The stochastic modelling of biological systems is informative and often very adequate, but it may easily be more expensive than other modelling approaches, such as differential equations. We present StochKit-FF, a parallel version of StochKit, a reference toolkit for stochastic simulations. StochKit-FF is based on the FastFlow programming toolkit for multicores and on the novel concept of selective memory. We experiment StochKit-FF on a model of HIV infection dynamics, with the aim of extracting information from efficiently run experiments, here in terms of average and variance and, on a longer term, of more structured data.
Titolo: | StochKit-FF: Efficient Systems Biology on Multicore Architectures |
Autori interni: | |
Anno del prodotto: | 2011 |
Abstract: | The stochastic modelling of biological systems is informative and often very adequate, but it may easily be more expensive than other modelling approaches, such as differential equations. We present StochKit-FF, a parallel version of StochKit, a reference toolkit for stochastic simulations. StochKit-FF is based on the FastFlow programming toolkit for multicores and on the novel concept of selective memory. We experiment StochKit-FF on a model of HIV infection dynamics, with the aim of extracting information from efficiently run experiments, here in terms of average and variance and, on a longer term, of more structured data. |
Handle: | http://hdl.handle.net/11568/568468 |
ISBN: | 9783642218774 9783642218781 |
Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |