Abstract
In this paper, we present the results of numerical simulations of hydrodynamic turbulence with self-gravity, employing the latest Intel Xeon Phi accelerators with KNL architecture. A new vectorized numerical method with a high order of accuracy on a local stencil is described in details. We outline the main features of the program implementation of the method for massively parallel architectures and study the code parallel implementation. We achieved a performance of 173 gigaFLOPS and an acceleration factor of 48 using a single Intel Xeon Phi KNL. Using 16 accelerators, we were able to achieve a scalability of 97%.
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The research was supported by the Russian Science Foundation (project 18-11-00044).
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Kulikov, I. et al. (2019). Numerical Modeling of Hydrodynamic Turbulence with Self-gravity on Intel Xeon Phi KNL. In: Sokolinsky, L., Zymbler, M. (eds) Parallel Computational Technologies. PCT 2019. Communications in Computer and Information Science, vol 1063. Springer, Cham. https://doi.org/10.1007/978-3-030-28163-2_22
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DOI: https://doi.org/10.1007/978-3-030-28163-2_22
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