A new parameterizable power macro-model for datapath components

Abstract

We propose a novel power macro-model which is based on the Hamming-distance of two consecutive input vectors and additional information on the module structure. The model is parameterizable in terms of input bit-widths and can be applied to a wide variety of datapath components. The good trade-off between estimation accuracy, model complexity and flexibility makes the model attractive for power analysis and optimization tasks on a high level of abstraction. Furthermore, a new approach is presented, that allows one to calculate the average Hamming-distance distribution of an input data stream. It is demonstrated, that the application of Hamming-distance distributions, instead of only average values, improves the estimation accuracy for a number of typical DSP-modules and data streams.