Parallel Spectral Graph Partitioning on CUDA

Orhan Firat, Alptekin Temizel
Department of Computer Engineering, Middle East Technical University
GPU Technology Conference (GTC), 2012


   title={Parallel Spectral Graph Partitioning on CUDA},

   author={F{i}rat, Orhan and Temizel, Alptekin},



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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.
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