high performance computing on graphics processing units: hgpu.org

A network generated by randomly rewiring the edges of an original network on some constraint conditions is called the null model of the original network. It’s a useful tool for revealing some mechanisms affecting the topology of networks. As the scales of networks become larger and larger, time consumption of generating null models increases. How to randomly rewire the edges of a large-scale network quickly becomes an urgent. In this paper, the generating algorithms for 0K, 1K and 2K null models of networks are implemented on GPU, which have not been done yet before. The experimental results show that the parallel algorithms greatly reduce the time consumption. Generating null models for large-scale networks on GPU is an efficient solution for study on null models of large-scale networks.