Energy-Quality Scalable Design Space Exploration of Approximate FFT Hardware Architectures

This paper presents a comprehensive design space exploration for boosting energy efficiency of a fast Fourier transform (FFT) VLSI accelerator, exploiting several approximate multipliers (AxM) combined with approximate adder (AxA) circuits. The FFT hardware herein presented consists of a fixed-point...

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Bibliographic Details
Published in:IEEE transactions on circuits and systems. I, Regular papers Regular papers, 2022-11, Vol.69 (11), p.4524-4534
Main Authors: Pereira, Pedro Taua Lopes, Costa, Patricia Ucker Leleu da, Ferreira, Guilherme da Costa, Abreu, Brunno Alves de, Paim, Guilherme, Costa, Eduardo Antonio Cesar da, Bampi, Sergio
Format: Article
Language:English
Subjects:
Adders
Adding circuits
approximate adders
Approximation
Approximation algorithms
Arithmetic
Computer architecture
Configuration management
Controllability
Discrete Fourier transforms
Energy dissipation
Energy efficiency
Fast Fourier transformations
FFT
Fixed point arithmetic
Fixed points (mathematics)
Fourier transforms
Hardware
Integrated circuits
Mathematical analysis
Multipliers
radix-2 butterflies
Signal processing
Signal to noise ratio
Space exploration
Spectrograms
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Summary:This paper presents a comprehensive design space exploration for boosting energy efficiency of a fast Fourier transform (FFT) VLSI accelerator, exploiting several approximate multipliers (AxM) combined with approximate adder (AxA) circuits. The FFT hardware herein presented consists of a fixed-point sequential architecture using a radix-2 butterfly with decimation in time. We explore a set of AxMs - namely Dynamic Range Unbiased (DRUM), Rounding-based Approximate (RoBA), leading one Bit-based Approximate (LoBA), and Truncated approach - jointly with the LOA, ETA-I, CopyA, CopyB, Trunc0, Trunc1 approximate adders. The approximate arithmetic operators are used in the butterfly kernel with exploration of the approximation levels (for the {L} and {K} least-significant bits, respectively, for the AxM and AxA), aiming at discovering the most energy-efficient configuration under a design-time QoR constraint. The mean square error and peak signal-to-noise ratio metrics define which approximate levels combining {L} and {K} variations will enable the FFT to process signals to generate spectrograms without significant losses. Our results show that the LoBA multiplier with L =8 together with the LOA, Trunc1 and Trunc0, at different approximation levels, provide most energy savings with controllable quality degradation, presenting a minimum decrease of 20.2% in power dissipation without degrading the spectrogram generation quality.
ISSN:1549-8328
1558-0806
DOI:10.1109/TCSI.2022.3191180