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Pangolin
2020
Proceedings of the VLDB Endowment
There is growing interest in graph pattern mining (GPM) problems such as motif counting. GPM systems have been developed to provide unified interfaces for programming algorithms for these problems and for running them on parallel systems. However, existing systems may take hours to mine even simple patterns in moderate-sized graphs, which significantly limits their real-world usability. We present Pangolin, an efficient and flexible in-memory GPM framework targeting shared-memory CPUs and GPUs.
doi:10.14778/3389133.3389137
fatcat:53fbcjljv5hpxa5yeqv4ioviou