Parallel Performance Analysis of Bacterial Biofilm Simulation Models

  • M. V. Sheraton
  • Peter M. A. Sloot
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10860)


Modelling and simulation of bacterial biofilms is a computationally expensive process necessitating use of parallel computing. Fluid dynamics and advection-consumption models can be decoupled and solved to handle the fluid-solute-bacterial interactions. Data exchange between the two processes add up to the communication overheads. The heterogenous distribution of bacteria within the simulation domain further leads to non-uniform load distribution in the parallel system. We study the effect of load imbalance and communication overheads on the overall performance of simulation at different stages of biofilm growth. We develop a model to optimize the parallelization procedure for computing the growth dynamics of bacterial biofilms.


Load imbalance Communication overhead Biofilm 



P.S. acknowledges the Russian Science Foundation for support under RSCF #14-21-00137.


  1. 1.
    Dhatt, G., Lefrançois, E., Touzot, G.: Finite Element Method. Wiley, Hoboken (2012)CrossRefGoogle Scholar
  2. 2.
    Chen, S., Doolen, G.D.: Lattice Boltzmann method for fluid flows. Ann. Rev. Fluid Mech. 30, 329–364 (1998)MathSciNetCrossRefGoogle Scholar
  3. 3.
    Versteeg, H.K., Malalasekera, W.: An Introduction to Computational Fluid Dynamics: The Finite Method. Pearson Education, New York City (2007)Google Scholar
  4. 4.
    Zhang, L., Wang, Z., Sagotsky, J.A., Deisboeck, T.S.: Multiscale agent-based cancer modeling. J. Math. Biol. 58, 545–559 (2009)MathSciNetCrossRefGoogle Scholar
  5. 5.
    Fox, G.C., Johnson, M.A., Lyzenga, G.A., Otto, S.W., Salmon, J.K., Walker, D.W.: Solving Problems on Concurrent Processors: General Techniques and Regular Problems, vol. 1. Prentice-Hall, Inc., Upper Saddle River (1988)Google Scholar
  6. 6.
    Fozard, J.A., Lees, M., King, J.R., Logan, B.S.: Inhibition of quorum sensing in a computational biofilm simulation. Biosystems 109, 105–114 (2012)CrossRefGoogle Scholar
  7. 7.
    Morgenroth, E., Wilderer, P.A.: Influence of detachment mechanisms on competition in biofilms. Water Res. 34, 417–426 (2000)CrossRefGoogle Scholar
  8. 8.
    Picioreanu, C., Van Loosdrecht, M.C., Heijnen, J.J.: Two-dimensional model of biofilm detachment caused by internal stress from liquid flow. Biotech. Bioeng. 72, 205–218 (2001)CrossRefGoogle Scholar
  9. 9.
    Weitz, J.S., Hartman, H., Levin, S.A.: Coevolutionary arms races between bacteria and bacteriophage. Proc. Natl. Acad. Sci. U.S.A. 102, 9535–9540 (2005)CrossRefGoogle Scholar
  10. 10.
    Picioreanu, C., Vrouwenvelder, J., Van Loosdrecht, M.: Three-dimensional modeling of biofouling and fluid dynamics in feed spacer channels of membrane devices. J. Membr. Sci. 345, 340–354 (2009)CrossRefGoogle Scholar
  11. 11.
    Fagerlind, M.G., Webb, J.S., Barraud, N., McDougald, D., Jansson, A., Nilsson, P., Harlén, M., Kjelleberg, S., Rice, S.A.: Dynamic modelling of cell death during biofilm development. J. Theor. Biol. 295, 23–36 (2012)MathSciNetCrossRefGoogle Scholar
  12. 12.
