Cuda Programming

CUDA Programming is a parallel programming model and computing platform that extends the C/C++ languages to enable direct control over the GPU architecture by allowing developers to write functions, known as kernels, that execute in parallel across thousands of threads organized in grids, blocks, and warps, thereby accelerating data-intensive computations.

692

Publications

62.8K

Citations

2K

Authors

656

Institutions

Publications per year

2017–2026

141

Authors

2K

  1. WH
    Wen‐mei Hwu

    University of Illinois Urbana-Champaign, United States

    10 publications · 495 citations

    10

    h-index

  2. SL
    Seyong Lee

    Oak Ridge National Laboratory, United States

    9 publications · 887 citations

    9

    h-index

  3. BS
    Bertil Schmidt

    Johannes Gutenberg University Mainz, Germany

    8 publications · 325 citations

    8

    h-index

  4. MF
    Massimiliano Fatica

    Nvidia (United States), United States

    7 publications · 269 citations

    7

    h-index

  5. MG
    Michael Garland

    University of Illinois Urbana-Champaign, United States

    7 publications · 4K citations

    7

    h-index

1–5 of 2K

Venues

  1. Computer Physics Communications

    13 publications · 651 citations

    12

    h-index

  2. arXiv (Cornell University)

    Repository · 15 publications · 4.9K citations

    11

    h-index

  3. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 11 publications · 766 citations

    11

    h-index

  4. Procedia Computer Science

    11 publications · 248 citations

    10

    h-index

  5. ACM SIGPLAN Notices

    9 publications · 542 citations

    9

    h-index

1–5