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Benefits from using mixed precision computations in the ELPA-AEO and ESSEX-II eigensolver projects


We first briefly report on the status and recent achievements of the ELPA-AEO (Eigen value 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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The authors thank the unknown referees for their valuable comments that helped to improve and clarify the presentation.

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Correspondence to Bruno Lang.

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This work has been supported by the Deutsche Forschungsgemeinschaft through the priority programme 1648 “Software for Exascale Computing” (SPPEXA) under the project ESSEX-II and by the Federal Ministry of Education and Research through the project “Eigenvalue soLvers for Petaflop Applications—Algorithmic Extensions and Optimizations” (ELPA-AEO) under Grant No. 01H15001.

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Alvermann, A., Basermann, A., Bungartz, HJ. et al. Benefits from using mixed precision computations in the ELPA-AEO and ESSEX-II eigensolver projects. Japan J. Indust. Appl. Math. 36, 699–717 (2019).

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  • Eigensolver
  • Parallel
  • Mixed precision

Mathematics Subject Classification

  • 65F15
  • 65F25
  • 65Y05
  • 65Y99