51 citations · 104 across the 7 of their papers we have counts for
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cs.MS2018★ 37 cited
Optimizations of the Eigensolvers in the ELPA Library
P. Kus, A. Marek, S. S. Koecher +6
The solution of (generalized) eigenvalue problems for symmetric or Hermitian matrices is a common subtask of many numerical calculations in electronic structure theory or materials…
physics.comp-ph2018★ 1 cited
Benefits from using mixed precision computations in the ELPA-AEO and ESSEX-II eigensolver projects
Andreas Alvermann, Achim Basermann, Hans-Joachim Bungartz +30
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…
cs.DC2018
Computing the sparse matrix vector product using block-based kernels without zero padding on processors with AVX-512 instructions
Berenger Bramas, Pavel Kus
The sparse matrix-vector product (SpMV) is a fundamental operation in many scientific applications from various fields. The High Performance Computing (HPC) community has therefore…