Dynamic Minimization of Bi-Kronecker Functional Decision Diagrams

A recently proposed canonical representation called Bi-Kronecker Functional Decision Diagrams (BKFDDs) utilizes the classical decompositions (the Shannon and Davio decompositions) and their biconditional variants, and hence can be seen as a generalization of some existing decision diagrams: BDDs, FD...

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Bibliographic Details
Published in:Digest of technical papers - IEEE/ACM International Conference on Computer-Aided Design pp. 1 - 9
Main Authors: Huang, Xuanxiang, Che, Haipeng, Fang, Liangda, Chen, Qingliang, Guan, Quanlong, Deng, Yuhui, Su, Kaile
Format: Conference Proceeding
Language:English
Published: Association on Computer Machinery 02.11.2020
Subjects:
Benchmark testing
Bi-Kronecker Functional Decision Diagrams
binary decision diagrams
BKFDD
Boolean function
Boolean functions
canonical representation
Decision diagrams
decomposition types
Design automation
Dynamic minimization
dynamic minimization algorithms
Heuristic algorithms
logic circuits
minimisation
Minimization
network synthesis
ODT
Semantics
Servers
ISSN:1558-2434
Online Access:Get full text
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Summary:A recently proposed canonical representation called Bi-Kronecker Functional Decision Diagrams (BKFDDs) utilizes the classical decompositions (the Shannon and Davio decompositions) and their biconditional variants, and hence can be seen as a generalization of some existing decision diagrams: BDDs, FDDs, KFDDs and BBDDs. However, the size of BKFDDs for a Boolean function is very sensitive to variable orders with decomposition types (ODTs). Therefore, identifying a good ODT is of paramount importance for BKFDDs. In this paper, we propose four dynamic minimization algorithms for BKFDDs, which encapsulate smart strategies to search for a good ODT in a dynamic way. The experiments have been carried out on four influential benchmarks: ISCAS89, MCNC, ITC99 and EPFL, and the experimental results show that the proposed group sifting algorithms for BKFDDs are very effective and can produce BKFDDs with smaller size than state-of-the-art packages of DDs.
ISSN:1558-2434
DOI:10.1145/3400302.3415618