A Comparison of Heterogeneous Multi-valued Decision Diagram Machines for Multiple-Output Logic Functions
Hiroki Nakahara, Tsutomu Sasao, Munehiro Matsuura · 2011
A heterogeneous multi-valued decision diagram~(HMDD) may have nodes with different numbers of variables. By partitioning the input variables into optimal disjoint sets, the HMDDs evaluate the function faster than BDDs with the same amount of memory. In this paper, we compare multi-output HMDD machines. First, we introduce three types of HMDDs: plural single-output HMDDs, Multi-Terminal HMDD, and HMDD for ECFN.Next, we show three HMDD machines~(HMDDMs). Then, we compare three HMDDMs with respect to the memory size, the execution time, and the area-time complexity. The comparison shows that, as for the area-time complexity, the HMDD for ECFN machine is the best.