RTNN: Accelerating Neighbor Search Using Hardware Ray Tracing

[Submitted on 4 Jan 2022 (v1), last revised 9 Mar 2022 (this version, v2)]

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Abstract:Neighbor search is of fundamental important to many engineering and science fields such as physics simulation and computer graphics. This paper proposes to formulate neighbor search as a ray tracing problem and leverage the dedicated ray tracing hardware in recent GPUs for acceleration. We show that a naive mapping under-exploits the ray tracing hardware. We propose two performance optimizations, query scheduling and query partitioning, to tame the inefficiencies. Experimental results show 2.2X -- 65.0X speedups over existing neighbor search libraries on GPUs. The code is available at this https URL.