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Concurrent FFT computing on multicore processors
Author(s) -
Barhen J.,
Humble T.,
Mitra P.,
Imam N.,
Schleck B.,
Kotas C.,
Traweek M.
Publication year - 2012
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.1746
Subject(s) - fast fourier transform , computer science , simd , reconfigurability , multi core processor , parallel computing , ibm , throughput , vectorization (mathematics) , split radix fft algorithm , power (physics) , scheme (mathematics) , computer architecture , fourier transform , algorithm , operating system , wireless , fourier analysis , mathematical analysis , materials science , physics , mathematics , short time fourier transform , quantum mechanics , nanotechnology
SUMMARY The emergence of streaming multicore processors with multi‐SIMD (single‐instruction multiple‐data) architectures and ultra‐low power operation combined with real‐time compute and I/O reconfigurability opens unprecedented opportunities for executing sophisticated signal processing algorithms faster and within a much lower energy budget. Here, we present an unconventional Fast Fourier Transform (FFT) implementation scheme for the IBM Cell, named transverse vectorization . It is shown to outperform (both in terms of timing and GFLOP throughput) the fastest FFT results reported to date for the Cell in the open literature. We also provide the first results for multi‐FFT implementation and application on the novel, ultra‐low power Coherent Logix HyperX processor. Copyright © 2011 John Wiley & Sons, Ltd.