Efficient Parallelization of the Stochastic Simulation Algorithm for Chemically Reacting Systems On the Graphics Processing Unit

Authors:
Hong Li;Linda Petzold
Affiliations:
DEPARTMENT OF COMPUTER SCIENCE, UNIVERSITY OF CALIFORNIA,SANTA BARBARA, CA 93106, U.S.A.;DEPARTMENT OF COMPUTER SCIENCE, UNIVERSITY OF CALIFORNIA,SANTA BARBARA, CA 93106, U.S.A.
Venue:
International Journal of High Performance Computing Applications
Year:
2010

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Abstract

The small number of some reactant molecules in biological systems formed by living cells can result in dynamical behavior which cannot be captured by traditional deterministic models. In such a problem, a more accurate simulation can be obtained with discrete stochastic simulation (Gillespieâ聙聶s stochastic simulation algorithm â聙聰 SSA). Many stochastic realizations are required to capture accurate statistical information of the solution. This carries a very high computational cost. The current generation of graphics processing units (GPU) is well-suited to this task. In this paper we describe our implementation and present some computational experiments illustrating the power of this technology for this important and challenging class of problems.