Geodesic
Methods for improving and evaluating the performance of unstructured CFD-algorithms
Matematičeskoe modelirovanie, Tome 35 (2023) no. 2, pp. 30-42.

Voir la notice de l'article provenant de la source Math-Net.Ru

The problem of improving the performance of unstructured CFD-algorithms on multicore processors is discussed. The details of the application of algorithms for reducing the adjacency matrix bandwidth and the implementation of the calculation scheme with asynchronous time integration are considered. The possibility of using a set-associative cache simulator for a comparative evaluation of data ordering methods is shown. A procedure for testing the speed of a finite-volume algorithm for modeling the Navier-Stokes equations is described using the example of calculating the problem of supersonic flow around a sphere on three mixed meshes containing from 270 thousand to 17 million cells.
Keywords: computational fluid dynamics, unstructured mixed mesh, data access optimization. 
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S. A. Sukov. Methods for improving and evaluating the performance of unstructured CFD-algorithms. Matematičeskoe modelirovanie, Tome 35 (2023) no. 2, pp. 30-42. http://geodesic.mathdoc.fr/item/MM_2023_35_2_a2/

[1] A. Gorobets, P. Bakhvalov, “Heterogeneous CPU+GPU parallelization for high-accuracy scale-resolving simulations of compressible turbulent flows on hybrid supercomputers”, Computer Physics Communications, 271 (2022), 108231 | DOI | MR

[2] V. E. Borisov, A. A. Davydov, I. Yu. Kudryashov, A. E. Lutsky, I. S. Men'shov, “Parallel Implementation of an Implicit Scheme Based on the LU-SGS Method for 3D Turbulent Flows”, Mathematical Models and Computer Simulations, 7:3 (2015), 222–232 | DOI | MR

[3] M. M. Krasnov, P. A. Kuchugov, M. E. Ladonkina et al, “Discontinuous Galerkin method on three-dimensional tetrahedral grids: Using the operator programming method”, MM CS, 9:5 (2017), 529–543 | DOI | MR

[4] A. Gorobets, S. Soukov, P. Bogdanov, “Multilevel parallelization for simulating turbulent flows on most kinds of hybrid supercomputers”, Computers and Fluids, 173 (2018), 171–177 | DOI | MR

[5] P.D Lax, “Weak Solutions of Nonlinear Hyperbolic Equations and their Numerical Computation”, Comm. Pure and Applied Mathematics, 7 (1954), 159–193 | DOI | MR

[6] A. Jameson, “Positive Schemes and Shock Modelling for Compressible Flow”, Int. J. Numerical Methods in Fluids, 20 (1995), 743–776 | DOI | MR

[7] E. Cuthill, J. McKee, “Reducing the bandwidth of sparse symmetric matrices”, Proc. ACM Nat. Conf., 1969, 157–172

[8] L. P. King, “An automatic reordering scheme for simultaneous equations derived from network problems”, Intern. J. for Numerical Methods in Engineering, 2 (1970), 523–533 | DOI

[9] A. L.G. A. Coutinho, M. A.D. Martins, R. M. Sydenstricker, R. N. Elias, “Performance comparison of data-reordering algorithms for sparse matrix-vector multiplication in edge-based unstructured grid computations”, Int. J. Numer. Meth. Eng., 66 (2006), 431–460 | DOI

[10] V. D. Levchenko, “Asinkhronnye parallelnye algoritmy kak sposob dostizheniia effektivnosti vychislenii”, Informatsionnye tekhnologii i vychislitelnye sistemy, 1 (2005), 68

[11] A. Iu. Perepelkina, V. D. Levchenko, I. A. Goriachev, “Trekhmernyi kineticheskii kod CFHall dlia modelirovaniia zamagnichennoi plazmy”, Matem. model., 25:11 (2013), 98–110 | MR

[12] S. Soukov, “Parallel CFD-Algorithm on Unstructured Adaptive Meshes”, Math. Models Computer Simul., 14:1 (2022), 19–27 | DOI | MR

[13] GAMBIT, http://www.ansys.com

[14] S. W. Sloan, “A Fortran program for profile and wavefront reduction”, International Journal for Numerical Methods in Engineering, 28 (1989), 2651–2679 | DOI