cuVASP: A GPU-Accelerated Plane-Wave Electronic-Structure Code

Abstract

We report about a source-code modification of the density-functional program suite VASP which greatly benefits from the use of graphics-processing units (GPUs). The blocked Davidson iteration scheme (EDDAV) has been optimized for GPUs and gains speed-ups of up to 3.39 on S1070 devices and of 6.97 on a C2050 device. Using the Fermi card, the code reaches an impressive 61.7% efficiency but does not suffer from any accuracy losses. The algorithmic bottleneck lies in the multiplication of rectangular matrices. We also give some initial thoughts about introducing a different level of parallelism in order to harness the computational power of multi-GPU installations.

Keywords

Fast Fourier Transformation Memory Transfer Rectangular Matrice CUDA Kernel Vector Computing 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    S. Maintz, B. Eck, R. Dronskowski, Comp. Phys. Commun. 2011, 182, 1421. CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Stefan Maintz
    • 1
  • Bernhard Eck
    • 1
  • Richard Dronskowski
    • 1
  1. 1.Institute of Inorganic ChemistryRWTH Aachen UniversityAachenGermany

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