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Lookup NU author(s): Dr Colin GillespieORCiD
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In recent years, computer simulations have become increasingly useful when trying to understand the complex dynamics of biochemical networks, particularly in stochastic systems. In such situations stochastic simulation is vital in gaining an understanding of the inherent stochasticity present, as these models are rarely analytically tractable. However, a stochastic approach can be computationally prohibitive for many models. A number of approximations have been proposed that aim to speed up stochastic simulations. However, the majority of these approaches are fundamentally serial in terms of central processing unit (CPU) usage. In this paper, we propose a novel simulation algorithm that utilises the potential of multi-core machines. This algorithm partitions the model into smaller sub-models. These sub-models are then simulated, in parallel, on separate CPUs. We demonstrate that this method is accurate and can speed-up the simulation by a factor proportional to the number of processors available. (C) 2012 American Institute of Physics. [doi: 10.1063/1.3670416]
Author(s): Gillespie CS
Publication type: Article
Publication status: Published
Journal: Journal of Chemical Physics
Year: 2012
Volume: 136
Issue: 1
Print publication date: 03/01/2012
ISSN (print): 0021-9606
ISSN (electronic): 1089-7690
Publisher: American Institute of Physics
URL: http://dx.doi.org/10.1063/1.3670416
DOI: 10.1063/1.3670416
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