Representations of Multiple-Output Functions Using Binary Decision Diagrams for Characteristic Functions
Summary :
This paper proposes a method to construct smaller binary decision diagrams for characteristic functions (BDDs for CFs). A BDD for CF represents an n-input m-output function, and evaluates all the outputs in O(n+m) time. We derive an upper bound on the number of nodes of the BDD for CF of n-bit adders (adrn). We also compare complexities of BDDs for CFs with those of shared binary decision diagrams (SBDDs) and multi-terminal binary decision diagrams (MTBDDs). Our experimental results show: 1) BDDs for CFs are usually much smaller than MTBDDs; 2) for adrn and for some benchmark circuits, BDDs for CFs are the smallest among the three types of BDDs; and 3) the proposed method often produces smaller BDDs for CFs than an existing method.
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- IEICE TRANSACTIONS on Fundamentals Vol.E82-A No.11 pp.2398-2406
- Publication Date
- 1999/11/25
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- Online ISSN
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- Type of Manuscript
- Special Section PAPER (Special Section on VLSI Design and CAD Algorithms)
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Hafiz Md. HASAN BABU, Tsutomu SASAO, "Representations of Multiple-Output Functions Using Binary Decision Diagrams for Characteristic Functions" in IEICE TRANSACTIONS on Fundamentals,
vol. E82-A, no. 11, pp. 2398-2406, November 1999, doi: .
Abstract: This paper proposes a method to construct smaller binary decision diagrams for characteristic functions (BDDs for CFs). A BDD for CF represents an n-input m-output function, and evaluates all the outputs in O(n+m) time. We derive an upper bound on the number of nodes of the BDD for CF of n-bit adders (adrn). We also compare complexities of BDDs for CFs with those of shared binary decision diagrams (SBDDs) and multi-terminal binary decision diagrams (MTBDDs). Our experimental results show: 1) BDDs for CFs are usually much smaller than MTBDDs; 2) for adrn and for some benchmark circuits, BDDs for CFs are the smallest among the three types of BDDs; and 3) the proposed method often produces smaller BDDs for CFs than an existing method.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e82-a_11_2398/_p
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@ARTICLE{e82-a_11_2398,
author={Hafiz Md. HASAN BABU, Tsutomu SASAO, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Representations of Multiple-Output Functions Using Binary Decision Diagrams for Characteristic Functions},
year={1999},
volume={E82-A},
number={11},
pages={2398-2406},
abstract={This paper proposes a method to construct smaller binary decision diagrams for characteristic functions (BDDs for CFs). A BDD for CF represents an n-input m-output function, and evaluates all the outputs in O(n+m) time. We derive an upper bound on the number of nodes of the BDD for CF of n-bit adders (adrn). We also compare complexities of BDDs for CFs with those of shared binary decision diagrams (SBDDs) and multi-terminal binary decision diagrams (MTBDDs). Our experimental results show: 1) BDDs for CFs are usually much smaller than MTBDDs; 2) for adrn and for some benchmark circuits, BDDs for CFs are the smallest among the three types of BDDs; and 3) the proposed method often produces smaller BDDs for CFs than an existing method.},
keywords={},
doi={},
ISSN={},
month={November},}
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TY - JOUR
TI - Representations of Multiple-Output Functions Using Binary Decision Diagrams for Characteristic Functions
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2398
EP - 2406
AU - Hafiz Md. HASAN BABU
AU - Tsutomu SASAO
PY - 1999
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E82-A
IS - 11
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - November 1999
AB - This paper proposes a method to construct smaller binary decision diagrams for characteristic functions (BDDs for CFs). A BDD for CF represents an n-input m-output function, and evaluates all the outputs in O(n+m) time. We derive an upper bound on the number of nodes of the BDD for CF of n-bit adders (adrn). We also compare complexities of BDDs for CFs with those of shared binary decision diagrams (SBDDs) and multi-terminal binary decision diagrams (MTBDDs). Our experimental results show: 1) BDDs for CFs are usually much smaller than MTBDDs; 2) for adrn and for some benchmark circuits, BDDs for CFs are the smallest among the three types of BDDs; and 3) the proposed method often produces smaller BDDs for CFs than an existing method.
ER -
English
