P‑Lingua in two steps: flexibility and efficiency

Abstract

Membrane computing is a bio-inspired computing paradigm that lacks in vivo implementation. That is why software or hardware implementations have to be used to validate models. Several tools have been created for this purpose; some of them are created for specific purposes, such as solving a computationally hard problem; and others are more generic, to cover a broad spectrum of possible models. The former have the advantage of being very efficient, crucial for solving large instances of certain problems; however, this efficiency leads to a loss of generality, since algorithms are usually hard-coded and they do not allow other models. On the contrary, the latter are perfect tools for researchers, given that new models can be checked without much effort by defining them in the framework; since these algorithms have to simulate as many models as possible, they lack specificities to improve the performance. P-Lingua has been widely used to simulate membrane systems, having integrated both a language and a simulator. To obtain better results in terms of time used to simulate models defined in this language, a new perspective is studied. The model defined in P-Lingua will be compiled into C++ source code that will implement an ad hoc simulator. This code will consider specifications about how rules have to be executed, that is, some simple specifications of the semantics. To show how it works, some examples of specifications of models will be presented, which can be simulated using the new-developed GNU GPLv3 command-line tool pcc.