Parallel Graph Component Labelling with GPUs and CUDA

K. A. Hawick, A. Leist, D. P. Playne
Institute of Information and Mathematical Sciences, Massey University – Albany, North Shore 102-904, Auckland, New Zealand
Parallel Computing, Volume 36, Issue 12, December 2010, Pages 655-678 (10 August 2010)


   title={Parallel graph component labelling with gpus and cuda},

   author={Hawick, KA and Leist, A. and Playne, DP},

   journal={Parallel Computing},





Download Download (PDF)   View View   Source Source   



Graph component labelling, which is a subset of the general graph colouring problem, is a computationally expensive operation that is of importance in many applications and simulations. A number of data-parallel algorithmic variations to the component labelling problem are possible and we explore their use with general purpose graphical processing units (GPGPUs) and with the CUDA GPU programming language. We discuss implementation issues and performance results on GPUs using CUDA. We present results for regular mesh graphs as well as arbitrary structured and topical graphs such as small-world and scale-free structures. We show how different algorithmic variations can be used to best effect depending upon the cluster structure of the graph being labelled and consider how features of the GPU architectures and host CPUs can be combined to best effect into a cluster component labelling algorithm for use in high performance simulations.
No votes yet.
Please wait...

* * *

* * *

HGPU group © 2010-2020 hgpu.org

All rights belong to the respective authors

Contact us: