ACCURATE POWER ESTIMATION OF CMOS SEQUENTIAL-CIRCUITS

The existence of near-closed sets makes the power estimation of sequen tial circuits more complicated and time consuming, If caution is not t aken, the Monte Carlo-based power estimation techniques for sequential circuits can wrongly terminate the simulation with undesired results, In this paper, we have developed a strategy for a statistical power e stimation technique to take into account the possible existence of nea r-closed sets, We propose an algorithm that partitions states into nea r-closed sets, if they do exist, and a technique that reduces the comp utation time of the probabilities of states if state transition graph (STG) is available. If STG is not available, we propose a Monte Carlo- based technique with a warm-up period, The results show that the parti tioning algorithm also serves as a detector that signifies whether the re may exist near-closed sets, The computation time of state probabili ty can be reduced up to 50% in cases when near-closed sets are present , The relative error of the estimated individual node activity by the Monte Carlo-based technique with a warm-up period is within 3% of the result of long rim simulation.