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- W2125119515 abstract "In this work we propose an effective solution to the main challenges of behavioral power modeling: the generation of models for the power dissipation of technology-independent soft macros and the strong dependence of power from input pattern statistics. Our methodology is based on a fast characterization performed by simulating the gate-level implementation of instances of soft macros within the behavioral description of the complete design. Once characterization has been completed, the backannotated behavioral model replaces the gate-level representation, thus allowing fast but accurate power estimates in a fully behavioral context. Our power characterization procedure is a very efficient process that can be easily embedded in synthesis-based design flows. No additional effort is required from the designer, since power characterization merges seamlessly with a natural top-down design methodology with iterative improvement. After characterization, the behavioral power simulation produces accurate average and instantaneous pourer estimates (with errors around 7% and 25%, respectively, from accurate gate-level power simulation)." @default.
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- W2125119515 date "1997-03-17" @default.
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- W2125119515 title "Adaptive least mean square behavioral power modeling" @default.
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- W2125119515 doi "https://doi.org/10.5555/787260.787698" @default.
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