Anaconda: simulation-based synthesis of analog circuits via stochastic pattern search

  • Authors:
  • R. Phelps;M. Krasnicki;R. A. Rutenbar;L. R. Carley;J. R. Hellums

  • Affiliations:
  • Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ., Pittsburgh, PA;-;-;-;-

  • Venue:
  • IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
  • Year:
  • 2006

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Abstract

Analog synthesis tools have traditionally traded quality for speed, substituting simplified circuit evaluation methods for full simulation in order to accelerate the numerical search for solution candidates. As a result, these tools have failed to migrate into mainstream use primarily because of difficulties in reconciling the simplified models required for synthesis with the industrial-strength simulation environments required for validation. We argue that for synthesis to be practical, it is essential to synthesize a circuit using the same simulation environment created to validate the circuit. In this paper, we develop a new numerical search algorithm efficient enough to allow full circuit simulation of each circuit candidate, and robust enough to find good solutions for difficult circuits. The method combines the population-of-solutions ideas from evolutionary algorithms with a novel variant of pattern search, and supports transparent network parallelism. Comparison of several synthesized cell-level circuits against manual industrial designs demonstrates the utility of the approach