Distributed Memory Algorithms
Distributed Memory Algorithms is a class of parallel numerical linear algebra algorithms designed for scalable algorithm design, in which computations are performed on data distributed across multiple processing units with non-uniform memory access, each processor accessing its own local memory exclusively and communicating with others explicitly through message passing to coordinate operations.
296
Publications
15.2K
Citations
651
Authors
260
Institutions
Publications per year
2017–2026
25
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University of California, Berkeley
Berkeley, United States
12 h-index
28 publications
1.4K citations

Lawrence Berkeley National Laboratory
Berkeley, United States
12 h-index
32 publications
1.6K citations
The Ohio State University
Columbus, United States
8 h-index
23 publications
1.2K citations
The University of Texas at Austin
Austin, United States
7 h-index
9 publications
397 citations
Virginia Tech
Blacksburg, United States
6 h-index
12 publications
292 citations
University of Tennessee at Knoxville
Knoxville, United States
6 h-index
16 publications
2.1K citations
University of Illinois Urbana-Champaign
Urbana, United States
5 h-index
6 publications
379 citations

Centre National de la Recherche Scientifique
Paris, France
5 h-index
14 publications
1.4K citations
1–8 of 260
16 publications · 457 citations
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9 publications · 1K citations
9
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9 publications · 438 citations
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TPDS · 6 publications · 184 citations
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5 publications · 504 citations
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