Convex Hull 3D Filtering with GPU Ray Tracing and Tensor Cores

Abstract

In recent years, applications such as real-time simulations, autonomous systems, and video games increasingly demand the processing of complex geometric models under stringent time constraints. Traditional geometric algorithms, including the convex hull, are subject to these challenges. This work presents a 3D preprocessing filter for the convex hull algorithm using ray tracing and tensor core technologies. The filter builds a delimiter polyhedron based on Manhattan distances that discards points from the original set. Experimental results show that the proposed filter, combined with convex hull construction, accelerates the computation of the 3D convex hull by up to 200x with respect to a CPU parallel implementation. Beyond execution time and speedup evaluation, we also analyze GPU energy consumption, showing that the proposed preprocessing filter not only reduces the computational workload but also achieves performance gains with controlled energy usage.

Roberto Carrasco

GPU filters for accelerating the convex hull

My research interests include Asados, Empanadas, and Choripanes.

Hector Ferrada

Professor at the Universidad Austral de Chile

Professor at the Universidad Austral de Chile

Cristobal A Navarro

Professor at the Universidad Austral de Chile

Professor at the Universidad Austral de Chile

Nancy Hitschfeld Kahler

+Lab founder | Full Professor Universidad de Chile

Full Professor at the Department of Computer Science, University of Chile. Her main research interests include geometric modeling, geometric meshes, and parallel algorithms (GPU computing), focused in computational science, and engineering applications.