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Implementing Adaptive Voltage Over-Scaling: Algorithmic Noise Tolerance vs. Approximate Error Detection

Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
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J. Low Power Electron. Appl. 2019, 9(2), 17; https://doi.org/10.3390/jlpea9020017
Received: 9 March 2019 / Revised: 12 April 2019 / Accepted: 16 April 2019 / Published: 21 April 2019
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Abstract

Adaptive Voltage Over-Scaling can be applied at run-time to reach the best tradeoff between quality of results and energy consumption. This strategy encompasses the concept of timing speculation through some level of approximation. How and on which part of the circuit to implement such approximation is an open issue. This work introduces a quantitative comparison between two complementary strategies: Algorithmic Noise Tolerance and Approximate Error Detection. The first implements a timing speculation by means approximate computing, while the latter exploits a more sophisticated approach that is based on the approximation of the error detection mechanism. The aim of this study was to provide both a qualitative and quantitative analysis on two real-life digital circuits mapped onto a state-of-the-art 28-nm CMOS technology. View Full-Text
Keywords: voltage scaling; energy efficiency; approximate circuit; error resilient applications; algorithm noise tolerance; reduced precision redundancy; approximate error detection correction voltage scaling; energy efficiency; approximate circuit; error resilient applications; algorithm noise tolerance; reduced precision redundancy; approximate error detection correction
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Rizzo, R.G.; Calimera, A. Implementing Adaptive Voltage Over-Scaling: Algorithmic Noise Tolerance vs. Approximate Error Detection. J. Low Power Electron. Appl. 2019, 9, 17.

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