Genetic algorithm-based FSM synthesis with area-power trade-offs

Traditionally, state-encoding strategies targeting minimization of area, dynamic power or a combination of them have been utilized in finite state machine (FSM) synthesis. With drastic scaling down of devices at recent technology level, leakage power has also become an important design parameter to be considered during synthesis. A genetic algorithm-based state encoding, targeting area and power minimized FSM, has been proposed in this paper. A unified technique to reduce both static power (leakage) and dynamic power along with area trade-off has been carried out for FSM synthesis, targeting static CMOS NAND–NAND PLA, dynamic CMOS NOR–NOR PLA and pseudo-NMOS NOR–NOR PLA implementations. Suitable weights for area, leakage power and dynamic power to minimize power density have also been explored. Simulation with MCNC benchmarks shows an average improvement of 31%, 26% and 29% in leakage power consumption, dynamic power consumption and area requirement respectively, over NOVA-based state assignment technique in case of dynamic CMOS PLA implementation. Improvements of 30% in leakage power and 15% in area have been obtained for pseudo-NMOS PLA implementation. For the static CMOS case, the improvements are about 29% in leakage power consumption, 14% in dynamic power consumption and 18% in area requirement.