NDLI: Rare event diagnosis by iterative failure region locating and elite learning sample selection

Content Provider	IEEE Xplore Digital Library
Author	Hosoon Shin Tan, S.X.-D. Guoyong Shi Tlelo-Cuautle, E.
Copyright Year	2015
Description	Author affiliation: Opt. & Electrics (INAOE), Puebla, Mexico (Tlelo-Cuautle, E.) \|\| Shanghai Jiao Tong Univ., Shanghai, China (Guoyong Shi) \|\| Univ. of California, Riverside, Riverside, CA, USA (Hosoon Shin; Tan, S.X.-D.)
Abstract	Accurately estimating the failure region of rare events for nanoscale analog circuit blocks under process variations is a challenging task. In this paper, we propose a new statistical rare event analysis method. The new method is based on the iterative failure region locating scheme to reduce the sample counts while still maintains estimation accuracy. We derive the complete formulation for failure probability calculation in each iterative step. In addition, the new approach applies an elite learning sampling scheme, which considers both effectiveness of samples and well-coverage for process parameter search space, to further reduce number of samples after the gradual failure region locating at each iteration. As a result, the sample counts for simulation can be significantly reduced while sufficient representative samples are still kept for accurate failure probability analysis. Experiments were performed on the rise and fall time balancing failure analysis with Vth-NMOS, Vth-PMOS process parameters and the 4-gates logic circuit with 48 process parameters. The proposed method can deliver 228x faster than the conventional MC method with only 0.02-0.2% estimation errors. Furthermore, the new method estimates 20x more accurately with only 1.2x additional simulation costs than a recently published approach.
Starting Page	1
Ending Page	5
File Size	657945
Page Count	5
File Format	PDF
ISBN	9781467367103
DOI	10.1109/LATW.2015.7102505
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-03-25
Publisher Place	Mexico
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Accuracy Monte Carlo methods Estimation Failure analysis Probability Delays Integrated circuit modeling
Content Type	Text
Resource Type	Article

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