Scheduled System Maintenance:
Some services will be unavailable Sunday, March 29th through Monday, March 30th. We apologize for the inconvenience.
By Topic

Using lower bounds during dynamic BDD minimization

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
$31 $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

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

Ordered Binary Decision Diagrams (BDDs) are a data structure for representation and manipulation of Boolean functions often applied in VLSI CAD. The choice of the variable ordering largely influences the size of the BDD; its size may vary from linear to exponential. The most successful methods for finding good orderings are based on dynamic variable reordering, i.e., exchanging of neighboring variables. This basic operation has been used in various variants, like sifting and window permutation. In this paper we show that lower bounds computed during the minimization process can speed up the computation significantly. First, lower bounds are studied from a theoretical point of view. Then these techniques are incorporated in dynamic minimization algorithms. By the computation of good lower bounds large parts of the search space can be pruned resulting in very fast computations. Experimental results are given to demonstrate the efficiency of our approach

Published in:

Design Automation Conference, 1999. Proceedings. 36th

Date of Conference:

1999