activity
20172026
most citedGPU-Acceleration of the ELPA2 Distributed Eigensolver for Dense Symmetric and Hermitian Eigenproblems

51 citations · 104 across the 7 of their papers we have counts for

collaborators

7 papers

cond-mat.soft2026

ESPResSo++: A Fast and Extensible Molecular Simulation Package for Coarse-Grained Models

Zhen-Hao Xu, James Vance, Nikita Tretyakov +9

ESPResSo++ is an open-source software package for molecular dynamics (MD) simulations with a particular emphasis on coarse-grained (CG) models of soft matter systems. Written in C+…

gr-qc2020★ 2 cited

Vortex solutions of Liouville equation and quasi spherical surfaces

Alfredo Iorio, Pavel Kus

We identify the two-dimensional surfaces corresponding to certain solutions of the Liouville equation of importance for mathematical physics, the non-topological Chern-Simons (or J…

physics.comp-ph2020★ 51 cited

GPU-Acceleration of the ELPA2 Distributed Eigensolver for Dense Symmetric and Hermitian Eigenproblems

Victor Wen-zhe Yu, Jonathan Moussa, Pavel Kůs +5

The solution of eigenproblems is often a key computational bottleneck that limits the tractable system size of numerical algorithms, among them electronic structure theory in chemi…

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…

math.NA2017★ 13 cited

Coupling parallel adaptive mesh refinement with a nonoverlapping domain decomposition solver

Pavel Kůs, Jakub Šístek

We study the effect of adaptive mesh refinement on a parallel domain decomposition solver of a linear system of algebraic equations. These concepts need to be combined within a par…