cuTauLeaping: a GPU-powered tau-leaping stochastic simulator for massive parallel analyses of biological systems.

Tau-leaping is a stochastic simulation algorithm that efficiently reconstructs the temporal evolution of biological systems, modeled according to the stochastic formulation of chemical kinetics. The analysis of dynamical properties of these systems in physiological and perturbed conditions usually r...

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Autores principales:	Marco S Nobile, Paolo Cazzaniga, Daniela Besozzi, Dario Pescini, Giancarlo Mauri
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2014
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/f0d8741414c140a3bd4c762d19c44e64
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spelling	oai:doaj.org-article:f0d8741414c140a3bd4c762d19c44e642021-11-18T08:26:30ZcuTauLeaping: a GPU-powered tau-leaping stochastic simulator for massive parallel analyses of biological systems.1932-620310.1371/journal.pone.0091963https://doaj.org/article/f0d8741414c140a3bd4c762d19c44e642014-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24663957/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203Tau-leaping is a stochastic simulation algorithm that efficiently reconstructs the temporal evolution of biological systems, modeled according to the stochastic formulation of chemical kinetics. The analysis of dynamical properties of these systems in physiological and perturbed conditions usually requires the execution of a large number of simulations, leading to high computational costs. Since each simulation can be executed independently from the others, a massive parallelization of tau-leaping can bring to relevant reductions of the overall running time. The emerging field of General Purpose Graphic Processing Units (GPGPU) provides power-efficient high-performance computing at a relatively low cost. In this work we introduce cuTauLeaping, a stochastic simulator of biological systems that makes use of GPGPU computing to execute multiple parallel tau-leaping simulations, by fully exploiting the Nvidia's Fermi GPU architecture. We show how a considerable computational speedup is achieved on GPU by partitioning the execution of tau-leaping into multiple separated phases, and we describe how to avoid some implementation pitfalls related to the scarcity of memory resources on the GPU streaming multiprocessors. Our results show that cuTauLeaping largely outperforms the CPU-based tau-leaping implementation when the number of parallel simulations increases, with a break-even directly depending on the size of the biological system and on the complexity of its emergent dynamics. In particular, cuTauLeaping is exploited to investigate the probability distribution of bistable states in the Schlögl model, and to carry out a bidimensional parameter sweep analysis to study the oscillatory regimes in the Ras/cAMP/PKA pathway in S. cerevisiae.Marco S NobilePaolo CazzanigaDaniela BesozziDario PesciniGiancarlo MauriPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 9, Iss 3, p e91963 (2014)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Marco S Nobile Paolo Cazzaniga Daniela Besozzi Dario Pescini Giancarlo Mauri cuTauLeaping: a GPU-powered tau-leaping stochastic simulator for massive parallel analyses of biological systems.
description	Tau-leaping is a stochastic simulation algorithm that efficiently reconstructs the temporal evolution of biological systems, modeled according to the stochastic formulation of chemical kinetics. The analysis of dynamical properties of these systems in physiological and perturbed conditions usually requires the execution of a large number of simulations, leading to high computational costs. Since each simulation can be executed independently from the others, a massive parallelization of tau-leaping can bring to relevant reductions of the overall running time. The emerging field of General Purpose Graphic Processing Units (GPGPU) provides power-efficient high-performance computing at a relatively low cost. In this work we introduce cuTauLeaping, a stochastic simulator of biological systems that makes use of GPGPU computing to execute multiple parallel tau-leaping simulations, by fully exploiting the Nvidia's Fermi GPU architecture. We show how a considerable computational speedup is achieved on GPU by partitioning the execution of tau-leaping into multiple separated phases, and we describe how to avoid some implementation pitfalls related to the scarcity of memory resources on the GPU streaming multiprocessors. Our results show that cuTauLeaping largely outperforms the CPU-based tau-leaping implementation when the number of parallel simulations increases, with a break-even directly depending on the size of the biological system and on the complexity of its emergent dynamics. In particular, cuTauLeaping is exploited to investigate the probability distribution of bistable states in the Schlögl model, and to carry out a bidimensional parameter sweep analysis to study the oscillatory regimes in the Ras/cAMP/PKA pathway in S. cerevisiae.
format	article
author	Marco S Nobile Paolo Cazzaniga Daniela Besozzi Dario Pescini Giancarlo Mauri
author_facet	Marco S Nobile Paolo Cazzaniga Daniela Besozzi Dario Pescini Giancarlo Mauri
author_sort	Marco S Nobile
title	cuTauLeaping: a GPU-powered tau-leaping stochastic simulator for massive parallel analyses of biological systems.
title_short	cuTauLeaping: a GPU-powered tau-leaping stochastic simulator for massive parallel analyses of biological systems.
title_full	cuTauLeaping: a GPU-powered tau-leaping stochastic simulator for massive parallel analyses of biological systems.
title_fullStr	cuTauLeaping: a GPU-powered tau-leaping stochastic simulator for massive parallel analyses of biological systems.
title_full_unstemmed	cuTauLeaping: a GPU-powered tau-leaping stochastic simulator for massive parallel analyses of biological systems.
title_sort	cutauleaping: a gpu-powered tau-leaping stochastic simulator for massive parallel analyses of biological systems.
publisher	Public Library of Science (PLoS)
publishDate	2014
url	https://doaj.org/article/f0d8741414c140a3bd4c762d19c44e64
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cuTauLeaping: a GPU-powered tau-leaping stochastic simulator for massive parallel analyses of biological systems.

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