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The Construction of the Parallel Algorithm Execution Schedule Taking into Account the Interprocessor Data Transfer

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Book cover Computational Science and Its Applications – ICCSA 2018 (ICCSA 2018)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10963))

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Abstract

The method of constructing a schedule for parallel algorithm execution is considered in the article. This algorithm takes into account the execution time of each operation of the algorithm and the relationship of operations on the data. The method is based on an information graph in which the nodes are the operations of the algorithm, and the edges are the directions of the data transfer. As a result of the interchange of operations between computing nodes, it is possible to achieve a reduction in the execution time of the algorithm by reducing the time spent on data transfer between computing nodes and reducing the downtime of computational nodes. The algorithm can be applied both in parallel programming and in adjacent areas, for example, when scheduling tasks in distributed systems.

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References

  1. He, B., Tang, L., Xie, J., Wang, X., Song, A.: Parallel numerical simulations of three-dimensional electromagnetic radiation with MPI-CUDA paradigms. Math. Probl. Eng. 2015 (2015). Article ID 823426, 9 p.

    Google Scholar 

  2. Jiancheng, Q., Yiqin, L., Yu, Z.: Parallel algorithm for wireless data compression and encryption. J. Sens. 2017 (2017). Article ID 4209397, 11 p.

    Google Scholar 

  3. Gong, C., Bao, W., Tang, G., Jiang, Y., Liu, J.: A parallel algorithm for the two-dimensional time fractional diffusion equation with implicit difference method. Sci. World J. 2014 (2014). Article ID 219580, 8 p.

    Google Scholar 

  4. Ma, X., Liu, S., Xiao, M., Xie, G.: Parallel algorithm with parameters based on alternating direction for solving banded linear systems. Math. Probl. Eng. 2014 (2014). Article ID 752651, 8 p.

    MathSciNet  Google Scholar 

  5. Hou, J., Lv, Q., Xiao, M.: A parallel preconditioned modified conjugate gradient method for large Sylvester matrix equation. Math. Probl. Eng. 2014 (2014). Article ID 598716, 7 p.

    MathSciNet  Google Scholar 

  6. Yu, D.-X., Yang, Z.-S., Yu, Y., Jiang, X.-R.: Research on large-scale road network partition and route search method combined with traveler preferences. Math. Probl. Eng. 2013 (2013). Article ID 950876, 8 p.

    Google Scholar 

  7. Amdahl, G.M.: Validity of the single processor approach to achieving large scale computing capabilities. In: Proceedings of the AFIPS Spring Joint Computer Conference, pp. 483–485. AFIPS Press, Reston (1967)

    Google Scholar 

  8. Ware, W.: The ultimate computer. IEEE Spectr. 9, 84–91 (1972)

    Article  Google Scholar 

  9. Grama, A., Gupta, A., Karypis, G., Kumar, V.: Introduction to Parallel Computing, 2nd edn. Addison Wesley, USA (2003)

    Google Scholar 

  10. Gergel, V.P., Strongin, R.G.: Parallel Computing for Multiprocessor Computers. NGU Publications, Nizhnij Novgorod (2003). (in Russian)

    Google Scholar 

  11. Quinn, M.J.: Parallel Programming in C with MPI and OpenMP, 1st edn. McGraw-Hill Education, New York (2003)

    Google Scholar 

  12. Wittwer, T.: An Introduction to Parallel Programming. VSSD uitgeverij, Netherlands (2006)

    Google Scholar 

  13. Tiwari, A., Tabatabaee, V., Hollingsworth, J.K.: Tuning parallel applications in parallel. Parallel Comput. 35(8–9), 475–492 (2009)

    Article  Google Scholar 

  14. Mubarak, M., Seol, S., Qiukai, L., Shephard, M.S.: A parallel ghosting algorithm for the flexible distributed mesh database. Sci. Program. 21(1–2), 17–42 (2013)

    Google Scholar 

  15. Kruatrachue, B., Lewis, T.: Grain size determination for parallel processing. IEEE Softw. 5(1), 23–32 (1988)

    Article  Google Scholar 

  16. Meuer, H., Strohmaier, E., Dongarra, J., Simon, H.: Top500 supercomputing sites (2015)

    Google Scholar 

  17. Yang, T., Gerasoulis, A.: DSC: scheduling parallel tasks on an unbounded number of processors. IEEE Trans. Parallel Distrib. Syst. 5(9), 951–967 (1994)

    Article  Google Scholar 

  18. Darbha, S., Agrawal, D.P.: Optimal scheduling algorithm for distributed memory machines. IEEE Trans. Parallel Distrib. Syst. 9(1), 87–95 (1998)

    Article  Google Scholar 

  19. Liu, C.L., Layland, J.W.: Scheduling algorithms for multiprogramming in hard real-time environment. J. ACM 20(1), 46–61 (1973)

