@inproceedings{4dd00c94e0b54a24ab95d33abe681c98,
title = "Soft NMR: Analysis & application to DSP systems",
abstract = "We have recently proposed the concept of soft N-modular redundancy (soft NMR) [1] in order to design robust and energy-efficient computing systems in nanoscale processes, where soft NMR was shown to achieve orders-of-magnitude improvement in robustness with significant power savings over NMR. In this paper, we analyze the performance of soft NMR and compare it with that of NMR and algorithmic noise-tolerance (ANT). An 8-b multiplier and a DCT-based still image compression system in a commercial 45nm CMOS process is considered. Two metrics of system performance: system reliability Pe,sys, and signal-to-noise ratio (SNR) are analyzed. We show that soft NMR always outperforms NMR and that our analysis predicts Pe,sys and SNR to within 4.2% and 2.7dB on average, respectively, of the results of Monte Carlo simulations.",
keywords = "CMOS digital integrated circuits, Image processing, MAP estimation, Nanotechnology, Robustness",
author = "Kim, {Eric P.} and Shanbhag, {Naresh R.}",
year = "2010",
doi = "10.1109/ICASSP.2010.5495498",
language = "English (US)",
isbn = "9781424442966",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1494--1497",
booktitle = "2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Proceedings",
address = "United States",
note = "2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 ; Conference date: 14-03-2010 Through 19-03-2010",
}