Parallel Matrix Computation
Parallel Matrix Computation is a computational framework within matrix computation that leverages concurrent processing across multiple processors or cores to perform matrix operations by partitioning data and distributing tasks, thereby reducing overall execution time through simultaneous arithmetic and memory access.
942
Publications
45K
Citations
1.9K
Authors
597
Institutions
Publications per year
2017–2026
87
942
A set of level 3 basic linear algebra subprograms
Jack Dongarra, Jeremy Du Croz, Sven Hammarling et al. · ACM Transactions on Mathematical Software · 1990 · 1.8K citations · Full text
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University of Tennessee at Knoxville
Knoxville, United States
25 h-index
125 publications
8.8K citations
The University of Texas at Austin
Austin, United States
21 h-index
63 publications
5.5K citations

Oak Ridge National Laboratory
Oak Ridge, United States
21 h-index
52 publications
3.6K citations
University of California, Berkeley
Berkeley, United States
18 h-index
57 publications
3.6K citations
University of Illinois Urbana-Champaign
Urbana, United States
16 h-index
41 publications
1.7K citations

University of Manchester
Manchester, United Kingdom
14 h-index
31 publications
2.2K citations

Universitat Jaume I
Castellon, Spain
13 h-index
31 publications
1.1K citations
University of California, Santa Barbara
Santa Barbara, United States
11 h-index
23 publications
2K citations
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40 publications · 2.3K citations
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TOMS · 27 publications · 4.7K citations
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36 publications · 1.5K citations
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21 publications · 1.5K citations
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23 publications · 1.2K citations
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