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Scan primitives for GPU computing

Shubhabrata Sengupta, Mark Harris, Yao Zhang, John D. Owens
University of California, Davis
In GH ’07: Proceedings of the 22nd ACM SIGGRAPH/EUROGRAPHICS symposium on Graphics hardware (2007), pp. 97-106.

@conference{sengupta2007scan,

   title={Scan primitives for GPU computing},

   author={Sengupta, S. and Harris, M. and Zhang, Y. and Owens, J.D.},

   booktitle={Proceedings of the 22nd ACM SIGGRAPH/EUROGRAPHICS symposium on Graphics hardware},

   pages={97–106},

   year={2007},

   organization={Eurographics Association}

}

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The scan primitives are powerful, general-purpose data-parallel primitives that are building blocks for a broad range of applications. We describe GPU implementations of these primitives, specifically an efficient formulation and implementation of segmented scan , on NVIDIA GPUs using the CUDA API. Using the scan primitives, we show novel GPU implementations of quicksort and sparse matrix-vector multiply, and analyze the performance of the scan primitives, several sort algorithms that use the scan primitives, and a graphical shallow-water fluid simulation using the scan framework for a tridiagonal matrix solver.
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