J. Yu
Graph has been widely used as a data structure to abstract complex relationships among entities. There exist many large graphs, for example, online bibliographic networks (DBLP, PubMed), online social networks (Facebook, Twitter, Flickr, LinkedIn), Wikipedia, or even the entire WWW. To support graph analytics over large graphs, algorithms are designed and systems are developed to maintain information, understand the complex relationships, and discovery knowledge. There are several challenges. Firstly, many graph analytical tasks are hard problems. To compute the exact solution for such hard problems induces high time complexities, making it impractical to be applied to real-world huge graphs. It needs to design new graph algorithms. Secondly, there are many graph processing systems developed. Such graph processing systems have their own features to deal with certain type of graph tasks efficiently, but not all. It needs to build an unified graph processing system that can efficiently process graph tasks in general. In this project, we concentrate on new algorithms design and graph processing system development.