Research Group on Natural Computing

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.