Parallel Acceleration of Subgraph Enumeration in the Process of Network Motif Detection

Network motifs bring a great interest to many fields, because they are a perfect candidate to speed up the applied research in the understanding of complex networks dynamics. One of the biggest problems raised in the process of finding these motifs is the performance. Starting from splitting the initial network into subgraphs to the subgraphs clusterization, each algorithm used addresses an NP problem. Hence there are many algorithms that are trying to solve network motifs discovery, however there is no perfect approach talking from a time performance perspective, but only solutions that are faster than others. This paper presents a redesign of one of the most competitive algorithms for subgraphs enumeration found in the literature called ESU. In the proposed approach a given network can be processed by using parallel programming, either with a process-driven model, or a hybrid one (process-driven and thread-driven). Finally, the existing and proposed models are compared using benchmark graphs, revealing competitive results.