  Large scale electronic structure calculations require modern high performance
computing (HPC) resources and, as important, mature HPC applications that can
make efficient use of those. Real-space grid-based applications of Density
Functional Theory (DFT) using the Projector Augmented Wave method (PAW) can
give the same accuracy as DFT codes relying on a plane wave basis set but
exhibit an improved scalability on distributed memory machines. The projection
operations of the PAW Hamiltonian are known to be the performance critical part
due to their limitation by the available memory bandwidth. We investigate on
the utility of a 3D factorizable basis of Hermite functions for the localized
PAW projector functions which allows to reduce the bandwidth requirements for
the grid representation of the projector functions in projection operations.
Additional on-the-fly sampling of the 1D basis functions eliminates the memory
transfer almost entirely. For an quantitative assessment of the expected memory
bandwidth savings we show performance results of a first implementation on
GPUs. Finally, we suggest a PAW generation scheme adjusted to the analytically
given projector functions.
