12947

Cholla : A New Massively-Parallel Hydrodynamics Code For Astrophysical Simulation

Evan E. Schneider, Brant E. Robertson
Steward Observatory, University of Arizona, 933 North Cherry Avenue, Tucson, AZ 85721, USA
arXiv:1410.4194 [astro-ph.IM], (15 Oct 2014)

@article{2014arXiv1410.4194S,

   author={Schneider}, E.~E. and {Robertson}, B.~E.},

   title={"{Cholla : A New Massively-Parallel Hydrodynamics Code For Astrophysical Simulation}"},

   journal={ArXiv e-prints},

   archivePrefix={"arXiv"},

   eprint={1410.4194},

   primaryClass={"astro-ph.IM"},

   keywords={Astrophysics – Instrumentation and Methods for Astrophysics, Physics – Computational Physics, Physics – Fluid Dynamics},

   year={2014},

   month={oct},

   adsurl={http://adsabs.harvard.edu/abs/2014arXiv1410.4194S},

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

}

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We present Cholla (Computational Hydrodynamics On ParaLLel Architectures), a new three-dimensional hydrodynamics code that harnesses the power of graphics processing units (GPUs) to accelerate astrophysical simulations. Cholla models the Euler equations on a static mesh using state-of-the-art techniques, including the unsplit Corner Transport Upwind (CTU) algorithm, a variety of exact and approximate Riemann solvers, and multiple spatial reconstruction techniques including the piecewise parabolic method (PPM). Cholla performs all hydrodynamical calculations in a massively-parallel manner, using GPUs to evolve the fluid properties of thousands of cells simultaneously while leaving the power of central processing units (CPUs) available for modeling additional physics. On current hardware, Cholla can update more than ten million cells per GPU-second while using an exact Riemann solver and PPM reconstruction with the CTU algorithm. Owing to the massively-parallel architecture of GPUs and the design of the Cholla code, astrophysical simulations with physically interesting grid resolutions (> 256^3) can easily be computed on a single device. Cholla utilizes the Message Passing Interface library to extend calculations onto multiple devices, and exhibits nearly ideal scaling beyond 100,000 GPU cores. The excellent performance of Cholla is demonstrated on a suite of test problems that highlights the physical accuracy of our modeling and provides a useful comparison to other codes. We also provide a set of Appendices that uniformly documents all of the reconstruction methods and Riemann solvers implemented in Cholla, and discusses strengths and weakness of the various methods.
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