research-article

Multidimensional analog test metrics estimation using extreme value theory and statistical blockade

Authors:

Haralampos-G. Stratigopoulos,

Firas MohamedAuthors Info & Claims

DAC '13: Proceedings of the 50th Annual Design Automation Conference

Article No.: 72, Pages 1 - 7

https://doi.org/10.1145/2463209.2488822

Published: 29 May 2013 Publication History

Abstract

The high cost of testing certain analog, mixed-signal, and RF circuits has driven in the recent years the development of alternative low-cost tests to replace the most costly or even all standard specification tests. However, there is a lack of solutions for evaluating the parametric test error, that is, the test error for circuits with process variations, resulting from this replacement. For this reason, test engineers are often reluctant to adopt alternative tests since it is not guaranteed that test cost reduction is not achieved at the expense of sacrificing test quality. In this paper, we present a technique to estimate the parametric test error fast and reliably with parts per million accuracy. The technique is based on extreme value theory and statistical blockade. Relying on a small number of targeted simulations, it is capable of providing accurate estimates of parametric test error in the general scenario where a set of alternative tests replaces all or a subset of standard specification tests.

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Cited By

Jallepalli S(2024)Machine Learning for High Sigma Analog Designs (Invited)2024 ACM/IEEE 6th Symposium on Machine Learning for CAD (MLCAD)10.1109/MLCAD62225.2024.10740260(1-6)Online publication date: 9-Sep-2024
https://doi.org/10.1109/MLCAD62225.2024.10740260
Bounceur AMir SEuler RBeznia K(2020)Estimation of Analog/RF Parametric Test Metrics Based on a Multivariate Extreme Value ModelIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2019.290792339:5(966-976)Online publication date: May-2020
https://doi.org/10.1109/TCAD.2019.2907923
Barragan MLeger GGines APeralias ERueda A(2017)On the limits of machine learning-based testProceedings of the Conference on Design, Automation & Test in Europe10.5555/3130379.3130398(79-84)Online publication date: 27-Mar-2017
https://dl.acm.org/doi/10.5555/3130379.3130398
Show More Cited By

Index Terms

Multidimensional analog test metrics estimation using extreme value theory and statistical blockade
1. Hardware
2. Mathematics of computing
  1. Probability and statistics
    1. Statistical paradigms
      1. Statistical graphics

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cover image ACM Conferences

DAC '13: Proceedings of the 50th Annual Design Automation Conference

May 2013

1285 pages

ISBN:9781450320719

DOI:10.1145/2463209

Copyright © 2013 ACM.

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Published: 29 May 2013

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DAC '13: The 50th Annual Design Automation Conference 2013

May 29 - June 7, 2013

Texas, Austin

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Cited By

Jallepalli S(2024)Machine Learning for High Sigma Analog Designs (Invited)2024 ACM/IEEE 6th Symposium on Machine Learning for CAD (MLCAD)10.1109/MLCAD62225.2024.10740260(1-6)Online publication date: 9-Sep-2024
https://doi.org/10.1109/MLCAD62225.2024.10740260
Bounceur AMir SEuler RBeznia K(2020)Estimation of Analog/RF Parametric Test Metrics Based on a Multivariate Extreme Value ModelIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2019.290792339:5(966-976)Online publication date: May-2020
https://doi.org/10.1109/TCAD.2019.2907923
Barragan MLeger GGines APeralias ERueda A(2017)On the limits of machine learning-based testProceedings of the Conference on Design, Automation & Test in Europe10.5555/3130379.3130398(79-84)Online publication date: 27-Mar-2017
https://dl.acm.org/doi/10.5555/3130379.3130398
Ahmadi AStratigopoulos HHuang KNahar AOrr BPas MCarulli JMakris Y(2017)Yield Forecasting Across Semiconductor Fabrication Plants and Design GenerationsIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2017.266986136:12(2120-2133)Online publication date: Dec-2017
https://doi.org/10.1109/TCAD.2017.2669861
Stratigopoulos HKaminska B(2016)Analog and Mixed-Signal TestElectronic Design Automation for IC System Design, Verification, and Testing10.1201/b19569-29(605-629)Online publication date: 14-Apr-2016
https://doi.org/10.1201/b19569-29
Jallepalli SMooraka RParihar SHunter EMaalouf E(2016)Employing Scaled Sigma Sampling for Efficient Estimation of Rare Event Probabilities in the Absence of Input Domain MappingIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2016.252344735:6(943-956)Online publication date: Jun-2016
https://doi.org/10.1109/TCAD.2016.2523447
Jallepalli SMooraka RParihar SHunter EMaalouf E(2016)Rapid Assessment of Design Sensitivity to Process Excursions via Scaled Sigma SamplingIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2016.252344535:6(957-970)Online publication date: Jun-2016
https://doi.org/10.1109/TCAD.2016.2523445
Stratigopoulos HBarragan MMir SLe Gall HBhargava NBal A(2015)Evaluation of low-cost mixed-signal test techniques for circuits with long simulation times2015 IEEE International Test Conference (ITC)10.1109/TEST.2015.7342385(1-7)Online publication date: Oct-2015
https://doi.org/10.1109/TEST.2015.7342385
Stratigopoulos HSunter S(2014)Fast Monte Carlo-Based Estimation of Analog Parametric Test MetricsIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2014.236045833:12(1977-1990)Online publication date: Dec-2014
https://doi.org/10.1109/TCAD.2014.2360458
Yilmaz EOzev S(2014)Adaptive Learning Based Importance Sampling for Analog Circuit DPPM EstimationIEEE Design & Test10.1109/MDAT.2014.2361719(1-1)Online publication date: 2014
https://doi.org/10.1109/MDAT.2014.2361719

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