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Parallelizing Biochemical Stochastic Simulations: A Comparison of GPUs and Intel Xeon Phi Processors

  • P. Cazzaniga
  • F. Ferrara
  • M. S. Nobile
  • D. BesozziEmail author
  • G. Mauri
Conference paper
First Online:
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9251)

Abstract

Stochastic simulations of biochemical reaction networks can be computationally expensive on Central Processing Units (CPUs), especially when a large number of simulations is required to compute the system states distribution or to carry out advanced model analysis. Anyway, since all simulations are independent, parallel architectures can be exploited to reduce the overall running time. The purpose of this work is to compare the computational performance of CPUs, general-purpose Graphics Processing Units (GPUs) and Intel Xeon Phi coprocessors based on the Many Integrated Core (MIC) architecture, for the execution of Gillespie’s Stochastic Simulation Algorithm (SSA). To this aim, we consider an ad hoc implementation of SSA on GPUs, while exploiting the peculiar capability of MICs of reusing existing CPUs source code. We measure the running time needed to execute several batches of simulations, for various biochemical models of increasing size. Our results show that in all tested cases GPUs outperform the other architectures, and that reusing available code with the MICs does not represent a clever strategy to fully leverage Xeon Phi horsepower.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • P. Cazzaniga
    • 1
  • F. Ferrara
    • 2
  • M. S. Nobile
    • 2
  • D. Besozzi
    • 3
    Email author
  • G. Mauri
    • 2
  1. 1.Dipartimento di Scienze Umane e SocialiUniversità degli Studi di BergamoBergamoItaly
  2. 2.Dipartimento di Informatica, Sistemistica e ComunicazioneUniversità degli Studi di Milano-BicoccaMilanoItaly
  3. 3.Dipartimento di InformaticaUniversità degli Studi di MilanoMilanoItaly

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