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GraphZero: Breaking Symmetry for Efficient Graph Mining

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arxiv 1911.12877 v1 pith:SLDYNU3B submitted 2019-11-28 cs.PF cs.DB

classification cs.PFcs.DB
keywords patternsgraphgraphzerominingschedulesymmetryapplicationsautomine
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Graph mining for structural patterns is a fundamental task in many applications. Compilation-based graph mining systems, represented by AutoMine, generate specialized algorithms for the provided patterns and substantially outperform other systems. However, the generated code causes substantial computation redundancy and the compilation process incurs too much overhead to be used online, both due to the inherent symmetry in the structural patterns. In this paper, we propose an optimizing compiler, GraphZero, to completely address these limitations through symmetry breaking based on group theory. GraphZero implements three novel techniques. First, its schedule explorer efficiently prunes the schedule space without missing any high-performance schedule. Second, it automatically generates and enforces a set of restrictions to eliminate computation redundancy. Third, it generalizes orientation, a surprisingly effective optimization that was mainly used for clique patterns, to apply to arbitrary patterns. Evaluated on multiple graph mining applications and complex patterns with 7 real-world graph datasets, GraphZero demonstrates up to 40X performance improvement and up to 197X reduction on schedule generation overhead over AutoMine.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Mayura: Exploiting Similarities in Motifs for Temporal Co-Mining

    cs.DB 2025-07 conditional novelty 6.0 of 10

    Mayura introduces the MG-Tree, a hierarchical prefix tree over temporal motifs, enabling exact co-mining of multiple motifs with 1.7-2.4x average speedups on GPU/CPU.

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