Publication:
Online Nbti Wear-out Estimation

dc.contributor.advisorWayne P. Burleson
dc.contributor.authorDabhoiwala, Mehernosh H
dc.contributor.departmentUniversity of Massachusetts Amherst
dc.contributor.departmentElectrical & Computer Engineering
dc.date2023-09-23T08:14:44.000
dc.date.accessioned2024-04-26T20:37:13Z
dc.date.available2013-08-22T00:00:00Z
dc.date.issued2013-01-01
dc.date.submittedSeptember
dc.description.abstractCMOS feature size scaling has been a source of dramatic performance gains, but it has come at a cost of on-chip wear-out. Negative Bias Temperature Instability (NBTI) is one of the main on-chip wear-out problems which questions the reliability of a chip. To check the accuracy of Reaction-Diffusion (RD) model, this work first proposes to compare the NBTI wear-out data from the RD wear-out model and the reliability simulator - Ultrasim RelXpert, by monitoring the activity of the register file on a Leon3 processor. The simulator wear-out data obtained is considered to be the baseline data and is used to tune the RD model using a novel technique time slicing. It turns out that the tuned RD model NBTI degradation is on an average 80% accurate with respect to RelXpert simulator and its calculation is approximately 8 times faster than the simulator. We come up with a waveform compression technique, for the activity waveforms from the Leon3 register file, which consumes 131KB compared to 256MB required without compression, and also provides 91% accuracy in NBTI degradation, compared to the same obtained without compression. We also propose a NBTI ΔVth estimation/prediction technique to reduce the time consumption of the tuned RD model threshold voltage calculation by an order of with one day degradation being 93% within the same of the tuned RD model. This work further proposes to a novel NBTI Degradation Predictor (NDP), to predict the future NBTI degradation, in a DE2 FPGA for WCET benchmarks. Also we measure the ΔVth variation across the 4 corners of the DE2 FPGA running a single Leon3, which varies from 0.08% to 0.11% of the base Vth.
dc.description.degreeMaster of Science in Electrical and Computer Engineering (M.S.E.C.E.)
dc.identifier.doihttps://doi.org/10.7275/4487941
dc.identifier.urihttps://hdl.handle.net/20.500.14394/44554
dc.relation.urlhttps://scholarworks.umass.edu/cgi/viewcontent.cgi?article=2258&context=theses&unstamped=1
dc.source.statuspublished
dc.subjectOnline NBTI wear-out estimation
dc.subjectComputer Engineering
dc.subjectElectrical and Computer Engineering
dc.titleOnline Nbti Wear-out Estimation
dc.typeopen
dc.typearticle
dc.typethesis
digcom.contributor.authorisAuthorOfPublication|email:mhdabhoiwala@gmail.com|institution:University of Massachusetts Amherst|Dabhoiwala, Mehernosh H
digcom.date.embargo2013-08-22T00:00:00-07:00
digcom.identifiertheses/1117
digcom.identifier.contextkey4487941
digcom.identifier.submissionpaththeses/1117
dspace.entity.typePublication
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