Files in this item

FilesDescriptionFormat

application/pdf

application/pdfKim_Eric.pdf (1MB)
(no description provided)PDF

Description

Title:Soft N-modular redundancy: exploiting statistics for robust computation
Author(s):Kim, Eric P.
Advisor(s):Shanbhag, Naresh R.
Contributor(s):Shanbhag, Naresh R.
Department / Program:Electrical & Computer Eng
Discipline:Electrical & Computer Engr
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:M.S.
Genre:Thesis
Subject(s):fault tolerance
low power
algorithmic technique
signal processing
N-modular redundancy
Abstract:Achieving energy-efficiency in nanoscale CMOS process technologies is made challenging due to the presence of process, temperature and voltage variations. In this thesis, we present soft N-modular redundancy (soft NMR) that 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. Analysis of soft NMR, NMR and ANT is given to facilitate future design of systems employing such robust techniques. We also compare NMR and soft NMR in the design of an energy-e cient and robust discrete cosine transform (DCT) image coder. Simulations in a commercial 45 nm, 1:2 V, CMOS process show that soft triple-MR (TMR) provides 10 improvement in robustness and 13% power savings over TMR at the same peak signal-to-noise ratio (PSNR) of 20 dB. In addition, soft dual-MR (DMR) provides a 2x improvement in robustness and a 35% power savings over TMR at the same PSNR of 20 dB. An FPGA implementation of the 2-D DCT showed that hardware emulation results match the RTL simulations.
Issue Date:2010-01-06
URI:http://hdl.handle.net/2142/14721
Rights Information:Copyright 2009 Eric P. Kim
Date Available in IDEALS:2010-01-06
2012-01-07
Date Deposited:December 2


This item appears in the following Collection(s)

Item Statistics