Accelerated Simulations of Chemical Reaction Systems using the Stochastic Simulation Algorithm on GPUs

Stochasticity due to fluctuations in chemical reactions can play important roles in cellular network-driven processes. Although the Stochastic Simulation Algorithm (SSA, aka Gillespie Algorithm) has long been accepted as a suitable method to solve the time-dependent chemical master equation, its computational cost is prohibitive for large scale complex networks such as those found in cellular processes. Here we present GPU-SSA, an implementation of the SSA formalism utilizing Graphics Processing Units for use in Python using the PySB modeling framework. We show that the GPU implementation of SSA can achieve significant speedup compared to parallel CPU or single-core CPU implementations. We further include supplementary didactic material to demonstrate how to incorporate GPU-SSA workflows for interested readers.