English

High-performance generation of the Hamiltonian and Overlap matrices in FLAPW methods

Computational Engineering, Finance, and Science 2018-01-17 v3 Data Structures and Algorithms Performance Computational Physics

Abstract

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 codes face the difficulty of implementing the mathematical operations in the model in terms of low level optimized kernels offering both performance and portability. Legacy codes suffer from the additional curse of rigid design choices based on outdated performance metrics (e.g. minimization of memory footprint). Using a representative code from the Materials Science community, we propose a methodology to restructure the most expensive operations in terms of an optimized combination of dense linear algebra kernels. The resulting algorithm guarantees an increased performance and an extended life span of this code enabling larger scale simulations.

Keywords

Cite

@article{arxiv.1602.06589,
  title  = {High-performance generation of the Hamiltonian and Overlap matrices in FLAPW methods},
  author = {Edoardo Di Napoli and Elmar Peise and Markus Hrywniak and Paolo Bientinesi},
  journal= {arXiv preprint arXiv:1602.06589},
  year   = {2018}
}

Comments

Second revised version. Corrected notation. Added acknowledgment. 30 pages, 2 figures and two tables. Submitted to a Special Issue of Computer Physics Communication