Gpu Architecture

GPU Architecture is a parallel computer architecture specialized for high-throughput execution of data-parallel workloads through a large number of streaming multiprocessors organized around single-instruction, multiple-data (SIMD) or single-instruction, multiple-thread (SIMT) execution models, distinguishing it from general-purpose CPU architectures by its emphasis on massively parallel throughput and memory bandwidth optimization.

3.2K

Publications

162.6K

Citations

9.8K

Authors

1.7K

Institutions

Publications per year

2017–2026

954

Authors

9.8K

  1. JD
    John D. Owens

    University of California, Davis, United States

    30 publications · 5.3K citations

    25

    h-index

  2. BH
    Bingsheng He

    National University of Singapore, Singapore

    30 publications · 2.4K citations

    23

    h-index

  3. WH
    Wen‐mei Hwu

    University of Illinois Urbana-Champaign, United States

    26 publications · 3.4K citations

    21

    h-index

  4. TM
    Tor M. Aamodt

    University of British Columbia, Canada

    24 publications · 2.3K citations

    18

    h-index

  5. DK
    David Kaeli

    Northeastern University, United States

    27 publications · 1.7K citations

    18

    h-index

1–5 of 9.8K

Venues

  1. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 74 publications · 3.5K citations

    32

    h-index

  2. arXiv (Cornell University)

    Repository · 73 publications · 6.7K citations

    31

    h-index

  3. ACM SIGARCH Computer Architecture News

    23 publications · 1.6K citations

    19

    h-index

  4. IEEE Micro

    25 publications · 5.8K citations

    19

    h-index

  5. 19

    h-index

1–5