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Fast in-place sorting with CUDA based on bitonic sort

Hagen Peters, Ole Schulz-Hildebrandt, and Norbert Luttenberger
Research Group for Communication Systems, Department of Computer Science, Christian-Albrechts-University Kiel, Germany
Parallel Processing and Applied Mathematics, Lecture Notes in Computer Science, 2010, Volume 6067/2010, 403-410, Proceedings of the 8th international conference on Parallel processing and applied mathematics, PPAM’09: Part I
@conference{peters2009fast,

   title={Fast in-place sorting with CUDA based on bitonic sort},

   author={Peters, H. and Schulz-Hildebrandt, O. and Luttenberger, N.},

   booktitle={Proceedings of the 8th international conference on Parallel processing and applied mathematics: Part I},

   pages={403–410},

   isbn={364214389X},

   year={2009},

   organization={Springer-Verlag}

}

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State of the art graphics processors provide high processing power and furthermore, the high programmability of GPUs offered by frameworks like CUDA increases their usability as high-performance coprocessors for general-purpose computing. Sorting is well-investigated in Computer Science in general, but (because of this new field of application for GPUs) there is a demand for high-performance parallel sorting algorithms that fit to the characteristics of modern GPU-architecture. We present a high-performance in-place implementation of Batcher’s bitonic sorting networks for CUDA-enabled GPUs. We adapted bitonic sort for arbitrary input length and assigned compare/exchange-operations to threads in a way that decreases low-performance global-memory access and thereby greatly increases the performance of the implementation.
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