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Scalable distributed data allocation in LuNA fragmented programming system

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Abstract

The paper presents a scalable distributed algorithm for static and dynamic data allocation in LuNA fragmented programming system. LuNA is intended for automation of construction of parallel programs, which implement large-scale numerical models for multicomputers with large number of computing nodes. The proposed algorithm takes into account data structure of the numerical model implemented, provides static and dynamic load balancing and can be used with various network topologies.

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Authors and Affiliations

  1. Institute of Computational Mathematics and Mathematical Geophysics SB RAS, Novosibirsk, Russia

    Victor Malyshkin, Vladislav Perepelkin & Georgy Schukin

  2. Novosibirsk State University, Novosibirsk, Russia

    Victor Malyshkin & Vladislav Perepelkin

  3. Novosibirsk State Technical University, Novosibirsk, Russia

    Victor Malyshkin & Georgy Schukin

Authors
  1. Victor Malyshkin
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  2. Vladislav Perepelkin
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  3. Georgy Schukin
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Corresponding author

Correspondence to Vladislav Perepelkin.

Additional information

This work was supported by Russian Foundation for Basic Research (Grants 14-07-00381 a and 14-01-31328 mol_a).

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Malyshkin, V., Perepelkin, V. & Schukin, G. Scalable distributed data allocation in LuNA fragmented programming system. J Supercomput 73, 726–732 (2017). https://doi.org/10.1007/s11227-016-1781-0

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  • DOI: https://doi.org/10.1007/s11227-016-1781-0

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