The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Um diagrama de decisão binário compartilhado (SBDD) representa uma função de múltiplas saídas, onde os nós são compartilhados entre BDDs representando as diversas saídas. Um SBDD particionado consiste em dois ou mais SBDDs que compartilham nós. Os SBDDs separados são otimizados de forma independente, muitas vezes resultando em uma redução no número de nós em um único SBDD. Mostramos um método para particionar um único SBDD em duas partes que reduz a contagem de nós. Entre as funções de benchmark testadas, é realizada uma redução de nós de até 23%.
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Munehiro MATSUURA, Tsutomu SASAO, Jon T. BUTLER, Yukihiro IGUCHI, "Bi-Partition of Shared Binary Decision Diagrams" in IEICE TRANSACTIONS on Fundamentals,
vol. E85-A, no. 12, pp. 2693-2700, December 2002, doi: .
Abstract: A shared binary decision diagram (SBDD) represents a multiple-output function, where nodes are shared among BDDs representing the various outputs. A partitioned SBDD consists of two or more SBDDs that share nodes. The separate SBDDs are optimized independently, often resulting in a reduction in the number of nodes over a single SBDD. We show a method for partitioning a single SBDD into two parts that reduces the node count. Among the benchmark functions tested, a node reduction of up to 23% is realized.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e85-a_12_2693/_p
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@ARTICLE{e85-a_12_2693,
author={Munehiro MATSUURA, Tsutomu SASAO, Jon T. BUTLER, Yukihiro IGUCHI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Bi-Partition of Shared Binary Decision Diagrams},
year={2002},
volume={E85-A},
number={12},
pages={2693-2700},
abstract={A shared binary decision diagram (SBDD) represents a multiple-output function, where nodes are shared among BDDs representing the various outputs. A partitioned SBDD consists of two or more SBDDs that share nodes. The separate SBDDs are optimized independently, often resulting in a reduction in the number of nodes over a single SBDD. We show a method for partitioning a single SBDD into two parts that reduces the node count. Among the benchmark functions tested, a node reduction of up to 23% is realized.},
keywords={},
doi={},
ISSN={},
month={December},}
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TY - JOUR
TI - Bi-Partition of Shared Binary Decision Diagrams
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2693
EP - 2700
AU - Munehiro MATSUURA
AU - Tsutomu SASAO
AU - Jon T. BUTLER
AU - Yukihiro IGUCHI
PY - 2002
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E85-A
IS - 12
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - December 2002
AB - A shared binary decision diagram (SBDD) represents a multiple-output function, where nodes are shared among BDDs representing the various outputs. A partitioned SBDD consists of two or more SBDDs that share nodes. The separate SBDDs are optimized independently, often resulting in a reduction in the number of nodes over a single SBDD. We show a method for partitioning a single SBDD into two parts that reduces the node count. Among the benchmark functions tested, a node reduction of up to 23% is realized.
ER -