Métodos acotados de aplicación de reglas de evolución para la implementación de Sistemas P de Transición

La característica fundamental de la Computación Natural se basa en el empleo de conceptos, principios y mecanismos del funcionamiento de la Naturaleza. La Computación Natural -y dentro de ésta, la Computación de Membranas- surge como una posible alternativa a la computación clásica y como resultado de la búsqueda de nuevos modelos de computación que puedan superar las limitaciones presentes en los modelos convencionales. En concreto, la Computación de Membranas se originó como un intento de formular un nuevo modelo computacional inspirado en la estructura y el funcionamiento de las células biológicas: los sistemas basados en este modelo constan de una estructura de membranas que actúan a la vez como separadores y como canales de comunicación, y dentro de esa estructura se alojan multiconjuntos de objetos que evolucionan de acuerdo a unas determinadas reglas de evolución. Al conjunto de dispositivos contemplados por la Computación de Membranas se les denomina genéricamente como Sistemas P. Hasta el momento los Sistemas P sólo han sido estudiados a nivel teórico y no han sido plenamente implementados ni en medios electrónicos, ni en medios bioquímicos, sólo han sido simulados o parcialmente implementados. Por tanto, la implantación de estos sistemas es un reto de investigación abierto. Esta tesis aborda uno de los problemas que debe ser resuelto para conseguir la implantación de los Sistemas P sobre plataformas hardware. El problema concreto se centra en el modelo de los Sistemas P de Transición y surge de la necesidad de disponer de algoritmos de aplicación de reglas que, independientemente de la plataforma hardware sobre la que se implementen, cumplan los requisitos de ser no deterministas, masivamente paralelos y además su tiempo de ejecución esté estáticamente acotado. Como resultado se ha obtenido un conjunto de algoritmos (tanto para plataformas secuenciales, como para plataformas paralelas) que se adecúan a las diferentes configuraciones de los Sistemas P. ABSTRACT The main feature of Natural Computing is the use of concepts, principles and mechanisms inspired by Nature. Natural Computing and within it, Membrane Computing emerges as an potential alternative to conventional computing and as from the search for new models of computation that may overcome the existing limitations in conventional models. Specifically, Membrane Computing was created to formulate a new computational paradigm inspired by the structure and functioning of biological cells: it consists of a membrane structure, which acts as separators as well as communication channels, and within this structure are stored multisets of objects that evolve according to certain evolution rules. The set of computing devices addressed by Membrane Computing are generically known P systems. Up to now, no P systems have been fully implemented yet in electronic or biochemical means. They only have been studied in theory, simulated or partially implemented. Therefore, the implementation of these systems is an open research challenge. This thesis addresses one of the problems to be solved in order to deploy P systems on hardware platforms. This specific problem is focused on the Transition P System model and emerges from the need of providing application rules algorithms that independently on the hardware platform on which they are implemented, meets the requirements of being nondeterministic, massively parallel and runtime-bounded. As a result, this thesis has developed a set of algorithms for both platforms, sequential and parallel, adapted to all possible configurations of P systems

Delimited Massively Parallel Algorithm based on Rules Elimination for Application of Active Rules in Transition P Systems

In the field of Transition P systems implementation, it has been determined that it is very important to determine in advance how long takes evolution rules application in membranes. Moreover, to have time estimations of rules application in membranes makes possible to take important decisions related to hardware/software architectures design. The work presented here introduces an algorithm for applying active evolution rules in Transition P systems, which is based on active rules elimination. The algorithm complies the requisites of being nondeterministic, massively parallel, and what is more important, it is time delimited because it is only dependant on the number of membrane evolution rules

Fast Linear Algorithm for Active Rules Application in Transition P Systems

Transition P systems are computational models based on basic features of biological membranes and the observation of biochemical processes. In these models, membrane contains objects multisets, which evolve according to given evolution rules. In the field of Transition P systems implementation, it has been detected the necessity to determine whichever time are going to take active evolution rules application in membranes. In addition, to have time estimations of rules application makes possible to take important decisions related to the hardware/software architectures design. In this paper we propose a new evolution rules application algorithm oriented towards the implementation of Transition P systems. The developed algorithm is sequential and, it has a linear order complexity in the number of evolution rules. Moreover, it obtains the smaller execution times, compared with the preceding algorithms. Therefore the algorithm is very appropriate for the implementation of Transition P systems in sequential devices

Parallel algorithm for P Systems implementation in multiprocessors

PARALLEL ALGORITHM FOR P SYSTEMS IMPLEMENTATION IN MULTIPROCESSOR

A Circuit Implementing Massive Parallelism in Transition P Systems.

P-systems are based on biological membranes and try to emulate cell behavior and its evolution due to the presence of chemical elements. These systems perform computation through transition between two consecutive configurations, which consist in a m-tuple of multisets present at any moment in the existing m regions of the system. Transition between two configurations is performed by using evolution rules also present in each region. Among main Transition P-systems characteristics are massive parallelism and non determinism. This work is part of a very large project and tries to determine the design of a hardware circuit that can improve remarkably the process involved in the evolution of a membrane. Process in biological cells has two different levels of parallelism: the first one, obviously, is the evolution of each cell inside the whole set, and the second one is the application of the rules inside one membrane. This paper presents an evolution of the work done previously and includes an improvement that uses massive parallelism to do transition between two states. To achieve this, the initial set of rules is transformed into a new set that consists in all their possible combinations, and each of them is treated like a new rule (participant antecedents are added to generate a new multiset), converting an unique rule application in a way of parallelism in the means that several rules are applied at the same time. In this paper, we present a circuit that is able to process this kind of rules and to decode the result, taking advantage of all the potential that hardware has to implement P Systems versus previously proposed sequential solutions