Heterogeneous Parallel Programming

Heterogeneous Parallel Programming is a computational methodology that orchestrates concurrent execution across diverse processing architectures, such as CPUs, GPUs, and FPGAs, by integrating distinct instruction sets and memory models to exploit the unique performance capabilities of each heterogeneous processing unit.

29

Publications

2.4K

Citations

88

Authors

43

Institutions

Publications per year

2017–2026

7

Authors

88

  1. MK
    Michael Kinsner

    Altera (United States), United States

    2 publications · 49 citations

    2

    h-index

  2. AF
    Alessandro Forin

    Microsoft (United States), United States

    2 publications · 97 citations

    2

    h-index

  3. RB
    Roberto Bisiani

    Carnegie Mellon University, United States

    2 publications · 97 citations

    2

    h-index

  4. JB
    James Brodman

    University of Illinois Urbana-Champaign, United States

    2 publications · 49 citations

    2

    h-index

  5. JR
    Jeff R. Hammond

    Argonne National Laboratory, United States

    2 publications · 49 citations

    2

    h-index

1–5 of 88

Venues

  1. Journal of Parallel and Distributed Computing

    2 publications · 60 citations

    2

    h-index

  2. Scientific Programming

    1 publications · 41 citations

    1

    h-index

  3. Journal of Central South University

    1 publications · 16 citations

    1

    h-index

  4. 1

    h-index

  5. ACM SIGOPS Operating Systems Review

    1 publications · 24 citations

    1

    h-index

1–5