Minimization Method of Finite State Machines for Low Power Design

Klimowicz, Adam; Соловьев, В. В.; Grzes, Tomasz

doi:10.1109/dsd.2015.21

Cited by 7 publications

(6 citation statements)

References 9 publications

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“…, }, descriptions of two FSMs, that is, base ckt and recon ckt b, are taken as inputs. The major contributing factors for power consumption and LUT requirement in FSM are the number of inputs and the internal states [8,19]. In any FSM, input variable and states are interdependent.…”

Section: Proposed Methodsmentioning

confidence: 99%

“…In FSM, splitting a state with high transitions results in low power consumption [8,19]. It also improves the operating speed [2,20].…”

Section: Proposition 1 Dummy Transitions In a Matched State Of Base mentioning

confidence: 99%

“…All dummy states and transitions are replaced by using Proposition 1. For output matching, 1 , 2 , 3 , 4 , 5 , 6 , 7 , 9 , 10 , 16 , and 18 are discarded because they contain 62, 12,13,8,6,6,38,4,16,46, and 78 instances of 1's, respectively, out of a total of 250 transitions.…”

Section: Experimental Evaluationmentioning

confidence: 99%

“…All states are matched with the states of base ckt in respective order. For output matching, 8 is discarded because it contains 3 instances of 1's, out of a total of 253 transitions.…”

Section: Experimental Evaluationmentioning

confidence: 99%

“…Due to the area and speed advantages, they act as an excellent alternative to their conventional LUT-based counterparts [7]. In such implementations, a considerable reduction in power consumption is obtained by disabling embedded memory blocks (EMBs) during the idle 2 International Journal of Reconfigurable Computing states [8,9]. The fundamental framework for FSM with input multiplexing (FSMIM) is made in [7] whose prime objective is to shorten the depth of ROM memory.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

FPGA Implementation of Reconfigurable Finite State Machine with Input Multiplexing Architecture Using Hungarian Method

Das

Priya

2018

International Journal of Reconfigurable Computing

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The mathematical model for designing a complex digital system is a finite state machine (FSM). Applications such as digital signal processing (DSP) and built-in self-test (BIST) require specific operations to be performed only in the particular instances. Hence, the optimal synthesis of such systems requires a reconfigurable FSM. The objective of this paper is to create a framework for a reconfigurable FSM with input multiplexing and state-based input selection (Reconfigurable FSMIM-S) architecture. The Reconfigurable FSMIM-S architecture is constructed by combining the conventional FSMIM-S architecture and an optimized multiplexer bank (which defines the mode of operation). For this, the descriptions of a set of FSMs are taken for a particular application. The problem of obtaining the required optimized multiplexer bank is transformed into a weighted bipartite graph matching problem where the objective is to iteratively match the description of FSMs in the set with minimal cost. As a solution, an iterative greedy heuristic based Hungarian algorithm is proposed. The experimental results from MCNC FSM benchmarks demonstrate a significant speed improvement by 30.43% as compared with variation-based reconfigurable multiplexer bank (VRMUX) and by 9.14% in comparison with combination-based reconfigurable multiplexer bank (CRMUX) during field programmable gate array (FPGA) implementation.

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Section: Proposed Methodsmentioning

confidence: 99%

“…In FSM, splitting a state with high transitions results in low power consumption [8,19]. It also improves the operating speed [2,20].…”

Section: Proposition 1 Dummy Transitions In a Matched State Of Base mentioning

confidence: 99%

Section: Experimental Evaluationmentioning

confidence: 99%

“…All states are matched with the states of base ckt in respective order. For output matching, 8 is discarded because it contains 3 instances of 1's, out of a total of 253 transitions.…”

Section: Experimental Evaluationmentioning

confidence: 99%