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  4. Increasing the accuracy of evaluation of the performance period of software complex components in multiprocessor computer systems under noise stochastic modeling

Increasing the accuracy of evaluation of the performance period of software complex components in multiprocessor computer systems under noise stochastic modeling

CSN.
2017;
, Number 881
: pp. 55 - 65
https://doi.org/10.23939/csn2017.881.055

Klushyn Y. Increasing the accuracy of evaluation of the performance period of software complex components in multiprocessor computer systems under noise stochastic modeling / Y. Klushyn // Visnyk Natsionalnoho universytetu "Lvivska politekhnika". Serie: Kompiuterni systemy ta merezhi. — Lviv : Vydavnytstvo Lvivskoi politekhniky, 2017. — No 881. — P. 55–65.

Authors:
  1. Yurii Klushyn
1
Lviv Polytechnic National University, Computer Engineering Department

To improve the accuracy of the estimation of the time of execution of complex software complexes on parallel computers, an algorithm for the uniform distribution of vertices of a graph of a given set of interrelated works is developed. This algorithm is used in the method of plywood stochastic simulation of multiprocessor computer systems.

parallel computing systems
complex interconnected works
direct stochastic modeling
Markov process
  1. Khritankov AS Mathematical model of performance characteristics of distributed computing systems. Computer science, management, economics LITERS OF MFTI. - 2010. - Vol. 2, No. 1 (5), p. 110-115.
  2. Ivanov N.N. Mathematical prediction of reliable execution of task sets with symmetric runtime distributions. Open Educational Journal, Issue No. 2-2 / 2011, p. 52-55. 3.
  3. Ignatushenko V.V., Klushin Yu.S. Prediction of Complex Software Complexes on Parallel Computers: Direct Stochastic Modeling // Automation and Telemechanics. 1994. N12, p. 142-157.
  4. Klushin Yu.S. Forecasting of Complex Software Complexes on Parallel Computers // Tez. Doc. The 2nd Ukrainian Automation Management Conference "Automation 95", Lviv, 1995, vol. 2, p. 100.
  5. Lysenko A.V. A brief overview of the methods of simulation simulation / AV Lysenko, NV Goryachev, I. D. Grab, B. K. Kemalov, N. K. Jurkov // Modern Information Technologies. 2011. № 14. P. 171-176.
  6. Borshchev A., Filippov A. From System Dynamics and Discrete Event to Practical Agent-Based Modeling: Reasons, Techniques, Tools. The 22nd International Conference of the System Dynamics Society, July 25 - 29, 2004, Oxford, England.
  7. Lobuzov AA The use of statistical simulation in the study of mass service systems, g. Almanac of World Science, ed. "AR-Consult", No. 2-1 (17), pages 10-13, 2017.
  8. Ignatushenko V.V., Klushyn Yu.S. Forecasting of Complex Software Complexes on Managing Parallel Computers: Accurate Methods // Scientific Works of the International Symposium "Automated Control Systems", Tbilisi: ed. Intelligence, 1996, p. 23-28. N. N. Ivanov, V. V.
  9. Klushin Yu.S. reduction of the number of states of the Markov process during the execution of complex software complexes on parallel computers. Scientific herald of Chernivtsi University. Computer systems and components. 2016. T. 7. Vip. 2, p. 53-62.
  10. Ivutin AN, Larkin YV, Prognostication of the execution time of the algorithm. Magazine. Izvestiya TulGU. Technical sciences. Issue No. 3 / 2013. From 301-315.
  11. Bocharov P.L., Preidunov Ju., B, Estimation of the execution time of a complex of works on a parallel computer system // System analysis and computer science. Sat scientific works, M .: Izd-dn, 1991. From 29-41.
  12. Ignatuschenko V.V. Organizing the Structures of Managing Multiprocessor Computing Systems. M.: Energoatomizdat. 1984.
  13. Klushin Yu.S. Evaluation of the effectiveness of various dispatcher disciplines to reduce the time spent implementing complex software complexes on parallel computing systems / Bulletin of the National University "Lvivska Polytechnika" № 413. Computer engineering and information technologies. - Lviv: NU "LP", 2000. - P. 19-23.