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PRODID:Linklings LLC
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TZID:Asia/Tokyo
X-LIC-LOCATION:Asia/Tokyo
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TZOFFSETFROM:+0900
TZOFFSETTO:+0900
TZNAME:JST
DTSTART:18871231T000000
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BEGIN:VEVENT
DTSTAMP:20260817T171533Z
LOCATION:Hall B7 (1)\, B Block\, Level 7
DTSTART;TZID=Asia/Tokyo:20241205T094600
DTEND;TZID=Asia/Tokyo:20241205T095800
UID:siggraphasia_SIGGRAPH Asia 2024_sess126_papers_526@linklings.com
SUMMARY:gDist: Efficient Distance Computation between 3D Meshes on GPU
DESCRIPTION:Peng Fan, Wei Wang, and Ruofeng Tong (Zhejiang University); Ha
 ilong Li (Poisson Soft); and Min Tang (Zhejiang University, Zhejiang Sci-T
 ech University)\n\nComputing maximum/minimum distances between 3D meshes i
 s crucial for various applications, i.e., robotics, CAD, VR/AR, etc. In th
 is work, we introduce a highly parallel algorithm (gDist) optimized for Gr
 aphics Processing Units (GPUs), which is capable of computing the distance
  between two meshes with over 15 million triangles in less than 0.4 millis
 econds. By testing on benchmarks with varying characteristics, the algorit
 hm achieves remarkable speedups over prior CPU-based and GPU-based algorit
 hms on a commodity GPU (NVIDIA GeForce RTX 4090). Notably, the algorithm c
 onsistently maintains high-speed performance, even in challenging scenario
 s that pose difficulties for prior algorithms.\n\nRegistration Category: F
 ull Access, Full Access Supporter\n\nLanguage Format: English Language\n\n
 Session Chair: Paul Kry (McGill University)\n\n
URL:https://asia.siggraph.org/2024/program/?id=papers_526&sess=sess126
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