Automatic characterization and modeling of power consumption in static RAMs

An automatic modeling technique is presented in this paper that allows one to build an accurate model of power consumption in embedded memory blocks. A software neural-network is used to create a regression tree by automatically splitting those variables that have a discontinuous effect on the power consumption. An application of the methodology to the modeling of a 0.35 /spl mu/m CMOS embedded SRAM is presented.

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