The ALIGN Automated Analog Layout Engine: Progress, Learnings, and Open Issues

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

The ALIGN (Analog Layout, Intelligently Generated from Netlists) project [1, 2] is a joint university-industry effort to push the envelope of automated analog layout through a systematic new approach, novel algorithms, and open-source software [3]. Analog automation research has been active for several decades, but has not found widespread acceptance due to its general inability to meet the needs of the design community. Therefore, unlike digital design, which has a rich history of automation and extensive deployment of design tools, analog design is largely unautomated. ALIGN attempts to overcome several of the major issues associated with this lack of success. First, to mimic the human designer's ability to recognize sub-blocks and specify constraints, ALIGN has used machine learning (ML) based methods to assist in these tasks. Second, to overcome the limitation of past automation approaches, which are largely specific to a class of designs, ALIGN attempts to create a truly general layout engine by decomposing the layout automation process into a set of steps, with specific constraints that are specific to the family of circuits, which are divided into four classes: low-frequency components (e.g., analog-To-digital converters (ADCs), amplifiers, and filters); wireline components for high-speed links (e.g., equalizers, clock/data recovery circuits, and phase interpolators); RF/Wireless components (e.g., components of RF transmitters and receivers), and power delivery components (e.g., capacitor-and inductor-based DC-DC converters and low dropout (LDO) regulators). For each class of circuits, different sets of constraints are important, depending on their frequency, parasitic sensitivity, need for matching, etc., and ALIGN creates a unified methodological framework that can address each class. Third, in each step, ALIGN has generated new algorithms and approaches to help improve the performance of analog layout. Fourth, given that experienced analog designers desire greater visibility into the process and input into the way that design is carried out, ALIGN is built modularly, providing multiple entry points at which a designer may intervene in the process.

Original languageEnglish (US)
Title of host publicationISPD 2023 - Proceedings of the 2023 International Symposium on Physical Design
PublisherAssociation for Computing Machinery
Pages101-102
Number of pages2
ISBN (Electronic)9781450399784
DOIs
StatePublished - Mar 26 2023
Event32nd ACM International Symposium on Physical Design, ISPD 2023 - Virtual, Online, United States
Duration: Mar 26 2023Mar 29 2023

Publication series

NameProceedings of the 2023 International Symposium on Physical Design

Conference

Conference32nd ACM International Symposium on Physical Design, ISPD 2023
Country/TerritoryUnited States
CityVirtual, Online
Period3/26/233/29/23

Bibliographical note

Publisher Copyright:
© 2023 Owner/Author.

Keywords

  • Analog circuits
  • Design automation
  • Layout
  • Machine learning

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