    Popławski, N.J., Shirinifard, A., Swat, M., Glazier, J.A.: Simulation of single-species bacterial-biofilm growth using the Glazier-Graner-Hogeweg model and the CompuCell 3D modeling environment. Math. Biosci. Eng.: MBE 5, 355 (2008)MathSciNetCrossRefGoogle Scholar
  13. 13.
    Han, K., Levenspiel, O.: Extended monod kinetics for substrate, product, and cell inhibition. Biotech. Bioeng. 32, 430–447 (1988)CrossRefGoogle Scholar
  14. 14.
    Beyenal, H., Chen, S.N., Lewandowski, Z.: The double substrate growth kinetics of pseudomonas aeruginosa. Enzyme Microb. Technol. 32, 92–98 (2003)CrossRefGoogle Scholar
  15. 15.
    Sternberg, C., Tolker-Nielsen, T.: Growing and analyzing biofilms in flow cells. Curr. Protoc. Microbiol. (1), 1B.2.1–1B.2.15 (2006)Google Scholar
  16. 16.
    Alowayyed, S., Závodszky, G., Azizi, V., Hoekstra, A.: Load balancing of parallel cell-based blood flow simulations. J. Comput. Sci. 24, 1–7 (2018)CrossRefGoogle Scholar
  17. 17.
    Cytowski, M., Szymanska, Z.: Large-scale parallel simulations of 3d cell colony dynamics. Comput. Sci. Eng. 16, 86–95 (2014)CrossRefGoogle Scholar
  18. 18.
    Logg, A., Mardal, K.-A., Wells, G.: Automated Solution of Differential Equations by The Finite Element Method: The FEniCS Book. Springer, Heidelberg (2012). Scholar
  19. 19.
    Alnæs, M., Blechta, J., Hake, J., Johansson, A., Kehlet, B., Logg, A., Richardson, C., Ring, J., Rognes, M.E., Wells, G.N.: The FEniCS project version 1.5. Arch. Numer. Softw. 3, 9–23 (2015)Google Scholar
  20. 20.
    Guermond, J.-L., Minev, P., Shen, J.: An overview of projection methods for incompressible flows. Comput. Methods Appl. Mech. Eng. 195, 6011–6045 (2006)MathSciNetCrossRefGoogle Scholar
  21. 21.
    Geuzaine, C., Remacle, J.F.: Gmsh: A 3-D finite element mesh generator with built-in pre-and post-processing facilities. Int. Journal Numer. Methods Eng. 79, 1309–1331 (2009)MathSciNetCrossRefGoogle Scholar
  22. 22.
    Guyer, J.E., Wheeler, D., Warren, J.A.: FiPy: partial differential equations with python. Comput. Sci. Eng. 11, 6–15 (2009)CrossRefGoogle Scholar
  23. 23.
    Heroux, M.A., Bartlett, R.A., Howle, V.E., Hoekstra, R.J., Hu, J.J., Kolda, T.G., Lehoucq, R.B., Long, K.R., Pawlowski, R.P., Phipps, E.T.: An overview of the trilinos project. ACM Trans. Math. Softw. (TOMS) 31, 397–423 (2005)MathSciNetCrossRefGoogle Scholar
  24. 24.
    Picioreanu, C., Kreft, J.-U., Klausen, M., Haagensen, J.A.J., Tolker-Nielsen, T., Molin, S.: Microbial motility involvement in biofilm structure formation–a 3D modelling study. Water Sci. Technol. 55, 337–343 (2007)CrossRefGoogle Scholar
  25. 25.
    Axner, L., Bernsdorf, J., Zeiser, T., Lammers, P., Linxweiler, J., Hoekstra, A.G.: Performance evaluation of a parallel sparse lattice Boltzmann solver. J. Comput. Phys. 227, 4895–4911 (2008)MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Interdisciplinary Graduate SchoolHealthTech NTU, Nanyang Technological UniversitySingaporeSingapore
  2. 2.Complexity InstituteNanyang Technological UniversitySingaporeSingapore
  3. 3.Institute for Advanced StudiesUniversity of AmsterdamAmsterdamNetherlands
  4. 4.National Research University ITMOSt. PetersburgRussia

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