Distributed Simulation of NEPs Based On-Demand Cloud Elastic Computation

Networks of Evolutionary Processors (NEP) are a bio-inspired computational model able to solve NP complete problems in an efficient manner. Up to now, the only way to analyze and execute these devices is through hardware and software simulators able to encapsulate the inherent parallelism and the efficiency in their computations. Nowadays, simulators for these models only cover many software applications developed under sequential/parallel architectures over multicore desktop computers or clusters of computers. Most of them, are not able to handle the size of non trivial problems within a massively parallel environment. We consider that cloud computation offers an interesting and promising option to overcome the drawbacks of these solutions. In this paper, we propose a novel parallel distributed architecture to simulate NEPs using on-demand cloud elastic computation. A flexible and extensible simulator is developed in order to demonstrate the suitability and scalability of our architecture with several variants of NEP.