• DocumentCode
    2941641
  • Title

    Optimized Parallel Implementation of Gillespie´s First Reaction Method on Graphics Processing Units

  • Author

    Dittamo, Cristian ; Cangelosi, Davide

  • Author_Institution
    Dept. of Comput. Sci., Univ. of Pisa, Pisa
  • fYear
    2009
  • fDate
    20-22 Feb. 2009
  • Firstpage
    156
  • Lastpage
    161
  • Abstract
    The simulation of chemical reacting systems is one of the most challenging topics in Systems Biology, due to their complexity and inherent randomness. The Gillespie´s Stochastic Simulation Algorithm (SSA) is a standard algorithm to simulate well-stirred biochemical systems, butthe computational burden makes this algorithm slow to compute for many realistic problems. Recent programmability improvements allow non-graphics applications to leverage the Graphics Processing Units´ (GPUs) computational power. This paper describes practical issues arising by a parallel implementation on GPU technology, shows how to reduce the memory space required by one of the most known versions of SSA, and presents the application of the implemented algorithm to a test model.
  • Keywords
    biochemistry; coprocessors; stochastic processes; Gillespie first reaction method; Gillespie stochastic simulation algorithm; chemical reacting systems simulation; graphics processing units; optimized parallel implementation; systems biology; well-stirred biochemical systems; Biological system modeling; Biology computing; Chemicals; Computational modeling; Graphics; Optimization methods; Space technology; Stochastic systems; Systems biology; Testing; First Reaction Method; Gillespie; Graphics Processing Unit; Stochastic simulation; data-parallel paradigm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Modeling and Simulation, 2009. ICCMS '09. International Conference on
  • Conference_Location
    Macau
  • Print_ISBN
    978-0-7695-3562-3
  • Electronic_ISBN
    978-1-4244-3561-6
  • Type

    conf

  • DOI
    10.1109/ICCMS.2009.42
  • Filename
    4797374