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IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Article . 2000 . Peer-reviewed
License: IEEE Copyright
Data sources: Crossref
DBLP
Article . 2000
Data sources: DBLP
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Power modeling for high-level power estimation

Authors: Subodh Gupta; Farid N. Najm;

Power modeling for high-level power estimation

Abstract

In this paper, we propose a modeling approach that captures the dependence of the power dissipation of a combinational logic circuit on its input/output signal switching statistics. The resulting power macromodel, consisting of a single four-dimensional table, can be used to estimate the power consumed in the circuit for any given input/output signal statistics. Given a low-level (typically gate-level) description of the circuit, we describe a characterization process by which such a table model can be automatically built. The four dimensions of our table-based model are the average input signal probability, average input transition density, average spatial correlation coefficient, and average output zero-delay transition density. This approach has been implemented and models have been built for many benchmark circuits. Over a wide range of input signal statistics, we show that this model gives very good accuracy, with an rms error of about 4% and average error of about 6%. Except for one out of about 10 000 cases, the largest error observed was under 20%. If one ignores the glitching activity, then the rms error becomes under 1%, the average error becomes under 5%, and the largest error observed in all cases is under 18%.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
99
Top 10%
Top 1%
Top 10%
bronze