Introduction
This chapter reviews the application of a biologically inspired heuristic technique - Cellular Automata (CA) - for developing high performance simulations of a well known complex system: the laser.
CA can be described as a class of mathematical systems. They were introduced several decades ago, and are well suited to model spatio-temporal phenomena. On the other hand, CA can be implemented very efficiently on parallel platforms, given both, their intrinsic parallel nature, with all the components working usually in a synchronized way, and the discreteness of the individual components using the same behavior rules. We therefore make use of this feature, and consider the problem of running Parallel CA simulations on non-dedicated clusters of workstations.We thus present results of laser dynamics simulations, traditionally modeled using differential equations.
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References
Einstein, A.: Zur quantenmechanik der strahlung. Physikalische Zeitschrift 18, 121–128 (1917)
Siegman, A.E.: Lasers. University Science Books (1986)
Guisado, J.L., Jiménez-Morales, F., Guerra, J.M.: Cellular automaton model for the simulation of laser dynamics. Physical Review E 67(6), 66708 (2003)
Ilachinski, A.: Cellular automata. A discrete Universe. World Scientific, Singapore (2001)
Sloot, P.M.A., Hoekstra, A.G.: Modeling Dynamic Systems with Cellular Automata, ch. 21, pp. 21–1+6. Chapman & Hall/CRC, Boca Raton (2007)
Chopard, B., Droz, M.: Cellular Automata Modeling of Physical Systems. Cambridge University Press, Cambridge (1998)
Guisado, J.L., Jiménez-Morales, F., Guerra, J.M.: Application of shannon’s entropy to classify emergent behaviors in a simulation of laser dynamics. Mathematical and Computer Modelling 42, 847–854 (2005)
Guisado, J.L., Jiménez-Morales, F., Guerra, J.M.: Computational simulation of laser dynamics as a cooperative phenomenon. Physica Scripta 118, 148–152 (2005)
Guisado, J.L., Jiménez-Morales, F., Fernández de Vega, F.: Cellular automata and cluster computing: An application to the simulation of laser dynamics. Advances in Complex Systems 10(Suppl.1), 167–190 (2007)
Guisado, J.L., Fernández de Vega, F., Jiménez-Morales, F., Iskra, K.: Parallel implementation of a cellular automaton model for the simulation of laser dynamics. In: Alexandrov, V.N., van Albada, G.D., Sloot, P.M.A., Dongarra, J. (eds.) ICCS 2006. LNCS, vol. 3993, pp. 281–288. Springer, Heidelberg (2006)
Guisado, J.L., Fernández de Vega, F., Iskra, K.: Performance analysis of a parallel discrete model for the simulation of laser dynamics. In: 2006 International Conference on Parallel Processing, Workshops, pp. 93–99. IEEE Computer Society, Los Alamitos (2006)
Guisado, J.L., Fernández de Vega, F., Jiménez-Morales, F., Iskra, K.A., Sloot, P.M.A.: Using cellular automata for parallel simulation of laser dynamics with dynamic load balancing. International Journal of High Performance Systems Architecture 1(4), 251–259 (2009)
Talia, D.: Cellular processing tools for high-performance simulation. IEEE Computer 33(9), 44–52 (2000)
Resnick, M.: Turtles, Termites, and Traffic Jams. MIT Press, Cambridge (1994)
Cannataro, M., Di Gregorio, S., Rongo, R., Spataro, W., Spezzano, G., Talia, D.: A parallel cellular automata environment on multicomputers for computational science. Parallel Computing 21(5), 803–823 (1995)
Spezzano, G., Talia, D., Di Gregorio, S., Rongo, R., Spataro, W.: A parallel cellular tool for interactive modeling and simulation. IEEE Computational Science & Engineering 3(3), 33–43 (1996)
Hutchinson, D., Kattner, L., Lanthier, M., Maheshwari, A., Nussbaum, D., Roytenberg, D., Sack, J.R.: Parallel neighbourhood modeling: research summary. In: Proceedings of the eighth annual ACM symposium on Parallel algorithms and architectures, pp. 204–207 (1996)
Carotenuto, L., Mele, F., Furnari, M., Napolitano, R.: PECANS: A parallel environment for cellular automata modeling. Complex Systems 10(1), 23–42 (1996)
Zeigler, B., Moon, Y., Kim, D., Ball, G.: The DEVS environment for high-performance modeling and simulation. IEEE Computational Science & Engineering 4(3), 61–71 (1997)
Schoneveld, A., de Ronde, J.F.: P-CAM: a framework for parallel complex systems simulations. Future Generation Computer Systems 16(2), 217–234 (1999)
Toffoli, T., Margolus, N.: Cellular automata machines: a new environment for modeling. MIT Press, Cambridge (1987)
Sloot, P.M.A., Kaandorp, J.A., Hoekstra, A.G., Overeinder, B.J.: Distributed simulation with cellular automata: architecture and applications. In: Bartosek, M., Tel, G., Pavelka, J. (eds.) SOFSEM 1999. LNCS, vol. 1725, pp. 203–248. Springer, Heidelberg (1999)
