Applying specialization-based parallel processing in constraint satisfaction problem solving

The purpose of this paper is to propose a method for constructing correct parallel processing programs from a problem description. The framework we adopt for this purpose is Equivalent Transformation Framework (ETF), which regards computation as transformation of definite clauses. In the framework, a problem´s domain knowledge and a query are described in definite clauses, and its meaning is defined by a model of the set of definite clauses. Then meaning-preserving transformation rules for the query are generated. We propose a parallel processing method based on “specialization”, a part of operation in the transformations, and discuss new parallel processing method based on the specialization that maintains correctness of the computation. The specialization is generalized notion of substitution in logic programming, and it allows more rich representation. We demonstrate the advantage of using specialization rather than substitution in constraint satisfaction problem solving.