Models for architectural power and power grid noise analysis on data bus

The transition activity on a data bus is a time series that determines power consumption on this data bus. The average values of power consumption and power grid voltage drop are proportional to average value of transition activity, i.e., transition probability. The fluctuation of power grid voltage drop appears as noise on power grid and its strength is determined by the second order statistics of transition activity, i.e., variance, auto-correlation function or power spectrum. In this paper, for the first time, simple accurate models for estimating variance and power spectrum of transition activity are proposed. The proposed models are based on linearly modeling spatial-time correlation of bit-level transition activity and result in low computational complexity but very good estimation accuracy. In addition, the dual bit type (DBT) [1, 2] model for estimating average transition activity was further developed. The previous DBT model was made complete with the equation derived in this paper for computing transition probability beyond breakpoint BP ₁. Besides DSP computational architecture and algorithm designs, the proposed simple models are of great significance for power grid noise decoupling and chip floor-planning.