97 citations · 208 across the 25 of their papers we have counts for
6 papers · 1 filter
Computing formation enthalpies through an explainable machine learning method: the case of Lanthanide Orthophosphates solid solutions
Edoardo Di Napoli, Xinzhe Wu, Thomas Bornhake +1
In the last decade, the use of Machine and Deep Learning (MDL) methods in Condensed Matter physics has seen a steep increase in the number of problems tackled and methods employed.…
Solving the Bethe-Salpeter equation on massively parallel architectures
Xiao Zhang, Sebastian Achilles, Jan Winkelmann +3
The last ten years have witnessed fast spreading of massively parallel computing clusters, from leading supercomputing facilities down to the average university computing center. M…
Non-Linear Least-Squares Optimization of Rational Filters for the Solution of Interior Eigenvalue Problems
Jan Winkelmann, Edoardo Di Napoli
Rational filter functions can be used to improve convergence of contour-based eigensolvers, a popular family of algorithms for the solution of the interior eigenvalue problem. We p…
Hybrid CPU-GPU generation of the Hamiltonian and Overlap matrices in FLAPW methods
Diego Fabregat-Traver, Davor Davidović, Markus Höhnerbach +1
In this paper we focus on the integration of high-performance numerical libraries in ab initio codes and the portability of performance and scalability. The target of our work is F…
Parallel adaptive integration in high-performance functional Renormalization Group computations
Julian Lichtenstein, Jan Winkelmann, David Sánchez de la Peña +2
The conceptual framework provided by the functional Renormalization Group (fRG) has become a formidable tool to study correlated electron systems on lattices which, in turn, provid…
High-performance generation of the Hamiltonian and Overlap matrices in FLAPW methods
Edoardo Di Napoli, Elmar Peise, Markus Hrywniak +1
One of the greatest efforts of computational scientists is to translate the mathematical model describing a class of physical phenomena into large and complex codes. Many of these…