Low power realization of finite state machines—a decomposition approach
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Finite state machine decomposition for low power
DAC '98 Proceedings of the 35th annual Design Automation Conference
Spanning tree based state encoding for low power dissipation
DATE '99 Proceedings of the conference on Design, automation and test in Europe
VLSID '03 Proceedings of the 16th International Conference on VLSI Design
Energy Efficiency of Power-Gating in Low-Power Clocked Storage Elements
Integrated Circuit and System Design. Power and Timing Modeling, Optimization and Simulation
Design and application of multimodal power gating structures
ISQED '09 Proceedings of the 2009 10th International Symposium on Quality of Electronic Design
Power Management of Datacenter Workloads Using Per-Core Power Gating
IEEE Computer Architecture Letters
Low power finite state machine synthesis using power-gating
Integration, the VLSI Journal
NOVA: state assignment of finite state machines for optimal two-level logic implementation
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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Partitioning is an effective method for synthesis of low power finite state machines (FSM). To make the partitioning more effective power gating can be applied to turn OFF the inactive sub-machine. During transition from the states of one sub-machine to the states of other sub-machine, the supply voltage is required to be turned OFF for one sub-machine and turned ON for other sub-machine. This adjustment of supply voltage needs some amount of time. Hence, it effects the partitioning of FSMs for its power gated implementation as both the sub-machines are ON during this time. In this paper we have considered this issue by developing a new probabilistic power model of the power-gated design of FSM. As effective partitioning and encoding of FSM decides the power consumption of final power gating implementation, in this paper Genetic Algorithm (GA) has been used to solve this integrated problem of both bi-partitioning and encoding. Experimental results obtained show the effectiveness of the approach in terms of total dynamic power consumption, compared to the technique reported in the literature.