Implementation of a Fast Fourier transform algorithm onto a manycore processor

The Fourier transform is the main processing step applied to data collected from the Square Kilometre Array (SKA) receivers. The requirement is to compute a Fourier transform of 219 real byte samples in real-time, while minimizing the power consumption. We address this challenge by optimizing a FFT...

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Bibliographic Details
Published in2015 Conference on Design and Architectures for Signal and Image Processing (DASIP) pp. 1 - 7
Main Authors Hascoet, Julien, Nezan, Jean-Francois, Ensor, Andrew, de Dinechin, Benoit Dupont
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2015
Subjects
Arrays
Fast Fourier Transform (FFT)
Fast Fourier transforms
Fixed-Point Arithmetic
Many-Core Processor
Network-On-Chip
Parallel processing
Parallel Programming
Receivers
Signal processing algorithms
Square Kilometer Array (SKA)
VLIW
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Summary:The Fourier transform is the main processing step applied to data collected from the Square Kilometre Array (SKA) receivers. The requirement is to compute a Fourier transform of 219 real byte samples in real-time, while minimizing the power consumption. We address this challenge by optimizing a FFT implementation for execution on the Kalray MPPA manycore processor. Although this processor delivers high floating-point performances, we use fixed-point number representations in order to reduce the memory consumption and the I/O bandwidth. The result is an execution time of 1,07ms per FFT, including data transfers. This enables to use only two first-generation MPPA chips per flow of data coming from the receivers, for a total power consumption of 17.4W.
DOI:10.1109/DASIP.2015.7367270