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Efficient Parasitic-aware gm/ID-based Hybrid Sizing Methodology for Analog and RF Integrated Circuits

Published: 28 October 2020 Publication History

Abstract

As the primary second-order effect, parasitic issues have to be seriously addressed when synthesizing high-performance analog and RF integrated circuits (ICs). In this article, a two-phase hybrid sizing methodology for analog and RF ICs is proposed to take into account parasitic effect in the early design stage. It involves symbolic modeling and mixed-integer nonlinear programming (MINLP) in the first phase, and a many-objective evolutionary algorithm (many-OEA)-based sizing refiner in the second phase. With the aid of our proposed current density factor and piecewise curve fitting technique, the gm/ID concept, which is typically utilized to solve the analog circuit design problem, can provide theoretical support to our accurate symbolic modeling. Thus, the intrinsic and interconnect parasitics can be accurately considered in our work with moderate modeling effort. A variety of electrical, geometric, and parasitic (including parasitic mismatch) constraints can be conveniently integrated into our MINLP problem formulation. Moreover, numerical simulations are embedded into the many-OEA-based sizing phase, which is able to tackle floorplan co-optimization. With such dynamic floorplan variation, the parasitics accuracy can be sustained along the evolution. The experimental results demonstrate high efficacy of our proposed parasitic-aware hybrid sizing methodology.

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    cover image ACM Transactions on Design Automation of Electronic Systems
    ACM Transactions on Design Automation of Electronic Systems  Volume 26, Issue 2
    March 2021
    220 pages
    ISSN:1084-4309
    EISSN:1557-7309
    DOI:10.1145/3430836
    Issue’s Table of Contents
    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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    Publication History

    Published: 28 October 2020
    Accepted: 01 August 2020
    Revised: 01 July 2020
    Received: 01 April 2019
    Published in TODAES Volume 26, Issue 2

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    Author Tags

    1. gm/ID
    2. Analog and RF ICs
    3. circuit modeling
    4. circuit sizing
    5. floorplan optimization
    6. many-objective evolutionary algorithm
    7. mixed-integer nonlinear programming
    8. parasitic modeling

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    • (2024)A State-of-the-Art Survey on Advanced Electromagnetic Design: A Machine-Learning PerspectiveIEEE Open Journal of Antennas and Propagation10.1109/OJAP.2024.34126095:4(1077-1094)Online publication date: Aug-2024
    • (2024)Reinforcement-Learning-Based Successive Approximation Algorithm2024 IEEE International Symposium on Circuits and Systems (ISCAS)10.1109/ISCAS58744.2024.10558578(1-5)Online publication date: 19-May-2024
    • (2023)Design Space Exploration of Multi-Stage Op Amps by Symbolic Modeling and gm/ID Sampling2023 International Symposium of Electronics Design Automation (ISEDA)10.1109/ISEDA59274.2023.10218716(40-45)Online publication date: 8-May-2023
    • (2022)Performance-driven Wire Sizing for Analog Integrated CircuitsACM Transactions on Design Automation of Electronic Systems10.1145/355954228:2(1-23)Online publication date: 24-Dec-2022

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