Savant: Automatic Parallelization of a Scheduling Heuristic with Machine Learning

Abstract : This paper investigates the automatic parallelization of a heuristic for an NP-complete problem, with machine learning. The objective is to automatically design a new concurrent algorithm that finds solutions of comparable quality to the original heuristic. Our approach, called Savant, is inspired from the Savant syndrome. Its concurrency model is based on map-reduce. The approach is evaluated with the well-known Min-Min heuristic. Simulation results on two problem sizes are promising, the produced algorithm is able to find solutions of comparable quality.
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Communication dans un congrès
NaBIC 2013 - 5th World Congress on Nature and Biologically Inspired Computing, Aug 2013, Fargo, United States. IEEE, Nature and Biologically Inspired Computing (NaBIC), 2013 World Congress on, pp.52-57, 2013, 〈http://www.mirlabs.org/nabic13/〉. 〈10.1109/NaBIC.2013.6617837〉
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Contributeur : Dorronsoro Bernabe <>
Soumis le : lundi 14 octobre 2013 - 20:08:07
Dernière modification le : mercredi 24 janvier 2018 - 17:43:54

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Frederic Pinel, Bernabé Dorronsoro, Pascal Bouvry, Samee U. Khan. Savant: Automatic Parallelization of a Scheduling Heuristic with Machine Learning. NaBIC 2013 - 5th World Congress on Nature and Biologically Inspired Computing, Aug 2013, Fargo, United States. IEEE, Nature and Biologically Inspired Computing (NaBIC), 2013 World Congress on, pp.52-57, 2013, 〈http://www.mirlabs.org/nabic13/〉. 〈10.1109/NaBIC.2013.6617837〉. 〈hal-00872988〉

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