Scalable parallel arc consistency algorithms for shared memory computers

The paper introduces three scalable static parallel arc consistency algorithms (SPAC-1, SPAC-2 and SPAC-3) designed for any general-purpose shared memory multiple instruction-stream, multiple data-stream (MIMD) computer. The algorithms are intended for constraint satisfaction problems in AI applications. Arc consistency is ensured of a finite domain binary constraint network. Through actual machine experimentation the paper measures work performed by the SPAC algorithms and compares it with work performed by existing sequential algorithms, AC-1 and AC-3. Results shows that the parallel arc consistency algorithms can be effectively used to pre-process a constraint network