Heterogeneous Computing Architecture

Heterogeneous Computing Architecture is a hardware architecture that integrates functionally distinct processing units—such as CPUs, GPUs, FPGAs, and accelerators—within a single system to enable parallel execution of diverse computational workloads more efficiently than homogeneous architectures.

606

Publications

26.9K

Citations

2.3K

Authors

608

Institutions

Publications per year

2017–2026

214

Authors

2.3K

  1. JD
    Jack Dongarra

    University of Tennessee at Knoxville, United States

    10 publications · 407 citations

    10

    h-index

  2. LB
    Luca Benini

    University of Bologna, Italy

    11 publications · 235 citations

    10

    h-index

  3. PP
    Partha Pratim Pande

    Washington State University, United States

    8 publications · 230 citations

    8

    h-index

  4. JC
    Jason Cong

    University of California, Los Angeles, United States

    7 publications · 420 citations

    7

    h-index

  5. JR
    Janardhan Rao Doppa

    Washington State University, United States

    7 publications · 190 citations

    7

    h-index

1–5 of 2.3K

Venues

  1. Journal of Parallel and Distributed Computing

    12 publications · 904 citations

    12

    h-index

  2. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 11 publications · 720 citations

    11

    h-index

  3. IEEE Micro

    11 publications · 1.2K citations

    11

    h-index

  4. The Journal of Supercomputing

    11 publications · 258 citations

    11

    h-index

  5. IEEE Access

    10 publications · 344 citations

    10

    h-index

1–5