    Article  MathSciNet  Google Scholar 

  20. Marte, B.: Preemptive scheduling with release times, deadlines and due times. J. ACM 29(3), 812–829 (1982)

    Article  MathSciNet  Google Scholar 

  21. Burns, A.: Scheduling hard real-time systems: a review. Softw. Eng. J. 6(3), 116–128 (1991)

    Article  Google Scholar 

  22. Stankovic, J.A.: Implications of Classical Scheduling Results for Real-Time Systems. IEEE Computer Society Press, Los Alamitos (1995)

    Article  Google Scholar 

  23. Tzen, T.H., Ni, L.M.: Trapezoid self-scheduling: a practical scheduling scheme for parallel compilers. IEEE Trans. Parallel Distrib. Syst. 4, 87–98 (1993)

    Article  Google Scholar 

  24. Sinnen, O., Sousa, L.A.: Communication contention in task scheduling. IEEE Trans. Parallel Distrib. Syst. 16, 503–515 (2005)

    Article  Google Scholar 

  25. Kupriyanov, M.S., Shichkina, Y.A.: Applying the list method to the transformation of parallel algorithms into account temporal characteristics of operations. In: Proceedings of the 19th International Conference on Soft Computing and Measurements, SCM 2016, 7519759, pp. 292–295 (2016). https://doi.org/10.1109/SCM.2016.7519759. ISBN: 978-146738919-8

  26. Shichkina, Y., Kupriyanov, M., Al-Mardi, M.: Optimization algorithm for an information graph for an amount of communications. In: Galinina, O., Balandin, S., Koucheryavy, Y. (eds.) NEW2AN/ruSMART-2016. LNCS, vol. 9870, pp. 50–62. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-46301-8_5

    Chapter  Google Scholar 

  27. Kwok, Y.-K., Ahmad, I.: Static scheduling algorithms for allocating directed task graphs to multiprocessors. ACM Comput. Surv. (CSUR) 31(4), 406–471 (1999)

    Article  Google Scholar 

  28. Shichkina, Y., Gushchanskiy, D., Degtyarev, A.: Information graph-based creation of parallel queries for databases. Int. J. Bus. Intell. Data Min. 13(4), 475–491 (2018). https://doi.org/10.1504/IJBIDM.2017.10004785

    Article  Google Scholar 

  29. Shichkina, Y., Degtyarev, A., Gushchanskiy, D., Iakushkin, O.: Application of optimization of parallel algorithms to queries in relational databases. In: Gervasi, O., et al. (eds.) ICCSA 2016. LNCS, vol. 9787, pp. 366–378. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-42108-7_28

    Chapter  Google Scholar 

  30. Bogdanov, A., Degtyarev, A., Korkhov, V., Gaiduchok, V., Gankevich, I.: Virtual supercomputer as basis of scientific computing. In: Horizons in Computer Science Research, vol. 11, pp. 159–198. Nova Science Publishers, Inc., New York (2015). 203 p.

    Google Scholar 

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Acknowledgments

The paper has been prepared within the scope of the state project “Initiative scientific project” of the main part of the state plan of the Ministry of Education and Science of Russian Federation (task No 2.6553.2017/8.9 BCH Basic Part) and partly supported by Russian Fund for Basic Research (grant No 16-07-00886).

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Authors and Affiliations

  1. Saint Petersburg Electrotechnical University “LETI”, ul. Professora Popova 5, 197376, St. Petersburg, Russia

    Yulia Shichkina & Al-Mardi Mohammed Haidar Awadh

  2. Saint Petersburg State University, Universitetskaia nab. 7-9, 199034, St. Petersburg, Russia

    Yulia Shichkina, Nikita Storublevtcev & Alexander Degtyarev

Authors
  1. Yulia Shichkina
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  2. Al-Mardi Mohammed Haidar Awadh
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  3. Nikita Storublevtcev
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  4. Alexander Degtyarev
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Corresponding author

Correspondence to Alexander Degtyarev .

Editor information

Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Italy

    Beniamino Murgante

  3. Covenant University, Ota, Nigeria

    Sanjay Misra

  4. Saint Petersburg State University, Saint Petersburg, Russia

    Elena Stankova

  5. Polytechnic University of Bari, Bari, Italy

    Carmelo M. Torre

  6. University of Minho, Braga, Portugal

    Ana Maria A.C. Rocha

  7. Monash University, Clayton, Victoria, Australia

    David Taniar

  8. Kyushu Sangyo University, Fukuoka shi, Fukuoka, Japan

    Bernady O. Apduhan

  9. Politecnico di Bari, Bari, Italy

    Eufemia Tarantino

  10. Myongji University, Yongin, Korea (Republic of)

    Yeonseung Ryu

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Shichkina, Y., Awadh, AM.M.H., Storublevtcev, N., Degtyarev, A. (2018). The Construction of the Parallel Algorithm Execution Schedule Taking into Account the Interprocessor Data Transfer. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2018. ICCSA 2018. Lecture Notes in Computer Science(), vol 10963. Springer, Cham. https://doi.org/10.1007/978-3-319-95171-3_6

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  • DOI: https://doi.org/10.1007/978-3-319-95171-3_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-95170-6

  • Online ISBN: 978-3-319-95171-3

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