Exploring the performance of spatial stochastic simulation algorithms
- Institute of Computer Science, University of Rostock, Joachim-Jungius-Str. 10, 18059 Rostock (Germany)
Since the publication of Gillespie's direct method, diverse methods have been developed to improve the performance of stochastic simulation methods and to enter the spatial realm. In this paper we discuss a spatial {tau}-leaping variant (S{tau}) that extends the basic leap method. S{tau} takes reaction and both outgoing and incoming diffusion events into account when calculating a leap candidate. A performance analysis shall reveal details on the achieved success in balancing speed and accuracy in comparison to other methods. However, performance analysis of spatial stochastic algorithms requires significant effort - it is crucial to choose suitable (benchmark) models and to carefully define model and simulation setups that take problem and simulation design spaces into account.
- OSTI ID:
- 21499789
- Journal Information:
- Journal of Computational Physics, Journal Name: Journal of Computational Physics Journal Issue: 7 Vol. 230; ISSN JCTPAH; ISSN 0021-9991
- Country of Publication:
- United States
- Language:
- English
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