Benefits from using mixed precision computations in the ELPA-AEO and ESSEX-II eigensolver projects
Authors:
Andreas Alvermann,
Achim Basermann,
Hans-Joachim Bungartz,
Christian Carbogno,
Dominik Ernst,
Holger Fehske,
Yasunori Futamura,
Martin Galgon,
Georg Hager,
Sarah Huber,
Thomas Huckle,
Akihiro Ida,
Akira Imakura,
Masatoshi Kawai,
Simone Köcher,
Moritz Kreutzer,
Pavel Kus,
Bruno Lang,
Hermann Lederer,
Valeriy Manin,
Andreas Marek,
Kengo Nakajima,
Lydia Nemec,
Karsten Reuter,
Michael Rippl
, et al. (8 additional authors not shown)
Abstract:
We first briefly report on the status and recent achievements of the ELPA-AEO (Eigenvalue Solvers for Petaflop Applications - Algorithmic Extensions and Optimizations) and ESSEX II (Equipping Sparse Solvers for Exascale) projects. In both collaboratory efforts, scientists from the application areas, mathematicians, and computer scientists work together to develop and make available efficient highl…
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We first briefly report on the status and recent achievements of the ELPA-AEO (Eigenvalue Solvers for Petaflop Applications - Algorithmic Extensions and Optimizations) and ESSEX II (Equipping Sparse Solvers for Exascale) projects. In both collaboratory efforts, scientists from the application areas, mathematicians, and computer scientists work together to develop and make available efficient highly parallel methods for the solution of eigenvalue problems. Then we focus on a topic addressed in both projects, the use of mixed precision computations to enhance efficiency. We give a more detailed description of our approaches for benefiting from either lower or higher precision in three selected contexts and of the results thus obtained.
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Submitted 4 June, 2018;
originally announced June 2018.