Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
169 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
45 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Mochi: Fast \& Exact Collision Detection (2402.14801v1)

Published 22 Feb 2024 in cs.GR

Abstract: Collision Detection (CD) has several applications across the domains such as robotics, visual graphics, and fluid mechanics. Finding exact collisions between the objects in the scene is quite computationally intensive. To quickly filter the object pairs that do not result in a collision, bounding boxes are built on the objects, indexed using a Bounding Volume Hierarchy(BVH), and tested for intersection before performing the expensive object-object intersection tests. In state-of-the-art CD libraries, accelerators such as GPUs are used to accelerate BVH traversal by building specialized data structures. The recent addition of ray tracing architecture to GPU hardware is designed to do the same but in the context of implementing a Ray Tracing algorithm to render a graphical scene in real-time. We present Mochi, a fast and exact collision detection engine that accelerates both the broad and narrow phases by taking advantage of the capabilities of Ray Tracing cores. We introduce multiple new reductions to perform generic CD to support three types of objects for CD: simple spherical particles, objects describable by mathematical equations, and complex objects composed of a triangle mesh. By implementing our reductions, Mochi achieves several orders of magnitude speedups on synthetic datasets and 5x-28x speedups on real-world triangle mesh datasets. We further evaluate our reductions thoroughly and provide several architectural insights on the ray tracing cores that are otherwise unknown due to their proprietorship.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (24)
  1. AMD: Amd ray tracing, 2023. URL: https://www.amd.com/en/technologies/rdna.
  2. Breuer M., Almohammed N.: Modeling and simulation of particle agglomeration in turbulent flows using a hard-sphere model with deterministic collision detection and enhanced structure models. International Journal of Multiphase Flow 73 (2015), 171–206.
  3. Binary ostensibly-implicit trees for fast collision detection. In Computer Graphics Forum (2020), vol. 39, Wiley Online Library, pp. 509–521.
  4. Chakravarthy A., Ghose D.: Obstacle avoidance in a dynamic environment: A collision cone approach. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans 28, 5 (1998), 562–574.
  5. Cordier F., Magnenat-Thalmann N.: Real-time animation of dressed virtual humans. In Computer Graphics Forum (2002), vol. 21, Wiley Online Library, pp. 327–335.
  6. Coumans E.: Bullet physics simulation. In ACM SIGGRAPH 2015 Courses. 2015, p. 1.
  7. Dehnen W., Read J. I.: N-body simulations of gravitational dynamics. The European Physical Journal Plus 126 (2011), 1–28.
  8. Fast radius search exploiting ray tracing frameworks. Journal of Computer Graphics Techniques (JCGT) 10, 1 (February 2021), 25–48. URL: http://jcgt.org/published/0010/01/02/.
  9. Forum N. O. D.: Nvidia optix developer forum, 2023. URL: https://forums.developer.nvidia.com/t/ray-in-the-triangle-plane/261746.
  10. Intel: Intel ray tracing, 2023. URL: https://www.intel.com/content/www/us/en/developer/articles/guide/real-time-ray-tracing-in-games.html.
  11. gproximity: hierarchical gpu-based operations for collision and distance queries. In Computer Graphics Forum (2010), vol. 29, Wiley Online Library, pp. 419–428.
  12. Möller T.: A fast triangle-triangle intersection test. Journal of graphics tools 2, 2 (1997), 25–30.
  13. Nagarajan V., Kulkarni M.: RT-DBSCAN: accelerating DBSCAN using ray tracing hardware. CoRR abs/2303.09655 (2023). URL: https://doi.org/10.48550/arXiv.2303.09655, arXiv:2303.09655, doi:10.48550/arXiv.2303.09655.
  14. Rt-knns unbound: Using RT cores to accelerate unrestricted neighbor search. In Proceedings of the 37th International Conference on Supercomputing, ICS 2023, Orlando, FL, USA, June 21-23, 2023 (2023), Gallivan K. A., Gallopoulos E., Nikolopoulos D. S., Beivide R., (Eds.), ACM, pp. 289–300. URL: https://doi.org/10.1145/3577193.3593738, doi:10.1145/3577193.3593738.
  15. nvidia: Nvidia rt white paper, 2018. URL: https://images.nvidia.com/aem-dam/en-zz/Solutions/design-visualization/technologies/turing-architecture/NVIDIA-Turing-Architecture-Whitepaper.pdf.
  16. Owl: A node graph "wrapper" library for optix 7. URL: https://github.com/owl-project/owl.
  17. Mccd: Multi-core collision detection between deformable models using front-based decomposition. Graphical Models 72, 2 (2010), 7–23. doi:DOI:10.1016/j.gmod.2010.01.001.
  18. A fast triangle to triangle intersection test for collision detection. Computer Animation and Virtual Worlds 17, 5 (2006), 527–535.
  19. Weller R.: New geometric data structures for collision detection and haptics. Springer Science & Business Media, 2013.
  20. Efficient bvh-based collision detection scheme with ordering and restructuring. In Computer graphics forum (2018), vol. 37, Wiley Online Library, pp. 227–237.
  21. RTX Beyond Ray Tracing: Exploring the Use of Hardware Ray Tracing Cores for Tet-Mesh Point Location. In High-Performance Graphics - Short Papers (2019), Steinberger M., Foley T., (Eds.), The Eurographics Association. doi:10.2312/hpg.20191189.
  22. Yershova A., LaValle S. M.: Improving motion-planning algorithms by efficient nearest-neighbor searching. IEEE Transactions on Robotics 23, 1 (2007), 151–157.
  23. Zhu Y.: Rtnn: Accelerating neighbor search using hardware ray tracing. In Proceedings of the 27th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (New York, NY, USA, 2022), PPoPP ’22, Association for Computing Machinery, p. 76–89. URL: https://doi.org/10.1145/3503221.3508409, doi:10.1145/3503221.3508409.
  24. Accelerating force-directed graph drawing with rt cores. In 2020 IEEE Visualization Conference (VIS) (2020), pp. 96–100. doi:10.1109/VIS47514.2020.00026.
Citations (1)

Summary

We haven't generated a summary for this paper yet.

X Twitter Logo Streamline Icon: https://streamlinehq.com