<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">José M. Cecilia</style></author><author><style face="normal" font="default" size="100%">Ginés D. Guerrero</style></author><author><style face="normal" font="default" size="100%">José M. García</style></author><author><style face="normal" font="default" size="100%">Miguel A. Martínez-del-Amor</style></author><author><style face="normal" font="default" size="100%">Ignacio Pérez-Hurtado</style></author><author><style face="normal" font="default" size="100%">Mario J. Pérez-Jiménez</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A massively parallel framework using P systems and GPUs</style></title><secondary-title><style face="normal" font="default" size="100%">Symposium on Application Accelerators in High Performance Computing</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">July 2009</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.p-lingua.org/~miguel/papers/2009/psystem_saahpc09.pdf</style></url></web-urls></urls><pub-location><style face="normal" font="default" size="100%">Illinois, USA</style></pub-location><abstract><style face="normal" font="default" size="100%">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 mod-                                                                   
eling 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.                                                                     </style></abstract><notes><style face="normal" font="default" size="100%">Poster also available: http://www.p-lingua.org/~miguel/papers/2009/psystem_poster_saahpc09.pdf
Webpage of the conference: http://saahpc.ncsa.illinois.edu/09/agenda.html</style></notes></record></records></xml>