Dan Fritchman

EECS Department, University of California, Berkeley

Technical Report No. UCB/EECS-2023-275

December 15, 2023

http://www2.eecs.berkeley.edu/Pubs/TechRpts/2023/EECS-2023-275.pdf

Analog and custom circuits have long been a bottleneck to the integrated circuit design process. Automation generation of such circuits has long been a topic of research, but has failed to break through to popular practice. This work introduces a modular framework including a cloud-native IC design database, an analog circuit programming framework, a web-native schematic system, and tools for directed programming and automatic compilation of semi-custom IC layout. Highlighted applications include wireline transceivers and data converters, including a recent prototype ADC targeted for neural sensing applications, and research infrastructure for distributed, machine learning based circuit optimization.

Advisors: Vladimir Stojanovic

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BibTeX citation:

@phdthesis{Fritchman:EECS-2023-275,
    Author= {Fritchman, Dan},
    Title= {An Integrated Circuit Design Framework for Human, Computer, and ML Designers},
    School= {EECS Department, University of California, Berkeley},
    Year= {2023},
    Month= {Dec},
    Url= {http://www2.eecs.berkeley.edu/Pubs/TechRpts/2023/EECS-2023-275.html},
    Number= {UCB/EECS-2023-275},
    Abstract= {Analog and custom circuits have long been a bottleneck to the integrated circuit design process. Automation generation of such circuits has long been a topic of research, but has failed to break through to popular practice. This work introduces a modular framework including a cloud-native IC design database, an analog circuit programming framework, a web-native schematic system, and tools for directed programming and automatic compilation of semi-custom IC layout. Highlighted applications include wireline transceivers and data converters, including a recent prototype ADC targeted for neural sensing applications, and research infrastructure for distributed, machine learning based circuit optimization.},
}

EndNote citation:

%0 Thesis
%A Fritchman, Dan 
%T An Integrated Circuit Design Framework for Human, Computer, and ML Designers
%I EECS Department, University of California, Berkeley
%D 2023
%8 December 15
%@ UCB/EECS-2023-275
%U http://www2.eecs.berkeley.edu/Pubs/TechRpts/2023/EECS-2023-275.html
%F Fritchman:EECS-2023-275