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PPoPP2025顶会

LibRTS: A Spatial Indexing Library by Ray Tracing

Liang Geng, Rubao Lee, Xiaodong Zhang

2025年份
11被引次数
2顶会引用

摘要

The Ray-Tracing (RT) core has become a widely integrated feature in modern GPUs to accelerate ray-tracing rendering. Recent research has shown that RT cores can also be repurposed to accelerate non-rendering workloads. Since the RT core essentially serves as a hardware accelerator for Bounding Volume Hierarchy (BVH) tree traversal, it holds the potential to significantly improve the performance of spatial workloads. However, the specialized RT programming model poses challenges for using RT cores in these scenarios. Inspired by the core functionality of RT cores, we designed and implemented LibRTS, a spatial index library that leverages RT cores to accelerate spatial queries. LibRTS supports both point and range queries and remains mutable to accommodate changing data. Instead of relying on a case-by-case approach, LibRTS provides a general, highperformance spatial indexing framework for spatial data processing. By formulating spatial queries as RT-suitable problems and overcoming load-balancing challenges, LibRTS delivers superior query performance through RT cores without requiring developers to master complex programming on this specialized hardware. Compared to CPU and GPU spatial libraries, LibRTS achieves speedups of up to 85.1x for point queries, 94.0x for range-contains queries, and 11.0x for range-intersects queries. In a real-world application, pointin-polygon testing, LibRTS also surpasses the state-of-the-art RT method by up to 3.8x.

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