A symbolic algorithm for low power sequential synthesis

We present an algorithm that restructures the state transition graph (STG) of a sequential circuit so as to reduce power dissipation. The STG is modified without changing the behavior of the circuit, by exploiting state equivalence. Rather than aiming primarily at reducing the number of states, our algorithm redirects transitions so that the new destination states are equivalent to the original ones, while the average activity of the circuit is decreased. The impact on area is also estimated to increase the accuracy of the power analysis. The STG and all other major data structures are stored as decision diagrams, and the algorithm does not enumerate explicitly the states or the transitions (i.e., it is symbolic.) Therefore, it can deal with circuits that have millions of states. Once the STG has been restructured we apply symbolic factoring algorithms, based on zero-suppressed BDDs, to convert the optimized graph into a multilevel circuit. We derive an efficient circuit from the BDDs of the STG by incorporating power constraints in the symbolic factoring algorithms.