Real-space density functional theory on graphical processing units: computational approach and comparison to Gaussian basis set methods

Xavier Andrade, Alan Aspuru-Guzik
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}

}

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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.
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