Applying tabu search to the job-shop scheduling problem
Annals of Operations Research - Special issue on Tabu search
Parallel CLP on heterogeneous networks
Proceedings of the eleventh international conference on Logic programming
Parallel programming in OpenMP
Parallel programming in OpenMP
Search Procedures and Parallelism in Constraint Programming
CP '99 Proceedings of the 5th International Conference on Principles and Practice of Constraint Programming
CSPLIB: A Benchmark Library for Constraints
CP '99 Proceedings of the 5th International Conference on Principles and Practice of Constraint Programming
Components for State Restoration in Tree Search
CP '01 Proceedings of the 7th International Conference on Principles and Practice of Constraint Programming
Constraint and Integer Programming in OPL
INFORMS Journal on Computing
A decomposition-based implementation of search strategies
ACM Transactions on Computational Logic (TOCL)
Constraint-Based Local Search
Nondeterministic Control for Hybrid Search
Constraints
Scheduling multithreaded computations by work stealing
SFCS '94 Proceedings of the 35th Annual Symposium on Foundations of Computer Science
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Distributed constraint-based local search
CP'06 Proceedings of the 12th international conference on Principles and Practice of Constraint Programming
High-level nondeterministic abstractions in c++
CP'06 Proceedings of the 12th international conference on Principles and Practice of Constraint Programming
Experiments with massively parallel constraint solving
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Massively parallel constraint programming for supercomputers: challenges and initial results
CPAIOR'10 Proceedings of the 7th international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
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The availability of commodity multicore and multiprocessor machines and the inherent parallelism in constraint programming search offer significant opportunities for constraint programming. These opportunities also present a fundamental challenge: how to exploit parallelism transparently to speed up constraint programs. This paper shows how to parallelize constraint programs transparently without changes to the sequential code. The main technical idea consists of automatically lifting a sequential exploration strategy into its parallel counterpart, allowing workers to share and steal subproblems. Experimental results show that the parallel implementation may produce significant speedups on multicore machines.