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Obtaining a 35x Speedup in 2D Phase Unwrapping Using Commodity Graphics Processors

Peter A. Karasev, Daniel P. Campbell, Mark A. Richards
School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0765 USA
IEEE Radar Conference, 2007

@inproceedings{karasev2007obtaining,

   title={Obtaining a 35x speedup in 2d phase unwrapping using commodity graphics processors},

   author={Karasev, P.A. and Campbell, D.P. and Richards, M.A.},

   booktitle={Radar Conference, 2007 IEEE},

   pages={574–578},

   year={2007},

   organization={IEEE}

}

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Graphics processing units (GPUs) are a powerful tool for numerical computation. The GPU architecture and computational model are uniquely designed for high-resolution high-speed grid-based calculations. This capability can be utilized to accelerate certain classes of compute-intensive radar signal processing algorithms. Characteristics of a problem well-suited for computation on a GPU include high levels of data parallelism, low control logic, uniform boundary conditions, and well-defined input and output. We describe the implementation of two-dimensional multigrid least-squares weighted phase unwrapping on a GPU and demonstrate a large speedup over C and MATLAB implementations. Details of the GPU computation are provided. Background information on the GPU architecture and its applicability to general-purpose computation is discussed.
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