Parallel Eigenvalue Computation
Parallel Eigenvalue Computation is a computational method within numerical linear algebra that determines eigenvalues of large matrices by simultaneously distributing and processing subproblems across multiple processors to accelerate convergence.
271
Publications
12.4K
Citations
525
Authors
240
Institutions
Publications per year
2017–2026
21
271
Matrix Eigensystem Routines--EISPACK Guide
Thomas Aird, Brian T. Smith, J. M. Boyle et al. · Mathematics of Computation · 1976 · 615 citations
Natural Sciences, Computer Engineering, Finite Element Analysis +11
A Proposal for Toeplitz Matrix Calculations
Gilbert Strang · Studies in Applied Mathematics · 1986 · 429 citations
A Survey of Parallel Algorithms in Numerical Linear Algebra
Don Heller · SIAM Review · 1978 · 339 citations · Full text
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240

Lawrence Berkeley National Laboratory
Berkeley, United States
11 h-index
32 publications
1.5K citations

Oak Ridge National Laboratory
Oak Ridge, United States
11 h-index
27 publications
632 citations
University of Tennessee at Knoxville
Knoxville, United States
9 h-index
21 publications
528 citations

University of Minnesota
Minneapolis, United States
7 h-index
12 publications
392 citations
Universitat Politècnica de València
Valencia, Spain
7 h-index
13 publications
336 citations

University of Manchester
Manchester, United Kingdom
6 h-index
6 publications
281 citations
Iowa State University
Ames, United States
6 h-index
12 publications
694 citations
University of California, Berkeley
Berkeley, United States
5 h-index
9 publications
482 citations
1–8 of 240
31 publications · 1.2K citations
21
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21 publications · 646 citations
14
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10 publications · 1.5K citations
10
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9 publications · 655 citations
9
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TOMS · 7 publications · 218 citations
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