Characterization-free behavioral power modeling

Authors:
A. Bogliolo;L. Benini;G. De Micheli
Affiliations:
DEIS - University of Bologna, Bologna, I-40136;CSL - Stanford University, Stanford, CA;CSL - Stanford University, Stanford, CA
Venue:
Proceedings of the conference on Design, automation and test in Europe
Year:
1998

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Abstract

We propose a new approach to RT-level power modeling for combinational macros, that does not require simulation-based characterization. A pattern-dependent power model for a macro is analytically constructed using only structural information about its gate-level implementation. The approach has three main advantages over traditional techniques: i) it provides models whose accuracy does not depend on input statistics, ii) it offers a wide range of trade-off between accuracy and complexity, and iii} it enables the construction of pattern-dependent conservative upper bounds.