Balancing Performance, Flexibility, and Scalability in a Parallel Computing Platform for Membrane Computing Applications

Abstract

It is an open question whether it is feasible to develop a parallel computing platform for membrane computing applications that significantly outperforms equivalent sequential computing platforms while still achieving acceptable flexibility and scalability. To move closer to an answer to this question, we have investigated a novel approach to the development of a parallel computing platform for membrane computing applications that has the potential to deliver a good balance between performance, flexibility and scalability. This approach involves the use of reconfigurable hardware and an intelligent software component that is able to configure the hardware to suit the specific properties of the membrane computing model to be executed. We have already developed a prototype computing platform called Reconfig-P based on the approach. Reconfig-P is the first computing platform of its type to implement parallelism at both the system and region levels. In this paper, we describe the functionality of the intelligent software component responsible for hardware configuration in Reconfig-P, and perform an empirical analysis of the performance, flexibility and scalability of Reconfig-P. The empirical results suggest that the implementation approach on which Reconfig-P is based is a viable means of attaining a good balance between performance, flexibility and scalability.