Lazy group sifting for efficient symbolic state traversal of FSMs

Proposes lazy group sifting for dynamic variable reordering during state traversal of finite state machines (FSMs). The proposed method relaxes the idea of pairwise grouping of the present state variables and their corresponding next state variables. This is done to produce better variable orderings...

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Veröffentlicht in:1999 IEEE/ACM International Conference on Computer-Aided Design. Digest of Technical Papers (Cat. No.99CH37051) S. 45 - 49
Hauptverfasser: Higuchi, H., Somenzi, F.
Format: Tagungsbericht Journal Article
Sprache:Englisch
Veröffentlicht: IEEE 1999
Schlagworte:
Automata
Binary decision diagrams
Circuit synthesis
Circuit testing
Flip-flops
Laboratories
Logic testing
Robustness
Sequential analysis
Sequential circuits
ISBN:9780780358324, 0780358325
ISSN:1092-3152
Online-Zugang:Volltext
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Abstract Proposes lazy group sifting for dynamic variable reordering during state traversal of finite state machines (FSMs). The proposed method relaxes the idea of pairwise grouping of the present state variables and their corresponding next state variables. This is done to produce better variable orderings during image computation without causing BDD (binary decision diagram) size blowup in the substitution of next state variables with present state variables at the end of image computation. Experimental results show that our approach is more robust in state traversal than the approaches that either unconditionally group variable pairs or never group them.
AbstractList Proposes lazy group sifting for dynamic variable reordering during state traversal of finite state machines (FSMs). The proposed method relaxes the idea of pairwise grouping of the present state variables and their corresponding next state variables. This is done to produce better variable orderings during image computation without causing BDD (binary decision diagram) size blowup in the substitution of next state variables with present state variables at the end of image computation. Experimental results show that our approach is more robust in state traversal than the approaches that either unconditionally group variable pairs or never group them.
This paper proposes lazy group sifting for dynamic variable re-ordering during state traversal. The proposed method relaxes the idea of pairwise grouping of present state variables and their corresponding next state variables. This is done to produce better variable orderings during image computation without causing BDD size blowup in the substitution of next state variables with present state variables at the end of image computation. Experimental results show that our approach is more robust in state traversal than the approaches that either unconditionally group variable pairs or never group them.
Author Somenzi, F.
Higuchi, H.
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Snippet Proposes lazy group sifting for dynamic variable reordering during state traversal of finite state machines (FSMs). The proposed method relaxes the idea of...
This paper proposes lazy group sifting for dynamic variable re-ordering during state traversal. The proposed method relaxes the idea of pairwise grouping of...
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StartPage 45
SubjectTerms Automata
Binary decision diagrams
Circuit synthesis
Circuit testing
Flip-flops
Laboratories
Logic testing
Robustness
Sequential analysis
Sequential circuits
Title Lazy group sifting for efficient symbolic state traversal of FSMs
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