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GPU-Optimized BVH and R-Triangle Methods for Rapid Self-Intersection Handling in Fabrics

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2024, 29(8), pp.59-65
  • DOI : 10.9708/jksci.2024.29.08.059
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : July 8, 2024
  • Accepted : August 9, 2024
  • Published : August 30, 2024

Jong-Hyun Kim 1

1인하대학교

Accredited

ABSTRACT

In this paper, we present a GPU-based acceleration of computationally intensive self-collision processing in triangular mesh-based cloth simulation. For Compute Unified Device Architecture (CUDA)-based parallel optimization, we propose 1) an efficient way to build, update, and traverse the Bounding Volume Hierarchy (BVH) tree on the GPU, and 2) optimize the Representative-Triangle (R-Triangle) technique on the GPU to minimize primitive collision checking in triangular mesh-based cloth simulations. As a result, the proposed method can handle self-collisions and object collisions of cloth simulation in GPU environment faster and more efficiently than CPU-based algorithms, and experiments on various scenes show that it can achieve simulation results that are 5x to 10x faster. Since the proposed method is optimized for BVH on GPU, it can be easily integrated into various algorithms and fields that utilize BVH.

Citation status

* References for papers published after 2023 are currently being built.

This paper was written with support from the National Research Foundation of Korea.