Abstract
The vertex-centric (VC) computation model has emerged as a promising approach for easy parallel programming and massive parallel execution for big graph processing. A simple graph computation can easily be implemented in the VC model, but some algorithms cannot easily be implemented in the VC model. Examples of the latter algorithms are those that use vertex subsets or subgraphs as a manipulation unit. Such a “global view style” is natural for programmers to design graph algorithms, but the VC model requires us to redesign algorithms in the “local view style” focusing on a vertex. The gap between these styles prevents us from writing parallel programs for useful graph computations. In this paper, we propose a novel DSL for graph processing that can be used to write parallel programs for big graph processing in the “global view style”. It is compiled into the VC model so that it can enjoy massive parallelism in various parallel computing environments including commercial cloud services like Amazon EC2. We show non-trivial examples in our DSL, and our experimental results show that the compiled program achieves good scalability.
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