Process Simulation of Complex Biochemical Pathways in Explicit 3D Space Enabled by Heterogeneous Computing Platform

Abstract

Biological pathways typically consist of dozens of reacting chemical species and hundreds of equations describing reactions within the biological system. Modeling and simulation of such biological pathways in explicit process space is a computationally intensive due to the size of the system complexity and nature of the interactions. Such biological pathways exhibit considerable behavioral complexity in multiple fundamental cellular processes. Hence, there is a strong need for new underlying simulation algorithms as well as need for newer computing platforms, systems and techniques. In this work we present a novel 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 a 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 and obtain better performance over the use of any single platform. The platform achieves 5x total speedup when compared to 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.