IPregel

Abstract

The expressiveness of the vertex-centric programming model introduced by Pregel attracted great attention. Over the years, numerous frameworks emerged, abiding by the same programming model, while relying on widely different architectural designs. The vast majority of existing vertex-centric frameworks exploits distributed memory parallelism or out-of-core computations. To our knowledge, only one vertex-centric framework is designed upon in-memory storage and shared memory parallelism. Unfortunately, while built on a faster architecture than that of other vertex-centric frameworks, it did not prove to significantly outperform other existing solutions.In this paper we present iPregel: another in-memory shared memory vertex-centric framework. The optimisations developed and presented in this paper particularly target three hotspots of vertex-centric calculations: selecting active vertices, routing messages to their recipient and updating recipients inbox. We compare iPregel against the state-of-the-art in-memory distributed memory framework Pregel+ on three of the most common vertex-centric applications: PageRank, Hashmin and the Single-Source Shortest Path. Experiments demonstrate that the single-node framework iPregel is faster than its distributed memory counterpart until at least 11 nodes are used. Further experiments show that iPregel completes a PageRank application with an order of magnitude less memory than popular vertex-centric frameworks.