Layout automation for analog and mixed-signal circuits using digital place-and-route tools

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Abstract/Contents

Abstract
Today's analog and mixed-signal (AMS) layout flow requires long manual iterations and does not leverage computing resources for data-driven optimization. This issue is further compounded by the explosion of design rules and layout-dependent effects. We present an AMS layout generation flow that leverages digital place-and-route tools, amortizes setup cost with reusable primitives, and prunes layout candidates using time-efficient layout quality surrogates. We also analyze layout-dependent effects and parasitics and investigate unique challenges and mitigation strategies associated with using digital place-and-route tools for AMS circuits. These insights are validated with a generated 4x time-interleaved successive approximation analog-to-digital converter, a StrongARM comparator, and a voltage-controlled oscillator (VCO) in 16 nm FinFET CMOS. Silicon measurement results of the VCO closely track the simulation, showing only 6% in maximal oscillation frequency degradation from its manual counterpart, verifying the methodology from netlist to silicon.

Description

Type of resource text
Form electronic resource; remote; computer; online resource
Extent 1 online resource.
Place California
Place [Stanford, California]
Publisher [Stanford University]
Copyright date 2021; ©2021
Publication date 2021; 2021
Issuance monographic
Language English

Creators/Contributors

Author Wei, Po-Hsuan
Degree supervisor Murmann, Boris
Thesis advisor Murmann, Boris
Thesis advisor Horowitz, Mark (Mark Alan)
Thesis advisor Lee, Thomas H, 1959-
Degree committee member Horowitz, Mark (Mark Alan)
Degree committee member Lee, Thomas H, 1959-
Associated with Stanford University, Department of Electrical Engineering

Subjects

Genre Theses
Genre Text

Bibliographic information

Statement of responsibility Po-Hsuan Wei.
Note Submitted to the Department of Electrical Engineering.
Thesis Thesis Ph.D. Stanford University 2021.
Location https://purl.stanford.edu/mv779vk8233

Access conditions

Copyright
© 2021 by Po-Hsuan Wei
License
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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