference · 1 publications · 18 citations

    1

    h-index

  2. International Journal of Parallel Programming

    1 publications · 27 citations

    1

    h-index

  3. ACM SIGOPS Operating Systems Review

    1 publications · 25 citations

    1

    h-index

  4. 1

    h-index

  5. Languages and Compilers for Parallel Computing

    Conference · 1 publications · 11 citations

    1

    h-index

1–5