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Parametric Flows: Automated Behavior Equivalencing for Symbolic Analysis of Races in CUDA Programs

Peng Li, Guodong Li, Ganesh Gopalakrishnan
School of Computing, University of Utah
ACM/IEEE Conference on Supercomputing (SC’12), 2012

@article{li2012parametric,

   title={Parametric Flows: Automated Behavior Equivalencing for Symbolic Analysis of Races in CUDA Programs},

   author={Li, P. and Li, G. and Gopalakrishnan, G.},

   year={2012}

}

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The growing scale of concurrency requires automated abstraction techniques to cut down the effort in concurrent system analysis. In this paper, we show that the high degree of behavioral symmetry present in GPU programs allows CUDA race detection to be dramatically simplified through abstraction. Our abstraction techniques is one of automatically creating parametric flows
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