H.A. James, C.J. Scogings, and K.A. Hawick (New Zealand)
parallel update; concurrency; artificial life; simulation.
Update methods are an important aspect of the burgeoning Artificial Life research area. Artificial Life models, like the Predator-Prey model, are able to operate quite efficiently when implemented in a sequential manner only while pop ulation numbers are low to moderate. We find that for large populations sequential implementations are too slow to ex tract meaningful measurement statistics. In this paper we discuss the parallelisation of sequential update methods for use in Artificial Life systems. We also discuss the rami fications that parallel update algorithms introduce to data dependencies and also the meaning of correctness in paral lel models.
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