Compact representations of logic functions using heterogeneous MDDs

In this paper we propose a compact representation of logic functions using Multi-valued Decision Diagrams (MDDs) called heterogeneous MDDs. In a heterogeneous MDD, each variable may take a different domain. By partitioning binary input variables and representing each partition as a single multi-valued variable, we can produce a heterogeneous MDD with 16% smaller memory size than a Reduced Ordered Binary Decision Diagram (ROBDD), and with as small memory size as the Free Binary Decision Diagrams (FBDDs). We minimized a large number of benchmark functions to show the compactness of heterogeneous MDDs.