Abstract

Cellular automata (CA) are discrete dynamical mathematical systems that have been used for modeling many physical and engineering systems. Usually they are used as an alternative to more complex models based on partial differential equations. CA models can be implemented efficiently in parallel hardware due to the properties of locality, uniformity, and spatial regularity of the rules that govern their behavior. At the same time, CA simulations make intensive use of memory and processing time. For a widespread use of these models, implementations able to run in short periods of time without requiring specialized hardware are needed. This work presents a generic library able to simulate efficiently CA models, using the multispin coding technique and parallel processing on a network of conventional personal computers. Results of three different models tested show that it is possible to obtain a linear speedup. The observed speedup improves as the domain size increases or the simulated models become more complex, as in the case of a heterogeneous biofilm model used for designing wastewater treatment systems. © 2008 ASCE.