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Document Type

Open Access

Degree Program

Electrical & Computer Engineering

Degree Type

Master of Science in Electrical and Computer Engineering (M.S.E.C.E.)

Year Degree Awarded

2013

Month Degree Awarded

September

Keywords

Online NBTI wear-out estimation

Abstract

CMOS 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.

First Advisor

Wayne P. Burleson

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