Real-space density functional theory on graphical processing units: computational approach and comparison to Gaussian basis set methods
Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, MA 02138, United States
arXiv:1306.2953 [physics.comp-ph], (12 Jun 2013)
@article{2013arXiv1306.2953A,
author={Andrade}, X. and {Aspuru-Guzik}, A.},
title={"{Real-space density functional theory on graphical processing units: computational approach and comparison to Gaussian basis set methods}"},
journal={ArXiv e-prints},
archivePrefix={"arXiv"},
eprint={1306.2953},
primaryClass={"physics.comp-ph"},
keywords={Physics – Computational Physics, Condensed Matter – Other Condensed Matter},
year={2013},
month={jun},
adsurl={http://adsabs.harvard.edu/abs/2013arXiv1306.2953A},
adsnote={Provided by the SAO/NASA Astrophysics Data System}
}
We discuss the application of graphical processing units (GPUs) to accelerate real-space density functional theory (DFT) calculations. To make our implementation efficient, we have developed a scheme to expose the data parallelism available in the DFT approach; this is applied to the different procedures required for a real-space DFT calculation. We present results for current-generation GPUs from AMD and Nvidia, which show that our scheme, implemented in the free code OCTOPUS, can reach a sustained performance of up to 90 GFlops for a single GPU, representing an important speed-up when compared to the CPU version of the code. Moreover, for some systems our implementation can outperform a GPU Gaussian basis set code, showing that the real-space approach is a competitive alternative for DFT simulations on GPUs.
June 14, 2013 by hgpu
