Abstract
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].
Original language | English (US) |
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Article number | 6374775 |
Pages (from-to) | 83-91 |
Number of pages | 9 |
Journal | Proceedings - Symposium on Computer Architecture and High Performance Computing |
DOIs | |
State | Published - Dec 1 2012 |
Event | 24th International Symposium on Computer Architecture and High Performance Computing, SBAC-PAD 2012 - New York, NY, United States Duration: Oct 24 2012 → Oct 26 2012 |
Keywords
- GPUs
- Multi-core CPUs
- Sparse FFT
- performance speedup