Parallel algorithms for complex network clustering with GPUs

Abstract

The complex network clustering algorithm to research the topology properties of complex network needs to deal with large-scale nodes and links.Therefore,it requires higher computation performance to the large-scale complex networks that represent the complex system in reality.Hence,a parallel complex network clustering algorithm on Graphic Processing Units(GPU) based on fast Newman clustering algorithm was designed through the primitive technology that not only reduced the complexity of the parallel algorithm design but also improved the universality in various applications.Then from the thread scheduling strategies and the cache management perspectives,the optimal parallel complex network clustering algorithms were presented to deal with the load balance and the data reuse problem in computing process.The experiments results of the parallel complex network clustering algorithm and the optimal algorithms show that the optimal algorithms have better performance than the former.