Accelerating Fast Fourier Transform for Wideband Channelization

Carlo del Mundo, Vignesh Adhinarayanan, Wu-chun Feng
Department of Electrical & Computer Engineering
IEEE International Conference on Communications (ICC), 2013

   title={Accelerating Fast Fourier Transform for Wideband Channelization},

   author={del Mundo, Carlo and Adhinarayanan, Vignesh and Feng, Wu-chun},



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Wideband channelization is a compute-intensive task with performance requirements that are arguably greater than what current multi-core CPUs can provide. To date, researchers have used dedicated hardware such as field programmable gate arrays (FPGAs) to address the performancecritical aspects of the channelizer. In this work, we assess the viability of the graphics processing unit (GPU) to achieve the necessary performance. In particular, we focus on the fast Fourier Transform (FFT) stage of a wideband channelizer. While there exists previous work for FFT on a NVIDIA GPU, the substantially higher peak floating-point performance of an AMD GPU has been less explored. Thus, we consider three generations of AMD GPUs and provide insight into the optimization of FFT on these platforms. Our architecture-aware approach across three different generations of AMD GPUs outperforms a multithreaded Intel Sandy Bridge CPU with vector extensions by factors of 4.3, 4.9, and 6.6 on the Radeon HD 5870, 6970, and 7970, respectively.
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