Discrete Collision Detection (DCD) is a fundamental task in several domains including particle-based physics simulations. Efficient DCD uses indexing structures such as Bounding Volume Hierarchy (BVH), but accelerating irregular BVH traversals demands meticulous efforts to achieve performance. Modern GPUs feature Ray Tracing (RT) architecture that provides hardware acceleration for BVH traversal and optimized drivers for BVH construction. Recent work has attempted to exploit RT architecture to accelerate DCD on spherical particles by reducing DCD to fixed-radius neighbor search. However, this reduction breaks down for particles with different radii, necessitating the use of large bounding boxes that result in a higher number of duplicate collisions and poor performance. To address these limitations, we present Mochi, a new reduction that reformulates DCD on RT architecture by exploiting the symmetry of collision relations to support both uniform and non-uniform spherical particles efficiently. Mochi introduces per-object proxy spheres that decouple BVH bounding volumes from the collision search radius, enabling significantly tighter bounding boxes without sacrificing correctness. Mochi is provably sound and guarantees that all true collisions are detected. We integrate Mochi into an end-to-end particle simulation pipeline and evaluate it across large-scale particle workloads, showing consistent speedups over state-of-the-art BVH-based and RT-based DCD implementations. Mochi generalizes prior RT-based neighbor search formulations while avoiding their fundamental limitations for non-uniform spheres.

翻译：离散碰撞检测（DCD）是粒子物理模拟等多个领域中的基础任务。高效的DCD依赖于包围体层次结构（BVH）等索引结构，但加速不规则的BVH遍历需要精细的设计才能实现高性能。现代GPU采用光线追踪（RT）架构，提供硬件加速的BVH遍历和优化的BVH构建驱动程序。近期研究尝试利用RT架构加速球形粒子的DCD，将其简化为固定半径邻域搜索。然而，这种简化在粒子半径不同时会失效，需使用较大的包围盒，导致重复碰撞数量增加与性能下降。为解决这些局限，我们提出Mochi——一种基于RT架构的新型归约方法，通过利用碰撞关系的对称性，统一高效地支持均匀与非均匀球形粒子。Mochi引入每个对象的代理球体，将BVH包围体积与碰撞搜索半径解耦，在不牺牲正确性的前提下实现更紧凑的包围盒。该方法在理论上可靠，保证能检测所有真实碰撞。我们将Mochi集成到端到端粒子模拟流水线中，在大规模粒子负载上进行评估，结果表明其相比基于BVH和RT的先进DCD实现均实现稳定加速。Mochi泛化了现有基于RT的邻域搜索公式，同时避免了其在非均匀球体场景中的根本性局限。