Parallel Search in Gecode

Constraint programming is an area of computer science which has developed rapidly over the last years. Constraint programming offers the tools needed to solve larger combinatorial problems with sufficient speed. The key to the success of constraint programmings success in combinatorial problem-solving over conventional search are clever algorithms and resource management. Today, computers with multiple processors working on shared memory are increasingly common. It is therefor natural to provide tools to use multiple processors for solving combinatorial problems with constraint programming. GECODE is a constraint programming library which introduces new and faster algorithms for finding solutions and using resources. GECODE however lacks support for using multiple processors. This thesis describes the work done too produce an adaptible system for using GECODE to do parallel search in a shared memory environment. This thesis handles the design and implementation of the tools needed fo