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DTSTAMP:20260402T024532Z
LOCATION:3003\, Level 3
DTSTART;TZID=America/Los_Angeles:20250623T164500
DTEND;TZID=America/Los_Angeles:20250623T170000
UID:dac_DAC 2025_sess122_RESEARCH1034@linklings.com
SUMMARY:PairGraph: An Efficient Search-space-aware Accelerator for High-pe
 rformance Concurrent Pairwise Queries
DESCRIPTION:Yutao Fu, Zhongtian Long, Yu Zhang, Zirui He, Jin Zhao, Qiyuan
  Niu, Zixiao Wang, and Hai Jin (Huazhong University of Science and Technol
 ogy)\n\nPairwise queries have been widely used in various applications. Ho
 wever, existing methods still face challenges in handling Concurrent Pairw
 ise Queries (CPQ) due to irregular memory access and fragmented data shari
 ng. To address this, we propose PairGraph, an accelerator that identifies 
 frequently traversed graph structure data and fully reuse the data worth s
 haring to minimize off-chip communications. Experimental results show that
  PairGraph achieves 5.59×∼14.25× and 3.76×∼7.58× speedups over software sy
 stems Gemini and Gunrock, respectively. It also outperforms the cutting-ed
 ge accelerators (LCCG, ScalaGraph, and ReGraph), achieving speedups of 1.6
 7×∼2.72×, 1.93×∼4.26×, and 2.66×∼4.28×, respectively.\n\nTopics: Design\n\
 nTracks: DES3: Emerging Models of ComputatioN\n\nSession Chairs: Cheng Wan
 g (Iowa State University) and Jun Shiomi (The University of Osaka)\n\n
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