Affiliations: Faculty of Mathematics and Computer Science,
University of Bucharest, Academiei 14, RO-010014, Bucharest, Romania.
{rceterchi, alexandru.tomescu}@gmail.com
Note: [] Address for correspondence: Faculty of Mathematics and Computer
Science, University of Bucharest, Academiei 14, RO-010014, Bucharest,
Romania
Abstract: Spiking neural P systems simulate the behavior of neurons sending
signals through axons. Recently, some applications concerning Boolean circuits
and sorting algorithms have been proposed. In this paper, we study the ability
of such systems to simulate a well known parallel sorting model, sorting
networks. First, we construct spiking neural P systems which act as comparators
of two values, and then show how to assemble these building blocks according to
the topology of a sorting network of N values. In the second part of the paper,
we formalize a framework to transform any sorting network into a network
composed of comparators which sort n values, 2 < n < N, having the same
behaviour as the original sorting network, but using fewer neurons and synapses
than the direct simulation. A comparison between the two models proposed here
and the sorting model of Ionescu and Sburlan is also given.
Keywords: membrane computing, spiking neural P systems, sorting networks, bitonic sort, optioptimal data layouts
