This title appears in the Scientific Report :
2016
Please use the identifier:
http://dx.doi.org/10.1016/j.cpc.2016.10.003 in citations.
High-performance generation of the Hamiltonian and Overlap matrices in FLAPW methods
High-performance generation of the Hamiltonian and Overlap matrices in FLAPW methods
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 kerne...
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Personal Name(s): | Di Napoli, Edoardo (Corresponding author) |
---|---|
Peise, Elmar (Corresponding author) / Hrywniak, Markus (Corresponding author) / Bientinesi, Paolo (Corresponding author) | |
Contributing Institute: |
Jülich Supercomputing Center; JSC JARA - HPC; JARA-HPC |
Published in: | Computer physics communications, 211 (2017) S. 61-72 |
Imprint: |
Amsterdam
North Holland Publ. Co.
2017
|
DOI: |
10.1016/j.cpc.2016.10.003 |
Document Type: |
Journal Article |
Research Program: |
Simulation and Data Laboratory Quantum Materials (SDLQM) Computational Science and Mathematical Methods |
Publikationsportal JuSER |
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 Legacy codes suffer from the additional curse of rigid design choices based on outdated performance metrics (e.g. minimization of memory footprint).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 (BLAS3) kernels. The resulting algorithm guarantees an increased performance and an extended life span of this code, enabling larger scale simulations. |