GPU-powered Simulation Methodologies for Biological Systems

Daniela Besozzi
(University of Milano)
Giulio Caravagna
(University of Milano Bicocca)
Paolo Cazzaniga
(University of Bergamo)
Marco Nobile
(University of Milano Bicocca)
Dario Pescini
(University of Milano Bicocca)
Alessandro Re
(University of Milano Bicocca)

The study of biological systems witnessed a pervasive cross-fertilization between experimental investigation and computational methods. This gave rise to the development of new methodologies, able to tackle the complexity of biological systems in a quantitative manner. Computer algorithms allow to faithfully reproduce the dynamics of the corresponding biological system, and, at the price of a large number of simulations, it is possible to extensively investigate the system functioning across a wide spectrum of natural conditions. To enable multiple analysis in parallel, using cheap, diffused and highly efficient multi-core devices we developed GPU-powered simulation algorithms for stochastic, deterministic and hybrid modeling approaches, so that also users with no knowledge of GPUs hardware and programming can easily access the computing power of graphics engines.

In Alex Graudenzi, Giulio Caravagna, Giancarlo Mauri and Marco Antoniotti: Proceedings Wivace 2013 - Italian Workshop on Artificial Life and Evolutionary Computation (Wivace 2013), Milan, Italy, July 1-2, 2013, Electronic Proceedings in Theoretical Computer Science 130, pp. 87–91.
Published: 30th September 2013.

ArXived at: http://dx.doi.org/10.4204/EPTCS.130.14 bibtex PDF
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