Improvement of the Embarrassingly Parallel Search for Data Centers

Abstract : We propose an adaptation of the Embarrassingly Parallel Search (EPS) method for data centers. EPS is a simple but efficient method for parallel solving of CSPs. EPS decomposes the problem in many distinct subproblems which are then solved independently by workers. EPS performed well on multi-cores machines (40), but some issues arise when using more cores in a datacenter. Here, we identify the decomposition as the cause of the degradation and propose a parallel decomposition to address this issue. Thanks to it, EPS gives almost linear speedup and outperforms work stealing by orders of magnitude using the Gecode solver.
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Communication dans un congrès
CP 2014, Sep 2014, Lyon, France. Principles and Practice of Constraint Programming - 20th International Conference, 2014, Lyon, France, September 8-12, 2014. Proceedings, 2014, 〈10.1007/978-3-319-10428-7_45〉
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Jean-Charles Régin, Mohamed Rezgui, Arnaud Malapert. Improvement of the Embarrassingly Parallel Search for Data Centers. CP 2014, Sep 2014, Lyon, France. Principles and Practice of Constraint Programming - 20th International Conference, 2014, Lyon, France, September 8-12, 2014. Proceedings, 2014, 〈10.1007/978-3-319-10428-7_45〉. 〈hal-01344078〉

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