Literature DB >> 19162916

A massively parallel implementation of gillespie algorithm on FPGAs.

Luca Macchiarulo1.   

Abstract

This paper targets the acceleration of complex stochastic simulations of biochemical systems by a dedicated hardware architecture on configurable devices (FPGA). Existing approaches are discussed and compared with the proposed one, and experimental data is introduced to support the feasibility of the system. Retargetable hardware description can be automatically generated for any suitable simulation problem, and preliminary results show very high performance - 100 million time steps per second for large models (1000 reactions).

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Year:  2008        PMID: 19162916     DOI: 10.1109/IEMBS.2008.4649413

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  4 in total

1.  Accelerating the Gillespie τ-Leaping Method using graphics processing units.

Authors:  Ivan Komarov; Roshan M D'Souza; Jose-Juan Tapia
Journal:  PLoS One       Date:  2012-06-08       Impact factor: 3.240

2.  Parallel solutions for voxel-based simulations of reaction-diffusion systems.

Authors:  Daniele D'Agostino; Giulia Pasquale; Andrea Clematis; Carlo Maj; Ettore Mosca; Luciano Milanesi; Ivan Merelli
Journal:  Biomed Res Int       Date:  2014-06-12       Impact factor: 3.411

3.  Accelerating the Gillespie Exact Stochastic Simulation Algorithm using hybrid parallel execution on graphics processing units.

Authors:  Ivan Komarov; Roshan M D'Souza
Journal:  PLoS One       Date:  2012-11-09       Impact factor: 3.240

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

Authors:  Marco S Nobile; Paolo Cazzaniga; Daniela Besozzi; Dario Pescini; Giancarlo Mauri
Journal:  PLoS One       Date:  2014-03-24       Impact factor: 3.240

  4 in total

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