In the last years, graphics processing units (GPUs) witnessed ever growing applications for a wide range of computational analyses in the field of life sciences. Despite its large potentiality, GPU computing risks remaining a niche for specialists, due to the programming and optimization skills it requires. In this work we present cupSODA, a simulator of biological systems that exploits the remarkable memory bandwidth and computational capability of GPUs. cupSODA allows to efficiently execute in parallel large numbers of simulations, which are usually required to investigate the emergent dynamics of a given biological system under different conditions. cupSODA works by automatically deriving the system of ordinary differential equations from a reaction-based mechanistic model, defined according to the mass-action kinetics, and then exploiting the numerical integration algorithm, LSODA. We show that cupSODA can achieve a 86 × speedup on GPUs with respect to equivalent executions of LSODA on the CPU. © 2014 Springer Science+Business Media New York.

GPU-accelerated simulations of mass-action kinetics models with cupSODA / M.S. Nobile, P. Cazzaniga, D. Besozzi, G. Mauri. - In: THE JOURNAL OF SUPERCOMPUTING. - ISSN 0920-8542. - 69:1(2014), pp. 17-24. [10.1007/s11227-014-1208-8]

GPU-accelerated simulations of mass-action kinetics models with cupSODA

D. Besozzi
Penultimo
;
2014

Abstract

In the last years, graphics processing units (GPUs) witnessed ever growing applications for a wide range of computational analyses in the field of life sciences. Despite its large potentiality, GPU computing risks remaining a niche for specialists, due to the programming and optimization skills it requires. In this work we present cupSODA, a simulator of biological systems that exploits the remarkable memory bandwidth and computational capability of GPUs. cupSODA allows to efficiently execute in parallel large numbers of simulations, which are usually required to investigate the emergent dynamics of a given biological system under different conditions. cupSODA works by automatically deriving the system of ordinary differential equations from a reaction-based mechanistic model, defined according to the mass-action kinetics, and then exploiting the numerical integration algorithm, LSODA. We show that cupSODA can achieve a 86 × speedup on GPUs with respect to equivalent executions of LSODA on the CPU. © 2014 Springer Science+Business Media New York.
Biochemical simulation; CUDA; cupSODA; Graphics processing unit; Systems biology
Settore INF/01 - Informatica
2014
http://www.springerlink.com/content/0920-8542
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/238699
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