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GPU Parallel Implementation of the Approximate K-SVD Algorithm Using OpenCL

Paul Irofti, Bogdan Dumitrescu
Department of Automatic Control and Computers, University Politehnica of Bucharest, 313 Spl. Independentei, 060042 Bucharest, Romania
22nd European Signal Processing Conference, 2014

@article{irofti2014gpu,

   title={GPU Parallel Implementation of the Approximate K-SVD Algorithm Using OpenCL},

   author={Irofti, Paul and Dumitrescu, Bogdan},

   year={2014}

}

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Training dictionaries for sparse representations is a time consuming task, due to the large size of the data involved and to the complexity of the training algorithms. We investigate a parallel version of the approximate K-SVD algorithm, where multiple atoms are updated simultaneously, and implement it using OpenCL, for execution on graphics processing units (GPU). This not only allows reducing the execution time with respect to the standard sequential version, but also gives dictionaries with which the training data are better approximated. We present numerical evidence supporting this somewhat surprising conclusion and discuss in detail several implementation choices and difficulties.
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