The Algorithm of Control Program Generation for Optimization of LuNA Program Execution

  • Anastasia A. TkachevaEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10421)


LuNA fragmented programming system is a high-level declarative system of parallel programming. Such systems have the problem of achieving on appropriate program execution performance in comparison with MPI. The reasons are a high degree of parallel program execution non-determinism and execution overhead. The paper presents an algorithm of control program generation for LuNA programs. That is a step towards automatic improvement of LuNA program execution performance. Performance tests presented show effectiveness of the proposed approach.


High performance computing Fragmented programming technology Fragmented programming system LuNA Parallel program generation 



The author would like to thank his supervisor Dr. Victor E. Malyshkin for his professional guidance and Vladislav A. Perepelkin for his constructive suggestions during the development of this research work.


  1. 1.
    Malyshkin, V.E., Perepelkin, V.A.: LuNA fragmented programming system, main functions and peculiarities of run-time subsystem. In: Malyshkin, V. (ed.) PaCT 2011. LNCS, vol. 6873, pp. 53–61. Springer, Heidelberg (2011). doi: 10.1007/978-3-642-23178-0_5 CrossRefGoogle Scholar
  2. 2.
    Kraeva, M.A., Malyshkin, V.E.: Assembly technology for parallel realization of numerical models on MIMD-multicomputers. J. Future Gener. Comput. Syst. 17(6), 755–765 (2001)CrossRefzbMATHGoogle Scholar
  3. 3.
    Kireev, S.E., Malyshkin, V.E.: Fragmentation of numerical algorithms for parallel subroutines library. J. Supercomput. 57(2), 161–171 (2011)CrossRefGoogle Scholar
  4. 4.
    Akhmed-Zaki, D.Z., Lebedev, D.V., Perepelkin, V.A.: Implementation of a three dimensional three-phase fluid flow (oilwatergas) numerical model in LuNA fragmented programming system. J. Supercomput. 73(2), 624–630 (2017)CrossRefGoogle Scholar
  5. 5.
    Bosilca, G., Bouteiller, A., et al.: DAGuE: a generic distributed DAG engine for high performance computing. In Proceedings of IPDPS 2011 Workshops, pp. 1151–1158 (2011)Google Scholar
  6. 6.
    Bosilca, G., Bouteiller, A., et al.: Flexible development of dense linear algebra algorithms on massively parallel architectures with DPLASMA. In: Proceedings of IPDPS 2011 Workshops, pp. 1432–1441 (2011)Google Scholar
  7. 7.
    Perez, J.M., Badia, R.M., Labarta, J.: A flexible and portable programming model for SMP and multi-cores. Technical report 03/2007, Barcelona Supercomputing Center (2007)Google Scholar
  8. 8.
    Kale, L.V., Krishnan, S.: CHARM++: a portable concurrent object oriented system based on C++. In: Proceedings of OOPSLA 1993, pp. 91–108. ACM, New York (1993)Google Scholar
  9. 9.
    Huang, C., Laxmikant, V.K.: Charisma: orchestrating migratable parallel objects. In: Proceedings of the 16th International Symposium on High Performance Distributed Computing (HPDC), pp. 75–84 (2007)Google Scholar
  10. 10.
    Coutts, D., Loeh, A.: Deterministic parallel programming with Haskell. Comput. Sci. Eng. 14(6), 36–43 (2012)CrossRefGoogle Scholar
  11. 11.
    Loogen, R., Ortega-Malln, Y., Pea-Mar, R.: Parallel functional programming in Eden. J. Funct. Program. 15(3), 431–475 (2005)CrossRefzbMATHGoogle Scholar
  12. 12.
    Malyshkin, V.E., Perepelkin, V.A., Tkacheva, A.A.: Control flow usage to improve performance of fragmented programs execution. In: Malyshkin, V. (ed.) PaCT 2015. LNCS, vol. 9251, pp. 86–90. Springer, Cham (2015). doi: 10.1007/978-3-319-21909-7_9 CrossRefGoogle Scholar
  13. 13.
    Malyshkin, V.E., Perepelkin, V.A., Schukin, G.A.: Scalable distributed data allocation in LuNA fragmented programming system. J. Supercomput. 73(2), 726–732 (2017)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Institute of Computational Mathematics and Mathematical GeophysicsSiberian Branch of Russian Academy of SciencesNovosibirskRussia
  2. 2.Novosibirsk State UniversityNovosibirskRussia

Personalised recommendations