Soft NMR: Analysis & application to DSP systems

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 DCTbased 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.