SYNC or ASYNC: time to fuse for distributed graph-parallel computation

Large-scale graph-structured computation usually exhibits iterative and convergence-oriented computing nature, where input data is computed iteratively until a convergence condition is reached. Such features have led to the development of two different computation modes for graph-structured programs, namely synchronous (Sync) and asynchronous (Async) modes. Unfortunately, there is currently no in-depth study on their execution properties and thus programmers have to manually choose a mode, either requiring a deep understanding of underlying graph engines, or suffering from suboptimal performance. This paper makes the first comprehensive characterization on the performance of the two modes on a set of typical graph-parallel applications. Our study shows that the performance of the two modes varies significantly with different graph algorithms, partitioning methods, execution stages, input graphs and cluster scales, and no single mode consistently outperforms the other. To this end, t...

• Type: Journal
• Year: 2015
• Where: PPOPP
• Authors: Chenning Xie, Rong Chen, Haibing Guan, Binyu Zang, Haibo Chen
• Keywords: Distributed And Parallel Computing, PPOPP 2015