Soft NMR: exploiting statistics for energy-efficiency

Authors:
Eric P. Kim;Rami A. Abdallah;Naresh R. Shanbhag
Affiliations:
Coordinated Science Laboratory, Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois;Coordinated Science Laboratory, Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois;Coordinated Science Laboratory, Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois
Venue:
SOC'09 Proceedings of the 11th international conference on System-on-chip
Year:
2009

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Abstract

Achieving energy-efficiency in nanoscale CMOS process technologies is made challenging due to the presence of process, temperature and voltage variations. In this paper, we present soft N-modular redundancy (soft NMR) that consciously exploits statistics of errors due to these nanoscale artifacts in order to design robust and energy-efficient systems. In contrast to conventional NMR, soft NMR employs estimation and detection techniques in the voter. We compare NMR and soft NMR in the design of an energy-efficient and robust discrete cosine transform (DCT) image coder. Simulations in a commercial 45nm, 1.2V, CMOS process show that soft triple-MR (TMR) provides 10× improvement in robustness and 13% power savings over TMR at a peak signal-to-noise ratio (PSNR) of 20dB. In addition, soft dual-MR (DMR) provides 2× improvement in robustness and 35 % power savings over TMR at a PSNR of 20dB.