research-article

Efficient parametric yield estimation of analog/mixed-signal circuits via Bayesian model fusion

Authors:

Wangyang Zhang,

Chenjie GuAuthors Info & Claims

ICCAD '12: Proceedings of the International Conference on Computer-Aided Design

Pages 627 - 634

https://doi.org/10.1145/2429384.2429519

Published: 05 November 2012 Publication History

Abstract

Parametric yield estimation is one of the most critical-yet-challenging tasks for designing and verifying nanoscale analog and mixed-signal circuits. In this paper, we propose a novel Bayesian model fusion (BMF) technique for efficient parametric yield estimation. Our key idea is to borrow the simulation data from an early stage (e.g., schematic-level simulation) to efficiently estimate the performance distributions at a late stage (e.g., post-layout simulation). BMF statistically models the correlation between early-stage and late-stage performance distributions by Bayesian inference. In addition, a convex optimization is formulated to solve the unknown late-stage performance distributions both accurately and robustly. Several circuit examples designed in a commercial 32 nm CMOS process demonstrate that the proposed BMF technique achieves up to 3.75X runtime speedup over the traditional kernel estimation method.

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Cited By

Fayazi MTaba MTabatabavakili AAfshari EDreslinski R(2023)FuNToM: Functional Modeling of RF Circuits Using a Neural Network Assisted Two-Port Analysis Method2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD)10.1109/ICCAD57390.2023.10323890(1-8)Online publication date: 28-Oct-2023
https://doi.org/10.1109/ICCAD57390.2023.10323890
Gao ZRohrer R(2022)Efficient Non-Monte-Carlo Yield EstimationIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2021.307910541:5(1222-1235)Online publication date: May-2022
https://doi.org/10.1109/TCAD.2021.3079105
Gao ZChen ZTao JSu YZhou DZeng X(2021)Bayesian Inference on Introduced General RegionProceedings of the 26th Asia and South Pacific Design Automation Conference10.1145/3394885.3431572(892-897)Online publication date: 18-Jan-2021
https://dl.acm.org/doi/10.1145/3394885.3431572
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Index Terms

Efficient parametric yield estimation of analog/mixed-signal circuits via Bayesian model fusion
1. Applied computing
  1. Arts and humanities
    1. Architecture (buildings)
      1. Computer-aided design
  2. Physical sciences and engineering
    1. Engineering
      1. Computer-aided design
2. Hardware
  1. Communication hardware, interfaces and storage
    1. Signal processing systems
  2. Integrated circuits

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Published In

cover image ACM Conferences

ICCAD '12: Proceedings of the International Conference on Computer-Aided Design

November 2012

781 pages

ISBN:9781450315739

DOI:10.1145/2429384

General Chair:
Alan J. Hu
Univ. of British Columbia, Vancouver, BC, Canada

Copyright © 2012 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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New York, NY, United States

Publication History

Published: 05 November 2012

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ICCAD '12: The International Conference on Computer-Aided Design

November 5 - 8, 2012

California, San Jose

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Overall Acceptance Rate 457 of 1,762 submissions, 26%

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Cited By

Fayazi MTaba MTabatabavakili AAfshari EDreslinski R(2023)FuNToM: Functional Modeling of RF Circuits Using a Neural Network Assisted Two-Port Analysis Method2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD)10.1109/ICCAD57390.2023.10323890(1-8)Online publication date: 28-Oct-2023
https://doi.org/10.1109/ICCAD57390.2023.10323890
Gao ZRohrer R(2022)Efficient Non-Monte-Carlo Yield EstimationIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2021.307910541:5(1222-1235)Online publication date: May-2022
https://doi.org/10.1109/TCAD.2021.3079105
Gao ZChen ZTao JSu YZhou DZeng X(2021)Bayesian Inference on Introduced General RegionProceedings of the 26th Asia and South Pacific Design Automation Conference10.1145/3394885.3431572(892-897)Online publication date: 18-Jan-2021
https://dl.acm.org/doi/10.1145/3394885.3431572
Fayazi MColter ZAfshari EDreslinski R(2021)Applications of Artificial Intelligence on the Modeling and Optimization for Analog and Mixed-Signal Circuits: A ReviewIEEE Transactions on Circuits and Systems I: Regular Papers10.1109/TCSI.2021.306533268:6(2418-2431)Online publication date: Jun-2021
https://doi.org/10.1109/TCSI.2021.3065332
Gao ZTao JZhou DZeng X(2020)Efficient Parametric Yield Estimation Over Multiple Process Corners via Bayesian Inference Based on Bernoulli DistributionIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2019.294068239:10(3144-3148)Online publication date: Oct-2020
https://doi.org/10.1109/TCAD.2019.2940682
Kovacs ITopa MPop CSandru EBuzo APelz G(2020)Correlating electrical and process parameters for yield detractors’ detection2020 International Symposium on Electronics and Telecommunications (ISETC)10.1109/ISETC50328.2020.9301121(1-4)Online publication date: 5-Nov-2020
https://doi.org/10.1109/ISETC50328.2020.9301121
Koziel SPietrenko-Dabrowska AKoziel SPietrenko-Dabrowska A(2020)IntroductionPerformance-Driven Surrogate Modeling of High-Frequency Structures10.1007/978-3-030-38926-0_1(1-22)Online publication date: 20-Feb-2020
https://doi.org/10.1007/978-3-030-38926-0_1
Tao JWang FCachecho PZhang WSun SLi XKanj RGu CZeng X(2019)Large-Scale Circuit Performance Modeling by Bayesian Model FusionMachine Learning in VLSI Computer-Aided Design10.1007/978-3-030-04666-8_14(403-422)Online publication date: 16-Mar-2019
https://doi.org/10.1007/978-3-030-04666-8_14
Zhai JYan CWang SZhou D(2018)An efficient Bayesian yield estimation method for high dimensional and high sigma SRAM circuitsProceedings of the 55th Annual Design Automation Conference10.1145/3195970.3195987(1-6)Online publication date: 24-Jun-2018
https://dl.acm.org/doi/10.1145/3195970.3195987
Zhai JYan CWang SZhou D(2018)An Efficient Bayesian Yield Estimation Method for High Dimensional and High Sigma SRAM Circuits2018 55th ACM/ESDA/IEEE Design Automation Conference (DAC)10.1109/DAC.2018.8465791(1-6)Online publication date: 24-Jun-2018
https://dl.acm.org/doi/10.1109/DAC.2018.8465791
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