A Multicore Tool for Constraint Solving
This addresses the need for efficient constraint solving in AI and optimization domains, representing an incremental improvement by integrating existing solvers into a novel parallel framework.
The paper tackles the problem of solving constraint satisfaction/optimization problems by introducing sunny-cp2, the first parallel CP portfolio solver that enables dynamic, cooperative, and simultaneous execution of solvers in a multicore setting, with empirical results showing it can outperform the oracle solver that always selects the best solver.
*** To appear in IJCAI 2015 proceedings *** In Constraint Programming (CP), a portfolio solver uses a variety of different solvers for solving a given Constraint Satisfaction / Optimization Problem. In this paper we introduce sunny-cp2: the first parallel CP portfolio solver that enables a dynamic, cooperative, and simultaneous execution of its solvers in a multicore setting. It incorporates state-of-the-art solvers, providing also a usable and configurable framework. Empirical results are very promising. sunny-cp2 can even outperform the performance of the oracle solver which always selects the best solver of the portfolio for a given problem.