Minimization of memory size for heterogeneous MDDs
Proceedings of the 2004 Asia and South Pacific Design Automation Conference
XML Framework for Various Types of Decision Diagrams for Discrete Functions
IEICE - Transactions on Information and Systems
Relation algebras, matrices, and multi-valued decision diagrams
RAMiCS'12 Proceedings of the 13th international conference on Relational and Algebraic Methods in Computer Science
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In this paper, we propose a compact representationof logic functions using Multi-valued Decision Diagrams(MDDs) called heterogeneous MDDs. In a heterogeneousMDD, each variable may take a different domain. By partitioningbinary input variables and representing each partitionas a single multi-valued variable, we can produce aheterogeneous MDD with 16% smaller memory size than aReduced Ordered Binary Decision Diagram (ROBDD), andwith as small memory size as the Free Binary Decision Diagrams(FBDDs). We minimized a large number of benchmarkfunctions to show the compactness of heterogeneousMDDs.