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Netlist Analysis and Transformations Using SpyDrNet

Dallin Skouson
NSF Center for Space, High-Performance, and Resilient Computing (SHREC)
Department of Electrical and Computer Engineering, Brigham Young University

Andrew Keller
NSF Center for Space, High-Performance, and Resilient Computing (SHREC)
Department of Electrical and Computer Engineering, Brigham Young University

Michael Wirthlin
NSF Center for Space, High-Performance, and Resilient Computing (SHREC)
Department of Electrical and Computer Engineering, Brigham Young University

Abstract

Digital hardware circuits (i.e., for application specific integrated circuits or field programmable gate array circuits) can contain a large number of discrete components and connections. These connections are defined by a data structure called a \textquotedbl{}netlist\textquotedbl{}. Important information can be gained by analyzing the structure of the circuit netlist and relationships between components. Many specific circuit manipulations require component reorganization in hierarchy and various circuit transformations. SpyDrNet is an open-source netlist analysis and transformation tool written in Python that performs many of these functions. SpyDrNet provides a framework for netlist representation, querying, and modification that is netlist format independent and generalized for use in a wide variety of applications. This tool is actively used to enhance circuit reliability and error detection for circuits operating in harsh radiation environments.

Keywords

Hardware Design, Netlists, EDA, CAD

DOI

10.25080/Majora-342d178e-006

Bibtex entry

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