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arXiv · 1409.1929

Adaptive Techniques for Clustered N-Body Cosmological Simulations

Harshitha Menon·Lukasz Wesolowski·Gengbin Zheng·Pritish Jetley·Laxmikant Kale·Thomas Quinn·Fabio Governato
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Abstract

ChaNGa is an N-body cosmology simulation application implemented using Charm++. In this paper, we present the parallel design of ChaNGa and address many challenges arising due to the high dynamic ranges of clustered datasets. We focus on optimizations based on adaptive techniques for scaling to more than 128K cores. We demonstrate strong scaling on up to 512K cores of Blue Waters evolving 12 and 24 billion particles. We also show strong scaling of highly clustered datasets on up to 128K cores.

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Harshitha Menon, Lukasz Wesolowski, Gengbin Zheng, Pritish Jetley, Laxmikant Kale, Thomas Quinn, Fabio Governato. 2014-09-05. Adaptive Techniques for Clustered N-Body Cosmological Simulations. https://arxiv.org/abs/1409.1929

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