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DTSTAMP:20240626T180035Z
LOCATION:3003\, 3rd Floor
DTSTART;TZID=America/Los_Angeles:20240627T141500
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UID:dac_DAC 2024_sess117_RESEARCH520@linklings.com
SUMMARY:Accelerating Regular Path Queries over Graph Database with Process
 ing-in-Memory
DESCRIPTION:Research Manuscript\n\nRuoyan Ma, Shengan Zheng, Guifeng Wang,
  Jin Pu, and Yifan Hua (Shanghai Jiao Tong University); Wentao Wang (Pekin
 g University); and Linpeng Huang (Shanghai Jiao Tong University)\n\nRegula
 r path queries (RPQs) in graph databases are bottlenecked by the memory wa
 ll. Emerging processing-in-memory (PIM) technologies offer a promising sol
 ution to dispatch and execute path matching tasks in parallel within PIM m
 odules. We present Moctopus, a PIM-based data management system for graph 
 databases that supports efficient batch RPQs and graph updates. Moctopus e
 mploys a PIM-friendly dynamic graph partitioning algorithm, which tackles 
 graph skewness and preserves graph locality with low overhead for RPQ proc
 essing. Moctopus enables efficient graph updates by amortizing the host CP
 U's update overhead to PIM modules. Evaluation of Moctopus demonstrates su
 periority over the state-of-the-art traditional graph database.\n\nTopic: 
 Design\n\nKeyword: In-memory and Near-memory Computing Circuits\n\nSession
  Chair: Shubham Jain (IBM Thomas J. Watson Research Center)
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