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Cosmological Calculations on the GPU

Deborah Bard, Matthew Bellis, Mark T. Allen, Hasmik Yepremyan, Jan M. Kratochvil
Kavli Institute for Particle Astrophysics and Cosmology, Stanford, CA 94309
arXiv:1208.3658v1 [astro-ph.IM] (17 Aug 2012)

@article{2012arXiv1208.3658B,

   author={Bard}, D. and {Bellis}, M. and {Allen}, M.~T. and {Yepremyan}, H. and {Kratochvil}, J.~M.},

   title={"{Cosmological Calculations on the GPU}"},

   journal={ArXiv e-prints},

   archivePrefix={"arXiv"},

   eprint={1208.3658},

   primaryClass={"astro-ph.IM"},

   keywords={Astrophysics – Instrumentation and Methods for Astrophysics, Astrophysics – Cosmology and Extragalactic Astrophysics},

   year={2012},

   month={aug},

   adsurl={http://adsabs.harvard.edu/abs/2012arXiv1208.3658B},

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

}

CONTEXT: Cosmological measurements require the calculation of nontrivial quantities over large datasets. The next generation of survey telescopes (such as DES, PanSTARRS, and LSST) will yield measurements of billions of galaxies. The scale of these datasets, and the nature of the calculations involved, make cosmological calculations ideal models for implementation on graphics processing units (GPUs). AIMS: We consider two cosmological calculations, the two-point angular correlation function and the aperture mass statistic, and aim to improve the calculation time by constructing code for calculating them on the GPU. METHODS: Using CUDA, we implement the two algorithms on the GPU and compare the calculation speeds to comparable code run on the CPU. RESULTS: We obtain a code speed-up of between 10 – 180x faster, compared to performing the same calculation on the CPU. The code has been made publicly available. CONCLUSIONS: GPUs are a useful tool for cosmological calculations, even for datasets the size of current surveys, allowing calculations to be made one or two orders of magnitude faster.
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