GPU Performance Profiling is a systematic analytical method used in parallel computing to quantitatively measure, characterize, and evaluate the execution behavior, resource utilization, and performance bottlenecks of applications running on a graphics processing unit.
291
Publications
15.5K
Citations
923
Authors
289
Institutions
Publications per year
2017–2026
102
Publications
291
Benchmarking GPUs to tune dense linear algebra
В. М. Волков, James Demmel · 2008 · 726 citations
Benchmarking GPUs to tune dense linear algebra
J. Demmel · 2008 · 475 citations
Demystifying GPU microarchitecture through microbenchmarking
Henry Wong, Misel-Myrto Papadopoulou, Maryam Sadooghi-Alvandi et al. · 2010 · 447 citations
1–5 of 291
Authors
923
- DN
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- MW
6
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- XS
6
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- MO
5
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- JM
5
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1–5 of 923
Institutions
289
Intel (United States)
Santa Clara, United States
11 h-index
26 publications
933 citations
Georgia Institute of Technology
Atlanta, United States
9 h-index
25 publications
2.2K citations
Nvidia (United States)
Santa Clara, United States
9 h-index
24 publications
917 citations
Los Alamos National Laboratory
Los Alamos, United States
8 h-index
17 publications
760 citations
William & Mary
Williamsburg, United States
8 h-index
25 publications
1.9K citations
University of Illinois Urbana-Champaign
Urbana, United States
7 h-index
20 publications
891 citations
North Carolina State University
Raleigh, United States
7 h-index
13 publications
397 citations
Oak Ridge National Laboratory
Oak Ridge, United States
6 h-index
15 publications
1.4K citations
1–8 of 289
Venues
- Journal of Parallel and Distributed Computing
6 publications · 764 citations
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- IEEE Transactions on Parallel and Distributed Systems
TPDS · 6 publications · 230 citations
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- Concurrency and Computation Practice and Experience
5 publications · 146 citations
5
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- Parallel Computing
4 publications · 184 citations
4
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- ACM SIGARCH Computer Architecture News
3 publications · 58 citations
3
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1–5