Simulation of Complex Biochemical Pathways in 3D Process Space via Heterogeneous Computing Platform: Preliminary Results

Abstract

Biological pathways typically consist of upto hundreds of reacting chemical species and reactions within a biological system. Modeling and simulation of biological pathways in explicit process space is a computationally intensive, both due to the number of interactions and time-scale of processes. Traditional stochastic or ODE based simulation of chemical processes ignore spatial and biological information. Hence there is a need for new underlying simulation algorithms as well as need for newer computing systems, platforms and techniques. Such pathways describe exhibit considerable behavioral complexity in multiple fundamental cellular processes. In this work we present a new heterogeneous computing platform to accelerate the simulation study of such complex biochemical pathways in 3D reaction process space. Several tasks involved in the simulation study has been carefully partitioned to run on a combination of reconfigurable hardware and massively parallel processor such as the GPU. This paper also presents an implementation to accelerate one of the most compute intensive tasks - sifting through the reaction space to determine reacting particles. Finally, we present the new heterogeneous computing framework integrating a FPGA and GPU to accelerate the computation over the use of a any single platform. This framework can achieve 10-times speedup over a single GPU-only platform. Besides, the extensible architecture is general enough to be used to study a variety of biological pathways in order to gain deeper insights into biomolecular systems.