<?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%">Ginés D. Guerrero</style></author><author><style face="normal" font="default" size="100%">José M. Cecilia</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%">Analysis of P systems simulation on CUDA</style></title><secondary-title><style face="normal" font="default" size="100%">XX Jornadas de Paralelismo</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%">September 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_jornadas09.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Servizo de Publicacións, Universidade da Coruña</style></publisher><pub-location><style face="normal" font="default" size="100%">A coruña, Spain</style></pub-location><pages><style face="normal" font="default" size="100%">289-294</style></pages><isbn><style face="normal" font="default" size="100%">84-9749-346-8</style></isbn><abstract><style face="normal" font="default" size="100%">GPUs (Graphics Processing Unit) have been con- 
solidated as a massively data-parallel coprocessor to
develop many general purpose computations, and en-
able developers to utilize several levels of parallelism
to obtain better performance of their applications.
The massively parallel nature of certain computa-
tions leads to use GPUs as an underlying architec-
ture, becoming a good alternative to other paral-
lel approaches. P systems or membrane systems
are theoretical devices inspired in the way that liv- 
ing cells work, providing computational models and
a high level computational modeling framework for
biological systems. They are massively parallel dis-
tributed, and non-deterministic systems. In this pa-
per, we evaluate the GPU as the underlying archi-
tecture to simulate the class of recognizer P systems
with active membranes. We analyze the performance
of three simulators implemented on CPU, CPU-GPU 
and GPU respectively. We compare them using a pre-
sented P system as a benchmark, showing that the
GPU is better suited than the CPU to simulate those
P systems due to its massively parallel nature.</style></abstract><notes><style face="normal" font="default" size="100%">Webpage of the conference: http://jornadas2009.gac.des.udc.es/</style></notes></record></records></xml>