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DTSTART:19700308T020000
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BEGIN:VEVENT
DTSTAMP:20260402T024534Z
LOCATION:Level 2 Lobby
DTSTART;TZID=America/Los_Angeles:20250623T180000
DTEND;TZID=America/Los_Angeles:20250623T190000
UID:dac_DAC 2025_sess287_LBR116@linklings.com
SUMMARY:Late Breaking Results: A Fast Nearest Neighbor Search Acceleration
  for 3D Point Cloud
DESCRIPTION:Jinao Li, Teng Wang, Qianyu Cheng, Zhendong Zheng, Lei Gong, C
 hao Wang, Xi Li, and Xuehai Zhou (University of Science and Technology of 
 China)\n\nThis paper presents FastNN, a novel accelerator architecture for
  efficient K-Nearest Neighbors (KNN) search in point clouds. FastNN levera
 ges a locality-sensitive E2LSH partitioning method and a pre-comparator mo
 dule to significantly reduce the candidate search space and minimize the n
 umber of Euclidean distance calculations. Compared to octree-based partiti
 oning methods, our approach reduces candidate points by 58.57% to 86.17% a
 nd achieves a 10.04× acceleration in processing throughput relative to the
  BitNN comparator subsystem. The proposed design effectively enhances sear
 ch throughput, resource utilization, and precision, highlighting its poten
 tial for accelerating KNN search on FPGA platforms.\n\n
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