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Acceleration of NOISEtte Code for Scale-Resolving Supercomputer Simulations of Turbulent Flows

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Abstract

The present work is devoted to accelerating the NOISEtte code and lowering its memory consumption. This code for scale-resolving supercomputer simulations of compressible turbulent flows is based on higher-accuracy methods for unstructured mixed-element meshes and hierarchical MPI \(+\) OpenMP parallelization for cluster systems with manycore processors. We demonstrate modifications of the underlying numerical method and its parallel implementation, which consist, in particular, in using a simplified approximation method for viscous fluxes and mixed floating-point precision. The modified version has been tested on several representative cases. The performance measurements and validation results are presented.

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ACKNOWLEDGMENTS

The research is carried out using the equipment of the shared research facilities of HPC computing resources at Lomonosov Moscow State University [35] supercomputer simulations), and using the equipment of the collective use center of the Keldysh Institute of Applied Mathematics (performance tests). The authors thankfully acknowledge these institutions.

Funding

This work has been funded by the Russian Science Foundation, project 19-11-00299.

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Authors and Affiliations

  1. Keldysh Institute of Applied Mathematics of Russian Academy of Sciences, 125047, Moscow, Russia

    A. V. Gorobets, P. A. Bakhvalov, A. P. Duben & P. V. Rodionov

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  1. A. V. Gorobets
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  2. P. A. Bakhvalov
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  3. A. P. Duben
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  4. P. V. Rodionov
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Corresponding authors

Correspondence to A. V. Gorobets, P. A. Bakhvalov, A. P. Duben or P. V. Rodionov.

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(Submitted by E. E. Tyrtyshnikov)

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Gorobets, A.V., Bakhvalov, P.A., Duben, A.P. et al. Acceleration of NOISEtte Code for Scale-Resolving Supercomputer Simulations of Turbulent Flows. Lobachevskii J Math 41, 1463–1474 (2020). https://doi.org/10.1134/S1995080220080077

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