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
455
3D finite difference computation on GPUs using CUDA
Paulius Micikevicius · 2009 · 518 citations
Ying Shan, T. Ryan Hoens, Jian Jiao et al. · 2016 · 417 citations
1–5 of 455
1.6K
7
h-index
Istituto per le Applicazioni del Calcolo Mauro Picone, Italy
6 publications · 116 citations
6
h-index
6
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6
h-index
University of North Carolina at Chapel Hill, United States
6 publications · 331 citations
6
h-index
1–5 of 1.6K
526

Oak Ridge National Laboratory
Oak Ridge, United States
12 h-index
24 publications
1.8K citations
The University of Texas at Austin
Austin, United States
12 h-index
33 publications
1.6K citations
Tokyo Institute of Technology
Tokyo, Japan
11 h-index
23 publications
851 citations
Institut national de recherche en sciences et technologies du numérique
Le Chesnay-Rocquencourt, France
10 h-index
19 publications
580 citations

Centre National de la Recherche Scientifique
Paris, France
10 h-index
37 publications
2.5K citations
Georgia Institute of Technology
Atlanta, United States
10 h-index
16 publications
900 citations
Nvidia (United States)
Santa Clara, United States
9 h-index
15 publications
938 citations

Pacific Northwest National Laboratory
Richland, United States
8 h-index
24 publications
2.4K citations
1–8 of 526
Repository · 21 publications · 2.1K citations
16
h-index
14 publications · 575 citations
12
h-index
9 publications · 220 citations
9
h-index
8 publications · 192 citations
8
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7 publications · 171 citations
7
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