High-level current macro-model for power-grid analysis

We present a frequency domain current macro-modeling technique for capturing the dependence of the block current waveform on its input vectors. The macro-model is based on estimating the discrete cosine transform (DCT) of the current waveform as a function of input vector pair and then taking the inverse transform to estimate the time domain current waveform. The input vector pairs are partitioned according to Hamming distance and a current macro-model is built for each Hamming distance using regression. Regression is done on a set of current waveforms generated for each circuit, using HSPICE. The average relative error in peak current estimation using the current macro-model is less than 20%