Title :
A novel low power FSM partition approach and its implementation
Author :
Xia, Y. ; Ye, X. ; Wang, L. ; Tap, J. ; Almain, A.E.A.
Author_Institution :
Sch. of Inf. Sci. & Eng., Ningbo Univ., China
Abstract :
A new finite state machine (FSM) partitioning approach is proposed in this paper. Genetic algorithm (GA) is employed to search the optimal or near optimal solution. A new cost function is used to guide the optimisation. The proposed algorithm is implemented in C. A new design model is proposed to implement partitioned sub-FSMs, which makes the existing monolithic FSM state assignment can be applied to partitioned FSMs. The experiment results show that the proposed approach can reduce power dissipation up to 78%.
Keywords :
finite state machines; genetic algorithms; logic partitioning; low-power electronics; C languange; finite state machine; genetic algorithm; low power FSM partition; monolithic FSM; Algorithm design and analysis; Automata; Binary codes; Circuits; Cost function; Genetic algorithms; Information science; Partitioning algorithms; Power dissipation; Power engineering and energy;
Conference_Titel :
NORCHIP Conference, 2005. 23rd
Print_ISBN :
1-4244-0064-3
DOI :
10.1109/NORCHP.2005.1596999