Distributed Linear Algebra
Distributed Linear Algebra is a computational framework within distributed memory parallelism that enables the scalable execution of linear algebra operations across multiple processing units by partitioning matrices and vectors and coordinating computations through message passing.
295
Publications
17.6K
Citations
642
Authors
257
Institutions
Publications per year
2017–2026
110
295
Large-scale matrix factorization with distributed stochastic gradient descent
Rainer Gemulla, Erik Nijkamp, Peter J. Haas et al. · 2011 · 619 citations
L. S. Blackford, Jaeyoung Choi, Andrew Cleary et al. · 1996 · 329 citations
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257
Yale University
New Haven, United States
12 h-index
28 publications
1.9K citations
Carnegie Mellon University
Pittsburgh, United States
12 h-index
32 publications
1.7K citations
University of California, Berkeley
Berkeley, United States
12 h-index
26 publications
3.4K citations
University of Southern California
Los Angeles, United States
9 h-index
18 publications
1.8K citations
Purdue University West Lafayette
West Lafayette, United States
9 h-index
14 publications
1.6K citations
University of Illinois Urbana-Champaign
Urbana, United States
8 h-index
18 publications
652 citations
Seoul National University
Seoul, South Korea
7 h-index
12 publications
640 citations
Iowa State University
Ames, United States
7 h-index
16 publications
439 citations
1–8 of 257
Repository · 23 publications · 945 citations
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10 publications · 740 citations
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7 publications · 367 citations
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6 publications · 372 citations
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6 publications · 525 citations
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