Multi-gpu Computing

Multi-GPU Computing is a computational paradigm within parallel processing that leverages two or more Graphics Processing Units to collaboratively execute tasks, thereby enhancing performance and scalability beyond single-GPU capabilities.

455

Publications

20K

Citations

1.6K

Authors

526

Institutions

Publications per year

2017–2026

180

Authors

1.6K

  1. KP
    Keshav Pingali

    The University of Texas at Austin, United States

    7 publications · 343 citations

    7

    h-index

  2. MB
    Massimo Bernaschi

    Istituto per le Applicazioni del Calcolo Mauro Picone, Italy

    6 publications · 116 citations

    6

    h-index

  3. DK
    David Kaeli

    Northeastern University, United States

    6 publications · 301 citations

    6

    h-index

  4. TA
    Takayuki Aoki

    Tokyo Institute of Technology, Japan

    6 publications · 122 citations

    6

    h-index

  5. JH
    James H. Anderson

    University of North Carolina at Chapel Hill, United States

    6 publications · 331 citations

    6

    h-index

1–5 of 1.6K

Venues

  1. arXiv (Cornell University)

    Repository · 21 publications · 2.1K citations

    16

    h-index

  2. Computer Physics Communications

    14 publications · 575 citations

    12

    h-index

  3. 9

    h-index

  4. The Journal of Supercomputing

    8 publications · 192 citations

    8

    h-index

  5. 7

    h-index

1–5