New Ideas on Face Constraint Generation

Frequently, the logic designer deals with functions with symbolic input variables. The binary encoding of such symbols should be chosen to optimize the final implementation. Conventionally, this input encoding problem has been solved in a two step process. First step generates constraints on the relationship between binary codes for different symbols, called group constraints. In a following step, symbols are encoded such that constraints are satisfied. Face generation has not received much attention contrary to the second step. In this paper we present a novel procedure for generating face constraint in the framework of the input encoding problem with a restriction on the length of the codes. It is based on the fact that as the solution to the symbolic minimization step, involved in the face constraint generation process, is not unique, different sets of face constraints can be used to guide the encoding step. Clearly the set selected can influence the cost of the final boolean cover obtained. Preliminary experiments show promising results.