Advanced Vectorization of PPML Method for Intel® Xeon® Scalable Processors

  • Igor ChernykhEmail author
  • Igor Kulikov
  • Boris Glinsky
  • Vitaly Vshivkov
  • Lyudmila Vshivkova
  • Vladimir Prigarin
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 965)


Piecewise Parabolic Method on a Local Stencil is very useful for numerical simulation of fluid dynamics, astrophysics. The main idea of the PPML method is the use of a piecewise parabolic numerical solution on the previous time step for computing the Riemann problem solving partial differential equations system (PDE). In this paper, we present the new version of PDE solver which is based on the PPML method optimized for Intel Xeon Scalable processor family. The results of performance comparison between different types of AVX-512 compatible Intel Xeon Scalable processors are presented. Special attention is paid to comparing the performance of Intel Xeon Phi (KNL) and Intel Xeon Scalable processors.


Massively parallel supercomputers Astrophysics Code vectorization 



This work was partially supported by RFBR grants 18-07-00757, 18-01-00166 and 16-07-00434. Methodical work was partially supported by the Grant of the Russian Science Foundation grant 16-11-10028.


  1. 1.
  2. 2.
  3. 3.
    Vshivkov, V.A., Lazareva, G.G., Snytnikov, A.V., Kulikov, I.M., Tutukov, A.V.: Hydrodynamical code for numerical simulation of the gas components of colliding galaxies. Astrophys. J. Suppl. Ser. 194(47), 1–12 (2011)Google Scholar
  4. 4.
    Bergin, E.A., Hartmann, L.W., Raymond, J.C., Ballesteros-Paredes, J.: Molecular cloud formation behind shock waves. Astrophys. J. 612, 921–939 (2004)CrossRefGoogle Scholar
  5. 5.
    Khoperskov, S.A., Vasiliev, E.O., Sobolev, A.M., Khoperskov, A.V.: The simulation of molecular clouds formation in the Milky Way. Mon. Not. R. Astron. Soc. 428(3), 2311–2320 (2013)CrossRefGoogle Scholar
  6. 6.
    Glover, S., Mac Low, M.-M.: Simulating the formation of molecular clouds. I. Slow formation by gravitational collapse from static initial conditions. Astrophys. J. Suppl. Ser. 169, 239–268 (2006)CrossRefGoogle Scholar
  7. 7.
    Chernykh, I., Stoyanovskaya, O., Zasypkina, O.: ChemPAK software package as an environment for kinetics scheme evaluation. Chem. Prod. Process Model. 4(4) (2009)Google Scholar
  8. 8.
    Snytnikov, V.N., Mischenko, T.I., Snytnikov, V., Chernykh, I.G.: Physicochemical processes in a flow reactor using laser radiation energy for heating reactants. Chem. Eng. Res. Des. 90(11), 1918–1922 (2012)CrossRefGoogle Scholar
  9. 9.
    Godunov, S.K., Kulikov, I.M.: Computation of discontinuous solutions of fluid dynamics equations with entropy nondecrease guarantee. Comput. Math. Math. Phys. 54, 1012–1024 (2014)MathSciNetCrossRefGoogle Scholar
  10. 10.
    Kulikov, I., Vorobyov, E.: Using the PPML approach for constructing a low-dissipation, operator-splitting scheme for numerical simulations of hydrodynamic flows. J. Comput. Phys. 317, 316–346 (2016)MathSciNetCrossRefGoogle Scholar
  11. 11.
  12. 12.
  13. 13.
    Glinskiy, B., Kulikov, I., Chernykh, I.: Improving the performance of an AstroPhi code for massively parallel supercomputers using roofline analysis. Commun. Comput. Inf. Sci. 793, 400–406 (2017)Google Scholar
  14. 14.
    Siberian Supercomputer Center ICMMG SB RAS.

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Igor Chernykh
    • 1
    Email author
  • Igor Kulikov
    • 1
  • Boris Glinsky
    • 1
  • Vitaly Vshivkov
    • 1
  • Lyudmila Vshivkova
    • 1
  • Vladimir Prigarin
    • 2
  1. 1.Institute of Computational Mathematics and Mathematical Geophysics SB RASNovosibirskRussia
  2. 2.Novosibirsk State Technical UniversityNovosibirskRussia

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