A Highly Efficient Runtime and Graph Library for Large Scale Graph Analytics

Abstract

Graph analytics on big data is currently a very active area of research in both industry and academia. To support graph analytics efficiently a large number of graph processing systems have emerged targeting various perspectives of a graph application such as in memory and on disk representations, persistent storage, database capability, runtimes and execution models for exploiting parallelism, etc.