Abstract
Simulation of reaction-diffusion phenomena are usually done using cellular automata with asynchronous mode of operation, which is in accordance with the stochastic nature of such processes, though does not provide acceptable parallelization efficiency, when the model is implemented on a supercomputer. The contradiction is resolved by endowing the asynchronous mode with some synchronization under the condition that the result is not distorted. How much of synchronization is admissible is not known. Moreover, it is not known what is the impact of synchronization on the parallelization efficiency. In the paper an attempt is made to answer these questions basing on the analysis of parallel experimental simulations of typical subclasses of reaction diffusion processes on a supercomputer.
Supported by Presidium of Russian Academy of Sciences, Basic Research Program N 15-9 (2015).
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Hoekstra, A.G., Kroc, J.K., Sloot, P.M.A. (eds.): Simulating Complex Systems by Cellular Automata. Springer, Heidelberg (2010)
Desai, R.C., Kapral, R.: Dynamics of Self-organized and Self-assembled Structures. Cambridge University Press, Cambridge (2009)
Echieverra, C., Kapral, R.: Molecular crowding and protein enzymatic dynamics. Phys. Chem. 14, 6755–6763 (2012)
Bandini, S., Bonomi, A., Vizzari, G.: What do we mean by asynchronous CA? a reflection on types and effects of asynchronicity. In: Bandini, S., Manzoni, S., Umeo, H., Vizzari, G. (eds.) ACRI 2010. LNCS, vol. 6350, pp. 385–394. Springer, Heidelberg (2010)
Bouré, O., Fatès, N., Chevrier, V.: First steps on asynchronous lattice-gas models with an application to a swarming rule. In: Sirakoulis, G.C., Bandini, S. (eds.) ACRI 2012. LNCS, vol. 7495, pp. 633–642. Springer, Heidelberg (2012)
Kireeva, A.: Parallel implementation of totalistic cellular automata model of stable patterns formation. In: Malyshkin, V. (ed.) PaCT 2013. LNCS, vol. 7979, pp. 330–343. Springer, Heidelberg (2013)
Matveev, A.V., Latkin, E.I., Elokhin, V.I., Gorodetskii, V.V.: Turbulent and stripes wave patterns caused by limited CO\(_{ads}\) diffusion during CO oxidation over Pd(110) surface: kinetic Monte Carlo studies. Chem. Eng. J. 107, 181–189 (2005)
Nurminen, L., Kuonen, A., Kaski, K.: Kinetic Monte-Carlo simulation on patterned substrates. Phys. Rev. B 63, 03540:17–03540:7 (2000)
Chatterjee, A., Vlaches, D.: G.: An overview of spatial microscopic and accelerated kinetic Monte-Carlo methods. J. Comput. Aided Mater. Des. 14, 253–308 (2007)
Bandman, O.: Parallel composition of asynchronous cellular automata simulating reaction diffusion processes. In: Bandini, S., Manzoni, S., Umeo, H., Vizzari, G. (eds.) ACRI 2010. LNCS, vol. 6350, pp. 395–398. Springer, Heidelberg (2010)
Kalgin, K.: Comparative study of parallel algorithms for asynchronous cellular automata simulation on different computer architectures. In: Bandini, S., Manzoni, S., Umeo, H., Vizzari, G. (eds.) ACRI 2010. LNCS, vol. 6350, pp. 399–408. Springer, Heidelberg (2010)
Bandman, O.: Implementation of large-scale cellular automata models on multi-core computers and clusters. In: 2013 International Conference on IEEE Conference Publications High Performance Computing and Simulation (HPCS), pp. 304–310 (2013)
Bandman, O.: Parallel simulation of asynchronous cellular automata evolution. In: El Yacoubi, S., Chopard, B., Bandini, S. (eds.) ACRI 2006. LNCS, vol. 4173, pp. 41–47. Springer, Heidelberg (2006)
Bandman, O., Kireeva, A.: Stochastic cellular automata simulation of oscillations and autowaves in reaction-diffusion systems. Numerical Analysis and Applications, vol. 2 (2015)
Bandman, O.: Functioning modes of asynchronous cellular automata simulating nonlinear spatial dynamics. Appl. Discrete Math. 1, 110–124 (2015). (in Russian)
Toffolli, T., Margolus, N.: Cellular Automata Machines: A New Environment for Modeling. MIT Press, USA (1987)
Bandman, O.: Cellular automata diffusion models for multicomputer implementation. Bull. Novosibirsk Comput. Cent. Ser. Comput. Sci. 36, 21–31 (2014)
Kolmogorov, A.N., Petrovski, I.G., Piskunov, I.S.: Investigation of the equation of diffusion, combined with the increase of substance and its application to a biological problem. Bull. Moscow State Univ. A Issue 6, 1–25 (1937). (in Russian)
Fisher, R.A.: The genetical Theory of Natural Selection. Oxford University Press, New York (1930)
Szakály, T., Lagzi, I., Izsák, F., Roszol, L., Volford, A.: Stochastic cellular automata modeling excitable systems. Central Eur. J. Phys. 5(4), 471–486 (2007)
van Saarloos, W.: Front propagation into unstable states. Phys. Rep. 386, 209–222 (2003)
Witten Jr., T.A., Sander, I.M.: Diffusion-limited aggregation, a kinetic critical phenomenon. Phys. Rev. Lett. 47(19), 1400–1403 (1981)
Ackland, G.J., Tweedie, E.S.: Microscopic model of diffusion limited aggregation and electro deposition in the presence of leveling molecules. Phys. Rev. E 73, 011606 (2006)
Bogoyavlenskiy, A., Chernova, N.A.: Diffusion-limited aggregation: a relationship between surface thermodynamics and crystal morphology. Phys. Rev. E. N 2, 1629–1633 (2000)
Batty, M., Longley, P.: Urban growth and form: scaling, fractal geometry, and diffusion-limited aggregation. Environ. Plann. A 21, 1447–1472 (1989)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Bandman, O. (2015). Contradiction Between Parallelization Efficiency and Stochasticity in Cellular Automata Models of Reaction-Diffusion Phenomena. In: Malyshkin, V. (eds) Parallel Computing Technologies. PaCT 2015. Lecture Notes in Computer Science(), vol 9251. Springer, Cham. https://doi.org/10.1007/978-3-319-21909-7_14
Download citation
DOI: https://doi.org/10.1007/978-3-319-21909-7_14
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-21908-0
Online ISBN: 978-3-319-21909-7
eBook Packages: Computer ScienceComputer Science (R0)