A generalized GPU-based connected component labeling algorithm

TL;DR

This paper introduces a versatile GPU-based connected component labeling algorithm applicable to various lattice and non-lattice environments, demonstrating its effectiveness through bond percolation problems on multiple lattice types.

Contribution

The paper presents a generalized GPU-based CCL algorithm that extends previous methods without iteration, applicable to diverse lattice structures and environments.

Findings

Successfully applied to honeycomb and triangle lattices

Confirmed correctness through bond percolation analysis

Demonstrated performance on Bethe lattice

Abstract

We propose a generalized GPU-based connected component labeling (CCL) algorithm that can be applied to both various lattices and to non-lattice environments in a uniform fashion. We extend our recent GPU-based CCL algorithm without the use of conventional iteration to the generalized method. As an application of this algorithm, we deal with the bond percolation problem. We investigate bond percolation on the honeycomb and triangle lattices to confirm the correctness of this algorithm. Moreover, we deal with bond percolation on the Bethe lattice as a substitute for a network structure, and demonstrate the performance of this algorithm on those lattices.