The computational investigation of a biological system often requires the execution of a large number of simulations to analyze its dynamics, and to derive useful knowledge on its behavior under physiologicaland perturbed conditions. This analysis usually turns out into very high computational costs when simulations are run on central processing units (CPUs), therefore demanding a shift to the use of high performance processors. In this work we present a simulator of biological systems, called cupSODA, which exploits the higher memory bandwidth and computational capability of graphics processing units (GPUs). This software allows to execute parallel simulations of the dynamics of biological systems, by first deriving a set of ordinary differential equations from reaction-based mechanistic models defined according to the massaction kinetics, and then exploiting the numerical integration algorithm LSODA. We show that cupSODA can achieve a 112× speedup on GPUs with respect to equivalent executions of LSODA on CPUs.
Nobile, M., Besozzi, D., Cazzaniga, P., Mauri, G., Pescini, D. (2013). cupSODA: A CUDA-Powered Simulator of Mass-Action Kinetics. In Proc. PaCT 2013 – 12th Int. Conf. on Parallel Computing Technologies (pp.344-357). Springer [10.1007/978-3-642-39958-9_32].
cupSODA: A CUDA-Powered Simulator of Mass-Action Kinetics
NOBILE, MARCO SALVATORE;BESOZZI, DANIELA;MAURI, GIANCARLO;PESCINI, DARIO
2013
Abstract
The computational investigation of a biological system often requires the execution of a large number of simulations to analyze its dynamics, and to derive useful knowledge on its behavior under physiologicaland perturbed conditions. This analysis usually turns out into very high computational costs when simulations are run on central processing units (CPUs), therefore demanding a shift to the use of high performance processors. In this work we present a simulator of biological systems, called cupSODA, which exploits the higher memory bandwidth and computational capability of graphics processing units (GPUs). This software allows to execute parallel simulations of the dynamics of biological systems, by first deriving a set of ordinary differential equations from reaction-based mechanistic models defined according to the massaction kinetics, and then exploiting the numerical integration algorithm LSODA. We show that cupSODA can achieve a 112× speedup on GPUs with respect to equivalent executions of LSODA on CPUs.
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