Remembrance of Transistors Past
Name
Remembrance_of_Transistors_Past_Compact_Model_Para.pdf
Description
Accepted version
Size
1.29 MB
Format
Unknown
Checksum (MD5)
d0b849e09569683b136ed97137fe721d
Author(s)
Yu, Li
Saxena, Sharad
Hess, Christopher
Elfadel, Abe
Antoniadis, Dimitri A.
Boning, Duane S
Alternative Title
Compact Model Parameter Extraction Using Bayesian Inference and Incomplete New Measurements
Date Issued
2014
Publisher
ACM Press
Citation
Yu, Li, Saxena, Sharad, Hess, Christopher, Elfadel, Abe, Antoniadis, Dimitri et al. 2014. "Remembrance of Transistors Past."
Version
Author's final manuscript
Abstract
In this paper, we propose a novel MOSFET parameter extraction method to enable early technology evaluation. The distinguishing feature of the proposed method is that it enables the extraction of an entire set of MOSFET model parameters using limited and incomplete IV measurements from on-chip monitor circuits. An important step in this method is the use of maximum-A-posteriori estimation where past measurements of transistors from various technologies are used to learn a prior distribution and its uncertainty ma- trix for the parameters of the target technology. The frame- work then utilizes Bayesian inference to facilitate extraction using a very small set of additional measurements. The pro- posed method is validated using various past technologies and post-silicon measurements for a commercial 28-nm pro- cess. The proposed extraction could also be used to charac- terize the statistical variations of MOSFETs with the signi-cant benet that some constraints required by the backward propagation of variance (BPV) method are relaxed. Copyright 2014 ACM.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1145/2593069.2593201
