Estimation of power dissipation using a novel power macromodeling technique
In this paper, we develop a novel technique based on Markov chains to accurately estimate power sensitivities to primary inputs in CMOS sequential circuits. A key application of power sensitivities is to construct a complicated power surface in the specification-space so as to easily obtain the power dissipation under any distribution of primary inputs, thereby offering an effective power macromodel for high-level power estimation. We demonstrate that such a power surface can be approximated by only a limited number of representative points. This benefit dramatically reduces the CPU and memory requirements. We have verified the feasibility and accuracy of the new technique to estimate power sensitivities on a large number of sequential benchmark circuits. Results on the power dissipation under different distributions of primary inputs demonstrate the efficiency and effectiveness of our power macromodeling technique.
estimation modeling power modeling and estimation simulation symbolic simulation symbolic techniques vlsi