Structure-aware high-dimensional performance modeling for analog and mixed-signal circuits


Conference Paper

Efficient high-dimensional performance modeling of nanoscale analog and mixed signal (AMS) circuits is extremely challenging. In this paper, we propose a novel structure-aware modeling (SAM) technique. The key idea of SAM is to accurately solve the model coefficients by applying an efficient statistical algorithm to exploit the underlying structure of AMS circuits. As a result, SAM dramatically reduces the required number of sampling points and, hence, the computational cost for performance modeling. Several circuit examples designed in a commercial 32nm CMOS process demonstrate that SAM achieves more than 2× runtime speedup over the traditional sparse regression technique without surrendering any accuracy. © 2013 IEEE.

Full Text

Duke Authors

Cited Authors

  • Sun, S; Li, X; Gu, C

Published Date

  • November 7, 2013

Published In

International Standard Serial Number (ISSN)

  • 0886-5930

International Standard Book Number 13 (ISBN-13)

  • 9781467361460

Digital Object Identifier (DOI)

  • 10.1109/CICC.2013.6658463

Citation Source

  • Scopus