Analysis and Evaluation of the GAS Model for Distributed Graph Computation

Abstract

Compared with distributed graph computation, traditionally single node computation is unfitted in processing large scale graph data. The GAS (Gather, Apply and Scatter) Model is a universal vertex-cut graph computation programming model based on edge-centric programs to support graph algorithms, which process distributed graph computation after graph partition. In this paper, we introduce that three minor-steps of GAS. We then analyze more complete process of GAS considering intra-node computation and internode communication of distributed graph computation. Based on our analysis, we evaluate the performance in different nodes of graph analysis algorithm applying GAS model. The evaluation shows that the bottleneck is computation performance or communication bandwidth depending on number of nodes, which is an inspiration of optimizing the GAS model.