Gpu Integration
GPU Integration is a technical framework within Heterogeneous System Architecture that enables the coherent and low-latency coupling of graphics processing units with central processing units, distinguished by its unified memory addressing, fine-grained data sharing, and synchronized task parallelism to accelerate general-purpose computing workloads.
241
Publications
13.1K
Citations
1.1K
Authors
373
Institutions
Publications per year
2017–2026
97
241
Christine M. Isborn, Nathan Luehr, Ivan S. Ufimtsev et al. · Journal of Chemical Theory and Computation · 2011 · 226 citations · Full text
Natural Sciences, Chemistry, Physics +17
The case for GPGPU spatial multitasking
Jacob T. Adriaens, Katherine Compton, Nam Sung Kim et al. · 2012 · 214 citations
1–5 of 241
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373

Centre National de la Recherche Scientifique
Paris, France
11 h-index
58 publications
1.3K citations
Tsinghua University
Beijing, China
11 h-index
28 publications
1.2K citations
Intel (United States)
Santa Clara, United States
8 h-index
44 publications
2.4K citations
The University of Texas at Austin
Austin, United States
8 h-index
14 publications
1.4K citations
National University of Singapore
Singapore, Singapore
7 h-index
9 publications
353 citations
University of Illinois Urbana-Champaign
Urbana, United States
6 h-index
17 publications
1.2K citations

Renmin University of China
Beijing, China
6 h-index
27 publications
663 citations
Stanford University
Stanford, United States
5 h-index
11 publications
1.2K citations
1–8 of 373
Repository · 9 publications · 2.2K citations
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TPDS · 5 publications · 195 citations
5
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3 publications · 435 citations
3
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JCTC · 3 publications · 319 citations
3
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CAGEO · 3 publications · 35 citations
3
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