Parallel Spectral Graph Partitioning on CUDA
Department of Computer Engineering, Middle East Technical University
GPU Technology Conference (GTC), 2012
@article{firat2012parallel,
title={Parallel Spectral Graph Partitioning on CUDA},
author={F{i}rat, Orhan and Temizel, Alptekin},
year={2012}
}
Parallelization of scientific problems is a challenging task which has a wide application area both on distributed programming, cloud computing and recently on GPGPU. Spectral graph partitioning is a widely used technique in many fields such as image processing, scientific computing, machine learning etc. In this study we analyze spectral graph partitioning subroutines on a GPGPU framework. Each step is analyzed with differing techniques to lead a conclusion about usage of GPGPU on overall spectral graph partitioning algorithms.
February 23, 2014 by hgpu
