StochKit-FF: Efficient systems biology on multicore architectures

Citation

Aldinucci M, Bracciali A, Lio P, Sorathiya A & Torquati M (2011) StochKit-FF: Efficient systems biology on multicore architectures. In: Guarracino M, Vivien F, Träff J, Cannatoro M, Danelutto M, Hast A, Perla F, Knüpfer A, Martino B & Alexander M (eds.) Euro-Par 2010 Parallel Processing Workshops. Lecture Notes in Computer Science, 6586. Berlin, Heidelberg: Springer, pp. 167-175. http://www.scopus.com/inward/record.url?partnerID=yv4JPVwI&eid=2-s2.0-80051706079&md5=286ea3e23e0a0be6103ad85e9652c57e

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.

Keywords
Stochastic biological models; simulation; multicore