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Sparse Fast Fourier Transform on GPUs and Multi-core CPUs

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5 Author(s)
Jiaxi Hu ; Dept. of Electr. & Comput. Eng., Univ. of Minnesota, Minneapolis, MN, USA ; Zhaosen Wang ; Qiyuan Qiu ; Weijun Xiao
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Given an N-point sequence, finding its k largest components in the frequency domain is a problem of great interest. This problem, which is usually referred to as a sparse Fourier Transform, was recently brought back on stage by a newly proposed algorithm called the sFFT. In this paper, we present a parallel implementation of sFFT on both multi-core CPUs and GPUs using a human voice signal as a case study. Using this example, an estimate of k for the 3dB cutoff points was conducted through concrete experiments. In addition, three optimization strategies are presented in this paper. We demonstrate that the multi-core-based sFFT achieves speedups of up to three times a single-threaded sFFT while a GPU-based version achieves up to ten times speedup. For large scale cases, the GPU-based sFFT also shows its considerable advantages, which is about 40 times speedup compared to the latest out-of-card FFT implementations [2].

Published in:

Computer Architecture and High Performance Computing (SBAC-PAD), 2012 IEEE 24th International Symposium on

Date of Conference:

24-26 Oct. 2012