  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additional curse of rigid design choices based on outdated performance metrics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.
