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Data Parallelization Algorithms for the Direct Simulation Monte Carlo Method for Rarefied Gas Flows on the Basis of OpenMP Technology

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Abstract

A data parallelization algorithm for the direct simulation Monte Carlo method for rarefied gas flows is considered. The scaling of performance of the main algorithm procedures are analyzed. Satisfactory performance scaling of the parallel particle indexing procedure is shown, and an algorithm for speeding up the operation of this procedure is proposed. Using examples of solving problems of free flow and flow around a cone for a 28-core node with shared memory, an acceptable speedup of the entire algorithm was obtained. The efficiency of the data parallelization algorithm and the computational domain decomposition algorithm for free flow is compared. Using the developed parallel code, a study of the supersonic rarefied flow around a cone is carried out.

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Funding

This work was supported by the Russian Science Foundation, project no. 22-11-00078. The computing resources were provided by the Supercomputer Center “Polytechnic.”

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Authors and Affiliations

  1. Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, 119333, Moscow, Russia

    N. Yu. Bykov & S. A. Fyodorov

  2. Peter the Great St. Petersburg Polytechnic University, 195251, St. Petersburg, Russia

    N. Yu. Bykov & S. A. Fyodorov

Authors
  1. N. Yu. Bykov
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  2. S. A. Fyodorov
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Correspondence to N. Yu. Bykov.

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Dedicated to Professor E.M. Shakhov on the occasion of his 90th birthday

Translated by A. Klimontovich

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Bykov, N.Y., Fyodorov, S.A. Data Parallelization Algorithms for the Direct Simulation Monte Carlo Method for Rarefied Gas Flows on the Basis of OpenMP Technology. Comput. Math. and Math. Phys. 63, 2275–2296 (2023). https://doi.org/10.1134/S0965542523120072

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