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Up to 700k GPU cores, Kepler, and the Exascale future for simulations of star clusters around black holes

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arxiv 1312.1789 v1 pith:XOG3RZE3 submitted 2013-12-06 astro-ph.IM

Up to 700k GPU cores, Kepler, and the Exascale future for simulations of star clusters around black holes

classification astro-ph.IM
keywords clusterscodeblackhardwareholeskeplerrealsimulations
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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We present direct astrophysical N-body simulations with up to a few million bodies using our parallel MPI/CUDA code on large GPU clusters in China, Ukraine and Germany, with different kinds of GPU hardware. These clusters are directly linked under the Chinese Academy of Sciences special GPU cluster program in the cooperation of ICCS (International Center for Computational Science). We reach about the half the peak Kepler K20 GPU performance for our phi-GPU code [2], in a real application scenario with individual hierarchically block time-steps with the high (4th, 6th and 8th) order Hermite integration schemes and a real core-halo density structure of the modeled stellar systems. The code and hardware are mainly used to simulate star clusters [23, 24] and galactic nuclei with supermassive black holes [20], in which correlations between distant particles cannot be neglected.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. On Computational CUDA Studies of Black Hole Shadows

    physics.gen-ph 2026-04 unverdicted novelty 4.0

    CUDA-based ray tracing shows black hole shadows and emission rates vary with global monopole, charge, and rotation parameters but are insensitive to the Euler-Heisenberg nonlinearity, yielding observational bounds on ...

  2. Constraining Black Hole Parameters in Non-Commutative Geometry using Machine Learning

    gr-qc 2026-05 unverdicted novelty 3.0

    Machine learning constrains non-commutative black hole parameters and reports consistency with Sgr A* Keck observations.