Please use this identifier to cite or link to this item: https://ktisis.cut.ac.cy/handle/10488/12613
Title: Minimal exercise vector generation for reliability improvement
Authors: Reddy, P. Madhukar 
Hadjitheophanousi, Stavros 
Soteriou, Vassos 
Gratz, Paul V. 
Michael, Maria K. 
Major Field of Science: Engineering and Technology
Field Category: Computer and Information Sciences
Keywords: Negative bias temperature instability;Systems analysis;Thermodynamic stability;Vectors;Failure mechanism
Issue Date: 19-Sep-2017
Source: 23rd IEEE International Symposium on On-Line Testing and Robust System Design, 2017, Thessaloniki, Greece, 3-5 July
Conference: IEEE International Symposium on On-Line Testing and Robust System Design 
Abstract: Negative Bias Temperature Instability (NBTI) is a prominent physical failure mechanism which severely degrades the performance of PMOS transistors whenever the voltage at the gate is negatively biased. It leads to catastrophic timing violations in critical circuits and a severe shortening of the overall operational lifetime of the entire system. To alleviate such damaging effects due to NBTI, we present PRITEXT, a novel technique which generates a minimal set of deterministic exercise vectors based on test generation techniques which inherently near-optimizes the bit patterns across each of the generated vectors; the end target being to exercise the critical paths of a device when dormant so as to achieve near-ideal NBTI stress reduction. We explore the design-space of our generated vectors and apply them to our test processor platform under differing sequences, where our evaluation under realistic benchmarks shows that PRITEXT leads to an average 4.99× and a maximum of 13.91× lifetime improvement using 9 generated vectors. In an attempt to reduce hardware overheads even further, we next propose a heuristic to further reduce the number of exercise vectors with minimum loss in lifetime improvement.
URI: http://ktisis.cut.ac.cy/handle/10488/12613
DOI: 10.1109/IOLTS.2017.8046205
Rights: © 2017 IEEE.
Type: Conference Papers
Affiliation : Texas AandM University 
University of Cyprus 
Cyprus University of Technology 
Appears in Collections:Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation

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