CAD Tools for Multi-Domain Systems on Chips

Steven P. Levitan, Donald M. Chiarulli, Timothy P. Kurzweg, Jose A. Martinez, Samuel J. Dickerson, Michael M. Bails, David K. Reed, Jason M. Boles

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

In the last several years there has been much success in the realm of multi-domain, mixed-signal system on chip (SoC) technology. Devices ranging from heterogeneous multi-core processors to micro-electromechanical systems (MEMS) to labs-on-chips are becoming highly integrated into chip-scale packages. However, the complexity of this multi-technology integration increases the difficulty of verifying such systems. Since different technology domains, such as electrical (digital and analog), optical (free-space and fiber), and mechanical (micro and macro), coexist in one package, there has emerged a need for tools that can verify such heterogeneous systems. For these integrated micro-systems the goal is to model large numbers of both linear and nonlinear components with sufficient speed and accuracy to explore the design space at the system level. Beyond functional design, mixed-technology tools, working at the system level, must support the traditional models of performance (e.g., speed, power, and area) as well as the special needs of mixed-technology systems. This means being able to analyze such things as crosstalk, noise, and mechanical tolerance in an interactive environment, and leads to the requirement of a computationally efficient yet accurate mixed-technology simulation framework. These problems are exacerbated by the need tomodel the behavior of the controlling digital hardware and/or software and the feedback between these two worlds. Most importantly, the tools must be able to capture the interaction of these realms in order to support the designer in making both architectural and technological tradeoffs.

Original languageEnglish (US)
Title of host publicationModel-Based Design for Embedded Systems
PublisherCRC Press
Pages643-695
Number of pages53
ISBN (Electronic)9781420067859
ISBN (Print)9781420067842
DOIs
StatePublished - Jan 1 2018

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • General Engineering

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