GPU Based Detection of Topological Changes in Voronoi Diagrams

TL;DR

This paper introduces a GPU-accelerated method for detecting topological changes in dynamic Voronoi diagrams, enabling efficient analysis of evolving spatial partitions in simulations.

Contribution

The paper presents a novel CUDA-based procedure for real-time detection of topological changes in moving Voronoi diagrams, applicable to complex physical simulations.

Findings

Efficient GPU implementation for topological change detection

Application to soft-glassy material simulations

Preliminary physics results demonstrating method effectiveness

Abstract

The Voronoi diagrams are an important tool having theoretical and practical applications in a large number of fields. We present a new procedure, implemented as a set of CUDA kernels, which detects, in a general and efficient way, topological changes in case of dynamic Voronoi diagrams whose generating points move in time. The solution that we provide has been originally developed to identify plastic events during simulations of soft-glassy materials based on a Lattice Boltzmann model with frustrated-short range attractive and mid/long-range repulsive-interactions. Along with the description of our approach, we present also some preliminary physics results.