GPU-based massively parallel quantum inspired genetic algorithm for detection of communities in complex networks

Abstract

The paper presents a parallel implementation of a variant of quantum inspired genetic algorithm (QIGA) for the problem of community structure detection in complex networks using NVIDIA® Compute Unified Device Architecture (CUDA®) technology. The paper explores feasibility of the approach in the domain of complex networks. The approach does not require any knowledge of the number of communities beforehand and works well for both directed and undirected networks. Experiments on benchmark networks show that the method is able to successfully reveal community structure with high modularity.