Using cellular automata for parallel simulation of laser dynamics with dynamic load balancing
We present an analysis of the feasibility of executing a parallel bioinspired model of laser dynamics, based on cellular automata (CA), on the usual target platform of this kind of applications: a heterogeneous non-dedicated cluster. As this model employs a synchronous cellular automaton, using the...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2008 |
| País: | España |
| Institución: | Universidad de Sevilla (US) |
| Repositorio: | idUS. Depósito de Investigación de la Universidad de Sevilla |
| OAI Identifier: | oai:idus.us.es:11441/162277 |
| Acceso en línea: | https://hdl.handle.net/11441/162277 https://doi.org/10.1504/IJHPSA.2008.024209 |
| Access Level: | acceso abierto |
| Palabra clave: | Cluster computing Simulation Parallel bioinspired model Laser dynamics Dynamic Load balancing Performance evaluation |
| Sumario: | We present an analysis of the feasibility of executing a parallel bioinspired model of laser dynamics, based on cellular automata (CA), on the usual target platform of this kind of applications: a heterogeneous non-dedicated cluster. As this model employs a synchronous cellular automaton, using the SPMD (Single Program, Multiple Data) paradigm, it is not clear in advance if an appropriate efficiency can be obtained on this kind of platform. We have evaluated its performance including artificial load to simulate other tasks or jobs submitted by other users. A dynamic load balancing strategy with two main differences from most previous implementations of CA based models has been used. First, it is possible to migrate load to cluster nodes initially not belonging to the pool. Second, a modular approach is taken in which the model is executed on top of a dynamic load balancing tool—the Dynamite system— gaining flexibility. Very satisfactory results have been obtained, with performance increases from 60% to 80% |
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