Abstract
Subgraph isomorphism is one of the most important graph query operations. Existing subgraph isomorphic parallelization methods suffer from redundant sharing or fine-grained parallelism. SLF, a parallel approach for subgraph isomorphism algorithm based on tree-search, is proposed in this paper. In SLF, threads are prevented from sharing tasks blindly by an “Ask for Sharing” mechanism. The “Low-depth Priority Sharing” rule filters out unnecessary sharing, which reduces the number of sharing. The context of shared tasks is represented by embedding, which reduces the time and memory usage of sharing. We prove that the parallelization overhead of SLF is smaller than that of previous method. The experimental results show that SLF achieves higher speedup and efficiency than state-of-the-art parallelization methods.
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