A Circuit Implementing Massive Parallelism in Transition P Systems

ransition 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.

HW Implementation of a Optimized Algorithm for the Application of Active Rules in a Transition P-system

P systems or Membrane Computing are a type of a distributed, massively parallel and non deterministic system based on biological membranes. They are inspired in the way cells process chemical compounds, energy and information. These systems perform a computation through transition between two consecutive configurations. As it is well known in membrane computing, a configuration consists in a m-tuple of multisets present at any moment in the existing m regions of the system at that moment time. Transitions between two configurations are performed by using evolution rules which are in each region of the system in a non-deterministic maximally parallel manner. This work is part of an exhaustive investigation line. The final objective is to implement a HW system that evolves as it makes a transition P-system. To achieve this objective, it has been carried out a division of this generic system in several stages, each of them with concrete matters. In this paper the stage is developed by obtaining the part of the system that is in charge of the application of the active rules. To count the number of times that the active rules is applied exist different algorithms. Here, it is presents an algorithm with improved aspects: the number of necessary iterations to reach the final values is smaller than the case of applying step to step each rule. Hence, the whole process requires a minor number of steps and, therefore, the end of the process will be reached in a shorter length of time.

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.