Abstract
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 (IE) problem has been solved in a two-step process. First step generates constraints on the relationship between codes for different symbols, called group constraints. In a following step, symbols are encoded such that constraints are satisfied. This paper addresses the partial input encoding problem (PIE), a variation of the IE problem which generates codes of minimum length. The role of group constraints within the framework of the PIE problem has been questioned. This paper describes an algorithm that unlike conventional approaches, which try to maximize the number of satisfied constraints, targets the economical implementation of each input constraint. The proposed approach is based on a powerful heuristic that produces high quality results in shorter time compared to previous algorithm.