Cecilia, José M.Guerrero, Ginés D.García, José M.Martínez del Amor, Miguel ÁngelPérez Hurtado de Mendoza, IgnacioPérez Jiménez, Mario de Jesús2018-01-102018-01-102009Cecilia, J.M., Guerrero, G.D., García, J.M., Martínez del Amor, M.Á., Pérez Hurtado, I. y Pérez Jiménez, M.d.J. (2009). A massively parallel framework using P systems and GPUs. En SAAHPC 2009: Symposium on Application Accelerators in High-Performance Computing Urbana, Illinois: National Center for Supercomputing Applications at the University of Illinois.http://hdl.handle.net/11441/68619Since 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.application/pdfengAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/openAccess