Title :
A Uniform Framework of Low Power FSM Partition Approach
Author :
Xia, Y. ; Ye, X. ; Wang, L. ; Tao, W. ; Almaini, A.
Author_Institution :
Fac. of Inf. Sci. & Technol., Ningbo Univ., Ningbo
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 partition. A new cost function is used to guide the optimization. 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 be applicable to partitioned FSMs. The experiment results show that the proposed approach can reduce power dissipation up to 80%.
Keywords :
finite state machines; genetic algorithms; finite state machine; genetic algorithm; low power FSM partition approach; optimization; Algorithm design and analysis; Automata; Circuits; Cities and towns; Contracts; Cost function; Genetic algorithms; Information science; Partitioning algorithms; Power dissipation;
Conference_Titel :
Communications, Circuits and Systems Proceedings, 2006 International Conference on
Conference_Location :
Guilin
Print_ISBN :
0-7803-9584-0
Electronic_ISBN :
0-7803-9585-9
DOI :
10.1109/ICCCAS.2006.285215
