Skip to main content

Development Progress of SWLBM a Framework Based on Lattice Boltzmann Method for Fluid Dynamics Simulation

  • Conference paper
  • First Online:
Applied Reconfigurable Computing. Architectures, Tools, and Applications (ARC 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13569))

Included in the following conference series:

  • 438 Accesses

Abstract

SWLBM is a software framework based on Lattice Boltzmann Method (LBM) for Computational Fluid Dynamic (CFD) running on Sunway many-core processors. In this paper, we review the achievements of code developing in early stage and introduce the development progress recently of this software, including the development of parallel optimization for Sunway new-generation supercomputing system, functional extensions of the software like pre-process function for mesh generation from a geometry file with STL file and BMP file, Immersed boundary condition for moving subject simulation. Some applications with SWLBM will be introduced to show the advantage of this software over other CFD code in large-scale simulations. SWLBM is still under development, with the continuous improvement of functions, it will play a greater role in the field of fluid simulation.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 44.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 59.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. McNamara, G.R., Zanetti, G.: Use of the Boltzmann equation to simulate lattice-gas automata. Phys. Rev. Lett. 61(20), 2332 (1988)

    Article  Google Scholar 

  2. Qian Y., d’Humières D., Lallemand P.: Lattice BGK models for Navier–Stokes equation. EPL (Europhys. Lett.) 17(6), 479 (1992)

    Google Scholar 

  3. Lallemand, P., Luo, L.: Theory of the lattice Boltzmann method: dispersion, dissipation, isotropy, galilean invariance, and stability. Phys. Rev. E 61(6), 6546–6562 (2000)

    Article  MathSciNet  Google Scholar 

  4. Luo, L.: Unified theory of lattice Boltzmann models for nonidealgases. Phys. Rev. Lett. 81(8), 1618–1621 (1998)

    Article  Google Scholar 

  5. Pohl, T., et al.: Performance evaluation of parallel large-scale lattice boltzmann applications on three supercomputing architectures. In: SC’04. Washington, DC, USA. IEEE Computer Society, p. 21 (2004)

    Google Scholar 

  6. Williams, S., Carter, J., Oliker, L., Shalf, J., Yelick, K.: Lattice Boltzmann simulation optimization on leading multicore platforms. In: Parallel and Distributed Processing, IPDPS 2008, pp. 1–14

    Google Scholar 

  7. Godenschwager, et al.: November. a framework for hybrid parallel flow simulations with a trillion cells in complex geometries. In Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis, p. 35. ACM (2013)

    Google Scholar 

  8. Bauer, et al.: Massively parallel phase-field simulations for ternary eutectic directional solidification. In Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis. ACM (2015)

    Google Scholar 

  9. Rettinger, C., Godenschwager, C., Eibl, S., Preclik, T., Schruff, T., Frings, R., Rüde, U.: Fully resolved simulations of dune formation in riverbeds. In: Kunkel, J.M., Yokota, R., Balaji, P., Keyes, D. (eds.) ISC High Performance 2017. LNCS, vol. 10266, pp. 3–21. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-58667-0_1

    Chapter  Google Scholar 

  10. Smagorinsky, J.: General circulation experiments with the primitive equations. Mon. Wea. Rev. 91, 99–164 (1963)

    Article  Google Scholar 

  11. Chu, X., Liu, Z., Shi, S., Meng, H., Lv, X., Han, J.: Development progress on SWLBM CFD software on sunway architecture. In: The 10th National Conference on Fluid Mechanics, HangZhou China (2018)

    Google Scholar 

  12. Liu, Z.: SunwayLB: enabling extreme-scale lattice boltzmann method based computing fluid dynamics simulations on sunway taihulight. In: IEEE International Parallel and Distributed Processing Symposium (IPDPS) (2019)

    Google Scholar 

  13. Lv, X., Liu, Z., Chu, X., Shi, S., Meng, H., Huang, Z.: Extreme-scale simulation based LBM computing fluid dynamics simulations. Comput. Sci. 47(4), 13–17 (2020)

    Google Scholar 

  14. Li, F., Li, Z., Xu, J., Fan, H., Chu, X., Li, X.: Research on adaptation of CFD software based on many-core architecture of 100P domestic supercomputing system. Comput. Sci. 47(1), 24–30 (2020)

    Google Scholar 

  15. Amdahl, G.M.: AFIPS Conference Proceedings, vol. 30, pp. 483–485 (1967). https://doi.org/10.1145/1465482.1465560

  16. Gustafson, J.L.: Communications of the ACM 31(5), 532–533 (1988). https://doi.org/10.1145/42411.42415

  17. Kravchenko, A.G., Moin, P.: Numerical studies of flow over a circular cylinder at ReD = 3900. Phys. Fluids 12(2), 403–417 (2000)

    Article  MATH  Google Scholar 

  18. Franke, J., Frank, W.: Large eddy simulation of the flow past a circular cylinder at ReD =3900. J. Wind Eng. Ind. Aerodyn. 90(10), 1191–1206 (2002)

    Article  Google Scholar 

  19. Parnaudeau, P., Carlier, J., Heitz, D., et al.: Experimental and numerical studies of the flow over a circular cylinder at Reynolds number 3900. Phys. Fluids 20(8), 12–287 (2008)

    Article  MATH  Google Scholar 

  20. Cao, P., Chu, X., Wang, J., et al.: Simulation of channel flow with lattice boltzmann method by DNS and LES. Aerodyn. Res. Exp. 33(02), 98–104 (2021)

    Google Scholar 

  21. Moser, R.D., Kim, J., Mansour, N.N.: Direct numerical simulation of turbulent channel flow up to Re = 590. Phys. Fluids 11(4), 943–945 (1999)

    Article  MATH  Google Scholar 

  22. Ma, Z., He, J., et al.: BAGUALU: targeting brain scale pretrained models with over 37 million cores. In Proceedings of the 27th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming (PPoPP'22)

    Google Scholar 

  23. Xiaoxiao, Z., Zhang, W., Xuesen, C., et al.: An efficient algorithm for pre-processing of lattice Boltzmann method based on STL files. ACTA Aerodynamica Sinica 39(03), 44–50 (2021)

    Google Scholar 

  24. Peskin, C.S.: Numerical analysis of blood flow in the heart. J. Comp. Phys. 25, 220–252 (1977)

    Article  MathSciNet  MATH  Google Scholar 

  25. Peskin, C.S.: The immersed boundary method. Acta. Numer. 11, 479–517 (2002)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Chu Xuesen .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Xuesen, C., Xiang, H., Fang, L., Zhao, L., Guangwen, Y. (2022). Development Progress of SWLBM a Framework Based on Lattice Boltzmann Method for Fluid Dynamics Simulation. In: Gan, L., Wang, Y., Xue, W., Chau, T. (eds) Applied Reconfigurable Computing. Architectures, Tools, and Applications. ARC 2022. Lecture Notes in Computer Science, vol 13569. Springer, Cham. https://doi.org/10.1007/978-3-031-19983-7_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-19983-7_5

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-19982-0

  • Online ISBN: 978-3-031-19983-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics