@inproceedings{Dom2002,Author = {Domenik Helms, Eike Schmidt, Arne Schulz, Ansgar Stammermann, Wolfgang Nebel},Title = {An Improved Power Macro-Model for Arithmetic Datapath Components},Year = {2002},Month = {9},Booktitle = {PATMOS},Organization = {Proceedings of PATMOS 02, Seville, Spain},type = {inproceedings},note = {We propose an improved power macro-model for arithmetic datapath components, which is based on spatio-temporal correlations of two consecutive input vectors and the output vector. Based on the enhanced Hamming-distance model [3], we introduce an additiona},Abstract = {We propose an improved power macro-model for arithmetic datapath components, which is based on spatio-temporal correlations of two consecutive input vectors and the output vector. Based on the enhanced Hamming-distance model [3], we introduce an additional spatial distance for the input vector and the Hamming-distance of the output vector to improve model accuracy significantly. Experimental results show that the models standard deviation is reduced by 3% for small components and up to 23% for complex components. Because of its fast and accurate power prediction, this model can be used for fast high-level power analysis.}}@COMMENT{Bibtex file generated on }