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https://doi.org/10.1109/dac.19...
Article . 2005 . Peer-reviewed
Data sources: Crossref
DBLP
Conference object . 2018
Data sources: DBLP
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Power Macromodeling For High Level Power Estimation

Authors: Subodh Gupta; Farid N. Najm;

Power Macromodeling For High Level Power Estimation

Abstract

A modeling approach is presentedthat captures the dependence of the power dissipationof a combinational logic circuit on its input/outputsignal switching activity.The resultingpower macromodel, consisting of a single three dimensionaltable, can be used to estimate the powerconsumed in the circuit for any given input/outputsignal statistics.Given a low-level (typically gate-level)description of the circuit, we describe a characterizationprocess by which such a table modelcan be automatically built.In contrast to otherproposed techniques, this can be done for any givenlogic circuit without any user intervention, and appliesto all possible input/output signal statistics;it does not require one to construct specialized analyticalequations for the power dissipation.Thethree dimensions of our table-based model are theaverage input signal probability, average input transitiondensity, and average output zero-delay transition density.This approach has been implemented and modelshave been built for many benchmark circuits.Overa wide range of input signal statistics, we show thatthis model gives very good accuracy, with an RMSerror of under about 6%.

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    popularity
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    Top 10%
    influence
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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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!
96
Top 10%
Top 1%
Top 10%