StochKit-FF: Efficient Systems Biology on Multicore Architectures

TL;DR

StochKit-FF is a parallelized toolkit for stochastic biological simulations that leverages multicore architectures and a novel selective memory concept to improve efficiency, demonstrated on HIV infection models.

Contribution

It introduces StochKit-FF, a new parallel version of StochKit utilizing FastFlow and selective memory for faster stochastic simulations.

Findings

Efficient simulation of HIV infection dynamics.

Improved extraction of statistical information from simulations.

Potential for more structured data analysis.

Abstract

The stochastic modelling of biological systems is an informative, and in some cases, very adequate technique, which may however result in being 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 exploits 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.