Abstract
This work concerns a general technique to enrich parallel version of stochastic simulators for biological systems with tools for on-line statistical analysis of the results. In particular, within the FastFlow parallel programming framework, we describe the methodology and the implementation of a parallel Monte Carlo simulation infrastructure extended with user-defined on-line data filtering and mining functions. The simulator and the on-line analysis were validated on large multi-core platforms and representative proof-of-concept biological systems.
Keywords
- multi-core
- parallel simulation
- stochastic simulation
- on-line clustering
This research has been funded by the BioBITs Project (Converging Technologies 2007, Biotechnology-ICT, Regione Piemonte). The authors acknowledge the HPC Advisory Council (www.hpcadvisorycouncil.com) University Award spring 2011.
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Aldinucci, M. et al. (2012). On Parallelizing On-Line Statistics for Stochastic Biological Simulations. In: Alexander, M., et al. Euro-Par 2011: Parallel Processing Workshops. Euro-Par 2011. Lecture Notes in Computer Science, vol 7156. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29740-3_2
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DOI: https://doi.org/10.1007/978-3-642-29740-3_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29739-7
Online ISBN: 978-3-642-29740-3
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