A realization of multiple-output logic functions using a RAM and a sequencer is presented. First, a multiple-output function is represented by an encoded characteristic function for non-zeros (ECFN). Then, it is represented by a cascade of look-up tables (LUTs
This paper shows a method to find a linear transformation that reduces the number of variables to represent a given incompletely specified index generation function. It first generates the difference matrix, and then finds a minimal set of variables using a covering table. Linear transformations are used to modify the covering table to produce a smaller solution. Reduction of the difference matrix is also considered.
Abstract-This paper shows four different methods to evaluate multiple-output logic functions using decision diagrams: Shared BDD (SBDD), Multi-Terminal BDD (MTBDD), BDD for characteristic functions (CF), and BDDs for Encoded Characteristic Function for Non-zero outputs (ECFNs). Methods to compute average evaluation time for each type of decision diagrams are presented. By experimental analysis using benchmark functions, the number of nodes and average evaluation time are compared. Our results show that BDDs for ECFNs outperforms MTBDDs, BDDs for CFs, and SBDDs with respect to both number of nodes and computation time. The sizes of BDDs for ECFNs are smaller than for MTBDDs, BDDs for CFs, and SBDDs.
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