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Accelerating Regular Path Queries over Graph Database with Processing-in-Memory
DescriptionRegular path queries (RPQs) in graph databases are bottlenecked by the memory wall. Emerging processing-in-memory (PIM) technologies offer a promising solution to dispatch and execute path matching tasks in parallel within PIM modules. We present Moctopus, a PIM-based data management system for graph databases that supports efficient batch RPQs and graph updates. Moctopus employs a PIM-friendly dynamic graph partitioning algorithm, which tackles graph skewness and preserves graph locality with low overhead for RPQ processing. Moctopus enables efficient graph updates by amortizing the host CPU's update overhead to PIM modules. Evaluation of Moctopus demonstrates superiority over the state-of-the-art traditional graph database.
Event Type
Research Manuscript
TimeThursday, June 272:15pm - 2:30pm PDT
Location3003, 3rd Floor
Topics
Design
Keywords
In-memory and Near-memory Computing Circuits