By Topic

Efficient dynamic minimization of word-level DDs based on lower bound computation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
W. Gunther ; Inst. of Comput. Sci., Albert-Ludwigs-Univ., Freiburg, Germany ; R. Drechsler ; S. Horeth

Word-Level Decision Diagrams (WLDDs), like *BMDs or K*BMDs, have been introduced to overcome the limitations of Binary Decision Diagrams (BDDs), which are the state-of-the-art data structure to represent and manipulate Boolean functions. However, the size of these graph types largely depends on the variable ordering, i.e. it may vary from linear to exponential. In the meantime, dynamic approaches to find a good variable ordering are also known for WLDDs. In this paper we show how these approaches can be accelerated significantly using a combination of a lower bound computation and synthesis operations. In the experiments it turned out that by this technique, the runtime for dynamic minimization can be reduced by more than 40% on average without loss of quality

Published in:

Computer Design, 2000. Proceedings. 2000 International Conference on

Date of Conference: