Practical implementation of a network-based stochastic biochemical simulation system on an FPGA

Abstract

Stochastic simulation of biochemical reaction networks are widely focused by life scientists to represent stochastic behaviors in cellular processes. Stochastic algorithm has loop-and thread-level parallelism, and it is suitable for running on application specific hardware to achieve high performance with low cost. We have implemented and evaluated the FPGA-based stochastic simulator according to theoretical research of the algorithm. This paper introduces an improved architecture for accelerating a stochastic simulation algorithm called the Next Reaction Method. This new architecture has scalability to various size of FPGA. As the result with a middle-range FPGA, 5.38 times higher throughput was obtained compared to software running on a Core 2 Quad Q6600 2.40 GHz.