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Solving Multidimensional Global Optimization Problems Using Graphics Accelerators

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Supercomputing (RuSCDays 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 687))

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Abstract

In the present paper an approach to solving the global optimization problems using a nested optimization scheme is developed. The use of different algorithms at different nesting levels is the novel element. A complex serial algorithm (on CPU) is used at the upper level, and a simple parallel algorithm (on GPU) is used at the lower level. This computational scheme has been implemented in ExaMin parallel solver. The results of computational experiments demonstrating the speedup when solving a series of test problems are presented.

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Acknowledgements

This study was supported by the Russian Science Foundation, project No. 15-11-30022 “Global optimization, supercomputing computations, and applications”.

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Authors and Affiliations

  1. Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia

    Konstantin Barkalov & Ilya Lebedev

Authors
  1. Konstantin Barkalov
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  2. Ilya Lebedev
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Corresponding author

Correspondence to Konstantin Barkalov .

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Editors and Affiliations

  1. Research Computing Center (RCC), Moscow State University, Moscow, Russia

    Vladimir Voevodin

  2. Moscow State University, Moscow, Russia

    Sergey Sobolev

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Barkalov, K., Lebedev, I. (2016). Solving Multidimensional Global Optimization Problems Using Graphics Accelerators. In: Voevodin, V., Sobolev, S. (eds) Supercomputing. RuSCDays 2016. Communications in Computer and Information Science, vol 687. Springer, Cham. https://doi.org/10.1007/978-3-319-55669-7_18

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  • DOI: https://doi.org/10.1007/978-3-319-55669-7_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-55668-0

  • Online ISBN: 978-3-319-55669-7

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