Gpu Performance Modeling
GPU Performance Modeling is a computational framework that predicts the execution behavior and efficiency of graphics processing units under varying workloads by abstracting hardware characteristics and workload dynamics through analytical or statistical methods.
294
Publications
16.1K
Citations
872
Authors
276
Institutions
Publications per year
2017–2026
95
Parents
294
An integrated GPU power and performance model
Sunpyo Hong, Hyesoon Kim · 2010 · 477 citations
Demystifying GPU microarchitecture through microbenchmarking
Henry Wong, Misel-Myrto Papadopoulou, Maryam Sadooghi-Alvandi et al. · 2010 · 447 citations
Understanding the efficiency of ray traversal on GPUs
Timo Aila, Samuli Laine · 2009 · 384 citations
1–5 of 294
872
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276
Georgia Institute of Technology
Atlanta, United States
12 h-index
31 publications
4.8K citations

Oak Ridge National Laboratory
Oak Ridge, United States
10 h-index
24 publications
1.8K citations
Intel (United States)
Santa Clara, United States
8 h-index
15 publications
448 citations
The University of Texas at Austin
Austin, United States
8 h-index
16 publications
793 citations
University of Wisconsin–Madison
Madison, United States
7 h-index
22 publications
2.9K citations
North Carolina State University
Raleigh, United States
6 h-index
13 publications
245 citations
Argonne National Laboratory
Lemont, United States
6 h-index
20 publications
785 citations
University of Illinois Urbana-Champaign
Urbana, United States
6 h-index
17 publications
2.1K citations
1–8 of 276
TPDS · 15 publications · 984 citations
14
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7 publications · 200 citations
7
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6 publications · 287 citations
6
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6 publications · 753 citations
6
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5 publications · 485 citations
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