Obtaining a 35x Speedup in 2D Phase Unwrapping Using Commodity Graphics Processors
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}
}
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.
July 14, 2011 by hgpu
