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Accelerating the Gillespie τ-Leaping Method Using Graphics Processing Units

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  • Ivan Komarov
  • Roshan M D’Souza
  • Jose-Juan Tapia

Abstract

The Gillespie τ-Leaping Method is an approximate algorithm that is faster than the exact Direct Method (DM) due to the progression of the simulation with larger time steps. However, the procedure to compute the time leap τ is quite expensive. In this paper, we explore the acceleration of the τ-Leaping Method using Graphics Processing Unit (GPUs) for ultra-large networks ( reaction channels). We have developed data structures and algorithms that take advantage of the unique hardware architecture and available libraries. Our results show that we obtain a performance gain of over 60x when compared with the best conventional implementations.

Suggested Citation

  • Ivan Komarov & Roshan M D’Souza & Jose-Juan Tapia, 2012. "Accelerating the Gillespie τ-Leaping Method Using Graphics Processing Units," PLOS ONE, Public Library of Science, vol. 7(6), pages 1-7, June.
    • Handle: RePEc:plo:pone00:0037370
    DOI: 10.1371/journal.pone.0037370
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