Utilizing model characteristics to obtain efficient parallelization in the context of agent based epidemiological models

There exist many problem agnostic frameworks and algorithms for parallel simulation. However, creating parallel simulation models that take advantage of characteristics specific to either the problem domain or a specific model can create significant performance benefits. This article provides an overview of general frameworks and algorithms for paralleling simulation execution, and also demonstrates two ways in which assumptions underlying the implementations of epidemiological models can be used to enable such parallelization in an efficient manner. These examples are based on planning and developing agent-based models activities carried out as part of the NIH's MIDAS (Models of Infectious Disease Agent Study) family of grants. © 2007 IEEE.