A massively parallel framework using P systems and GPUs

Jose M. Cecilia, Gines D. Guerrero, Jose M. Garcia, Miguel A. Martinez-del-Amor, Ignacio Perez-Hurtado, Mario J. Perez-Jimenez
Grupo de Arquitectura y Computacion Paralela, Dpto. Ingenieria y Tecnologia de Computadores, Universidad de Murcia, Campus de Espinardo, 30100 Murcia, Spain
Symposium on Application Accelerators in High Performance Computing, 2009 (SAAHPC’09)


   title={A massively parallel framework using P systems and GPUs},

   author={Cecilia, J.M. and Guerrero, G.D. and Garc{i}a, J.M. and Mart{i}nez–del–Amor, M.A. and P{‘e}rez–Hurtado, I. and P{‘e}rez–Jim{‘e}nez, M.J.},

   booktitle={Application Accelerators in High Performance Computing, 2009 Symposium, Papers},



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Since CUDA programing model appeared on the general purpose computations, the developers can extract all the power contained in GPUs (Graphics Processing Unit) across many computational domains. Among these domains, P systems or membrane systems provide a high level computational modeling framework that allows, in theory, to obtain polynomial time solutions to NP-complete problems by trading time for space, and also to model biological phenomena in the area of computational systems biology. P systems are massively parallel distributed devices and their computation can be divided in two levels of parallelism: membranes, that can be expressed as blocks in CUDA programming model; and objects, that can be expressed as threads in CUDA programming model. In this paper, we present our initial ideas of developing a simulator for the class of recognizer P systems with active membranes by using the CUDA programing model to exploit the massively parallel nature of those systems at maximum. Experimental results of a preliminary version of our simulator on a Tesla C1060 GPU show a 60X of speed-up compared to the sequential code.
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