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Polymer Field-Theory Simulations on Graphics Processing Units

Kris T. Delaney, Glenn H. Fredrickson
Materials Research Laboratory, University of California, Santa Barbara, CA 93106-5121, USA
arXiv:1204.5434v1 [physics.comp-ph] (24 Apr 2012)

@article{2012arXiv1204.5434D,

   author={Delaney}, K.~T. and {Fredrickson}, G.~H.},

   title={"{Polymer Field-Theory Simulations on Graphics Processing Units}"},

   journal={ArXiv e-prints},

   archivePrefix={"arXiv"},

   eprint={1204.5434},

   primaryClass={"physics.comp-ph"},

   keywords={Physics – Computational Physics, Condensed Matter – Soft Condensed Matter, Condensed Matter – Statistical Mechanics},

   year={2012},

   month={apr},

   adsurl={http://adsabs.harvard.edu/abs/2012arXiv1204.5434D},

   adsnote={Provided by the SAO/NASA Astrophysics Data System}

}

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We report the first CUDA graphics-processing-unit (GPU) implementation of the polymer field-theoretic simulation framework for determining fully fluctuating expectation values of equilibrium properties for periodic and select aperiodic polymer systems. Our implementation is suitable both for self-consistent field theory (mean-field) solutions of the field equations, and for fully fluctuating simulations using the complex Langevin approach. Running on NVIDIA Tesla T20 series GPUs, we find double-precision speedups of up to 30x compared to single-core serial calculations on a recent reference CPU, while single-precision calculations proceed up to 60x faster than those on the single CPU core. Due to intensive communications overhead, an MPI implementation running on 64 CPU cores remains two times slower than a single GPU.
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