D’Ambrosio, D., Spataro, W.: Parallel evolutionary modeling of geological processes. Parallel Computing 33(3), 186–212 (2007)
Mazzariol, M., Gennart, B., Hersch, R.: Dynamic load balancing of parallel cellular automata. In: Proc. SPIE Conference on Parallel and Distributed Methods for Image Processing IV, San Diego, July 2000, vol. 4118, p. 2129. SPIE (2000)
Kohring, G.A.: Dynamic load balancing for parallelized particle simulations on MIMD computers. Parallel Computing 21, 683–693 (1995)
Cortés, A., Planas, M., Millán, J.L., Ripoll, A., Senar, M.A., Luque, E.: Applying load balancing in data parallel applications using DASUD. In: Dongarra, J., Laforenza, D., Orlando, S. (eds.) EuroPVM/MPI 2003. LNCS, vol. 2840, pp. 237–241. Springer, Heidelberg (2003)
Fabero, J.C., Martin, I., Bautista, A., Molina, S.: Dynamic load balancing in a heterogeneous environment under PVM. In: 4th Euromicro Workshop on Parallel and Distributed Processing (PDP 1996), pp. 414–419. IEEE Computer Society, Los Alamitos (1996)
Weimar, J.R.: Cellular automata for reaction-diffusion systems. Parallel Computing 23(11), 1699–1715 (1997)
Dick van Albada, G., Clinckmaillie, J., Emmen, A.H.L., Gehring, J., Heinz, O., van der Linden, F., Overeinder, B.J., Reinefeld, A., Sloot, P.M.A.: Dynamite - blasting obstacles to parallel cluster computing. In: Sloot, P.M.A., Hoekstra, A.G., Bubak, M., Hertzberger, B. (eds.) HPCN-Europe 1999. LNCS, vol. 1593, pp. 300–310. Springer, Heidelberg (1999)
Overeinder, B.J., Sloot, P.M.A., Heederik, R.N., Hertzberger, L.O.: A dynamic load balancing system for parallel cluster computing. Future Generation Computer Systems 12(1), 101–115 (1996)
Iskra, K., Hendrikse, Z.W., Dick van Albada, G., Overeinder, B.J., Sloot, P.M.A., Gehring, J.: Experiments with migration of message-passing tasks. In: Buyya, R., Baker, M. (eds.) GRID 2000. LNCS, vol. 1971, pp. 203–213. Springer, Heidelberg (2000)
Iskra, K., Hendrikse, Z.W., Dick van Albada, G., Overeinder, B.J., Sloot, P.M.A.: Dynamic migration of PVM tasks. In: ASCI 2000, Proceedings of the sixth annual conference of the Advanced School for Computing and Imaging, June 2000, pp. 206–212 (2000)
Folino, G., Spezzano, G.: An autonomic tool for building self-organizing grid-enabled applications. Future Generation Computer Systems 23(5), 671–679 (2007)
Vadhiyar, S.S., Dongarra, J.J.: Self adaptivity in grid computing. Concurrency Computation Practice and Experience 17(2-4), 235–257 (2005)
Foster, I.: Designing and building parallel programs. Addison-Wesley, Reading (1995)
Dongarra, J., Foster, I., Fox, G.C., Gropp, W., Kennedy, K., Torczon, L., White, A. (eds.): Sourcebook of parallel computing. Morgan Kaufmann, San Francisco (2003)
Sugerman, J., Venkitachalam, G., Lim, B.: Virtualizing i/o devices on vmware workstation’s hosted virtual machine monitor
Barham, P., Dragovic, B., Fraser, K., Hand, S., Harris, T., Ho, A., Neugebauer, R., Pratt, I., Warfield, A.: Xen and the art of virtualization. In: Proceedings of the nineteenth ACM symposium on Operating systems principles, pp. 164–177 (2003)
Watson, J.: Virtualbox: bits and bytes masquerading as machines. Linux J. 2008(166), 1 (2008)
Elnozahy, E., Alvisi, L., Wang, Y., Johnson, D.: A survey of rollback-recovery protocols in message-passing systems. ACM Computing Surveys (CSUR) 34(3), 375–408 (2002)
Robin, J., Irvine, C.: N.P.S.M.C.D.O.C. SCIENCE. Analysis of the Intel Pentium’s Ability to Support a Secure Virtual Machine Monitor, Defense Technical Information Center (2000)
Nieh, J., Leonard, O.C.: Examining VMware. j-DDJ 25(8), 70, 72–74, 76 (2000)
Chase, J.S., Irwin, D.E., Grit, L.E., Moore, J.D., Sprenkle, S.E.: Dynamic Virtual Clusters in a Grid Site Manager. In: HPDC 2003: Proceedings of the 12th IEEE International Symposium on High Performance Distributed Computing, p. 90 (2003)
Foster, I., Freeman, T., Keahy, K., Scheftner, D., Sotomayer, B., Zhang, X.: Virtual Clusters for Grid Communities. In: CCGRID 2006: Proceedings of the Sixth IEEE International Symposium on Cluster Computing and the Grid, pp. 513–520 (2006)
Emeneker, W., Stanzione, D.: Dynamic Virtual Clustering, 2007. In: IEEE International Conference on Cluster Computing, pp. 84–90 (2007)
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Guisado, J.L. et al. (2010). Laser Dynamics Modelling and Simulation: An Application of Dynamic Load Balancing of Parallel Cellular Automata. In: de Vega, F.F., Cantú-Paz, E. (eds) Parallel and Distributed Computational Intelligence. Studies in Computational Intelligence, vol 269. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10675-0_14
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