By Topic

Process Variation and Temperature-Aware Full Chip Oxide Breakdown Reliability Analysis

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Cheng Zhuo ; Dept. of Electr. Eng. & Comput. Sci., Univ. of Michigan, Ann Arbor, MI, USA ; Chopra, K. ; Sylvester, D. ; Blaauw, D.

Gate oxide breakdown (OBD) is a key factor limiting the useful lifetime of an integrated circuit. Unfortunately, the conventional approach for full chip OBD reliability analysis assumes a uniform oxide thickness and worst-case temperature for all devices. In practice, however, gate oxide thickness varies from die-to-die and within-die and hence may cause different reliability for different devices even chips. Moreover, due to the increased across-die temperature variation, such difference may be exacerbated. Thus, as the precision of variation control worsens, an alternative reliability analysis approach is needed. In this paper, we propose a statistical framework for chip-level gate OBD reliability analysis while considering both die-to-die and within-die components of thickness variations as well as the across-die temperature variation. The thickness of each device is modeled as a distinct random variable and thus the full chip reliability estimation problem is defined on a huge sample space of several million devices. We observe that the chip-level OBD reliability function is independent of the relative location of the individual devices. This enables us to transform the problem such that the resulting representation can be expressed in terms of much fewer random variables. Using this transformation, we present a computationally efficient and accurate approach for estimating the full chip reliability while considering spatial correlations of gate oxide thickness as well as temperature variation. We show that, compared to Monte Carlo simulation, the proposed method incurs an error of only around 1% while improving the runtime by more than three orders of magnitude.

Published in:

Computer-Aided Design of Integrated Circuits and Systems, IEEE Transactions on  (Volume:30 ,  Issue: 9 )