Research

Smart Macromodeling for Custom Analog Circuits

Group Members: Hongzhou Liu, Amith Singhee, Saurabh Tiwary

Collaborators: L.R. Carley, CMU

Over the past decade, analog design automation has progressed to the point where there are industrially useful and commercially available tools at the cell level for analog components with 10–100 devices. Automated techniques for device sizing, for layout, and for basic statistical centering have been successfully deployed. However, successful component-level tools do not scale trivially to system-level applications. While a typical analog circuit may require only 100 devices, a typical system such as a phase-locked loop, data converter, or RF front-end might assemble a few hundred such circuits, and comprise 10,000 devices or more. And unlike purely digital systems, mixed-signal designs typically need to optimize dozens of competing continuous-valued performance specifications, which depend on the circuit designer’s abilities to successfully exploit a range of nonlinear behaviors across levels of abstraction from devices to circuits to systems. For purposes of synthesis or verification, these designs are not tractable when considered “flat”. In this project we developed a range of efficient macromodeling strategies — tools and algorithms to automatically extract useful, efficient models of the profoundly nonlinear behavior of these design — applicable from individual circuits to entire analog design spaces.

Key Papers/Talks

  • H. Liu, A. Singhee, R.A. Rutenbar, L.R. Carley, “Remembrance of circuits past: macromodeling by data mining in large analog design spaces,” Proceedings. 39th ACM/IEEE Design Automation Conference, June 2002. Winner, Best Paper Award. pdf
  • R.A. Rutenbar, “The Glorious Future of Macromodeling (In A Nutshell),” Invited Keynote talk given at IEEE Behavioral Modeling and Simulation Workshop, BMAS03, Oct 2003. pdf
  • R.A. Rutenbar, “The Glorious Future of Macromodeling (In A Nutshell),” Tutorial talk given at ACM/IEEE Design Automation Conference, June 2004. pdf
  • S.K. Tiwary, R.A. Rutenbar, “Scalable trajectory methods for on-demand analog macromodel extraction,” Proc ACM/IEEE Proceedings. 42nd Design Automation Conference, 2005. (Best Paper Nominee.) pdf
  • S.K. Tiwary, R.A. Rutenbar, “Faster, Parametric Trajectory-based Macromodels Via Localized Linear Reductions,” Proc. IEEE/ACM International Conference on
    Computer-Aided Design, Nov. 2006. pdf
  • S.K. Tiwary, R.A. Rutenbar, “On-the-Fly Fidelity Assessment for Trajectory-Based Circuit Macromodels,” Proc. IEEE Custom Integrated Circuits Conference (CICC), Sept 2006. pdf

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