GPSA: A Graph Processing System with Actors

Jianhua Sun, Dongwei Zhou, Hao Chen, Cheng Chang, Zhiwen Chen, Wentao Li, Ligang He

Abstract: Due to the increasing need to process the fast growing graph-structured data (e.g. Social networks and Web graphs), designing high performance graph processing systems becomes one of the most urgent problems facing systems researchers. In this paper, we introduce GPSA, a single-machine graph processing system based on an actor computation model inspired by the Bulk Synchronous Parallel(BSP) computation model. GPSA takes advantage of actors to improve the concurrency on a single machine with limited resource. GPSA improves the conventional BSP computation model to fit in the actor programming paradigm by decoupling the message dispatching from the computation. Furthermore, we exploit memory mapping to avoid explicit data management to improve I/O performance. Experimental evaluation shows that our system outperforms existing systems by 2x-6x in processing large-scale graphs on a single system.