DocumentCode :
2089788
Title :
Accelerating fast Fourier Transform for wideband channelization
Author :
del Mundo, Carlo ; Adhinarayanan, Vignesh ; Wu-Chun Feng
Author_Institution :
Dept. of Electr. & Comput. Eng., Virginia Tech, Blacksburg, VA, USA
fYear :
2013
fDate :
9-13 June 2013
Firstpage :
4776
Lastpage :
4780
Abstract :
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 performance-critical 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.
Keywords :
fast Fourier transforms; graphics processing units; multiprocessing systems; AMD GPU; FFT; FPGA; NVIDIA GPU; architecture-aware approach; fast Fourier transform; field programmable gate arrays; graphics processing unit; multicore CPU; wideband channelization; Acceleration; Graphics processing units; High definition video; Kernel; Optimization; Vectors; Wideband;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications (ICC), 2013 IEEE International Conference on
Conference_Location :
Budapest
ISSN :
1550-3607
Type :
conf
DOI :
10.1109/ICC.2013.6655329
Filename :
6655329
Link To Document :
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