MATHEMATICAL MODELS PRODUCTIVITY OF CLUSTER SYSTEM BASED ON RASPBERRY PI 3B+

Authors

  • S. M. Babchuk IvanoFrankivsk National Technical University of Oil and Gas, Ivano-Frankivsk, Ukraine.
  • Т. V. Humeniuk Ivano-Frankivsk National Technical University of Oil and Gas, Ivano-Frankivsk, Ukraine.
  • I. T. Romaniv Ivano-Frankivsk National Technical University of Oil and Gas, Ivano-Frankivsk, Ukraine.

DOI:

https://doi.org/10.15588/1607-3274-2021-1-5

Keywords:

cluster, cluster system, Raspberry Pi 3B , mathematical model, computer system performance, efficiency criterion.

Abstract

Context. High-performance computing systems are needed to solve many scientific problems and to work with complex applied problems. Previously, real parallel data processing was supported only by supercomputers, which are very limited and difficult to access. Currently, one way to solve this problem is to build small, cheap clusters based on single-board computers Raspberry Pi.

Objective. The goal of the work is the creation of a complex criterion for the efficiency of the cluster system, which could properly characterize the operation of such a system and find the dependences of the performance of the cluster system based on Raspberry Pi 3B+ on the number of boards in it with different cooling systems.

Method. It is offered to apply in the analysis of small cluster computer systems the complex criterion of efficiency of work of cluster system which will consider the general productivity of cluster computer system, productivity of one computing element in cluster computer system, electricity consumption by cluster system, electricity consumption per one computing element, the cost of calculating 1 Gflops cluster computer system, the total cost of the cluster computer system.

Results. The developed complex criterion of cluster system efficiency was used to create an experimental cluster system based on single-board computers Raspberry Pi 3B+. Mathematical models of the dependence of the performance of a small cluster system based on single-board computers Raspberry Pi 3B+ depending on the number of boards in it with different cooling systems have also been developed.

Conclusions. The conducted experiments confirmed the expediency of using the developed complex criterion of efficiency of the cluster system and allow to recommend it for use in practice when creating small cluster systems. Prospects for further research are to determine the weights of the constituent elements of the complex criterion of efficiency of the cluster system, as well as in the experimental study of the proposed weights.

Author Biographies

S. M. Babchuk , IvanoFrankivsk National Technical University of Oil and Gas, Ivano-Frankivsk, Ukraine.

PhD, Associate Professor, Associate Professor of the Department of Computer Systems and Networks.

Т. V. Humeniuk , Ivano-Frankivsk National Technical University of Oil and Gas, Ivano-Frankivsk, Ukraine.

PhD, Associate Professor of the Department of Computer Systems and Networks. 

I. T. Romaniv , Ivano-Frankivsk National Technical University of Oil and Gas, Ivano-Frankivsk, Ukraine.

Student of the Department of Computer Systems and Networks.

References

Mappuji A., Effendy N., Mustaghfirin M. et al. Study of Raspberry Pi 2 Quad-core Cortex-A7 CPU Cluster as a Mini Supercomputer, Emprowering Technology for Better Future : Eight international conference, Eastparc, 5–6 October 2016 : proceedings. Yogyakarta, ICITEE, 2016, P. 161. DOI: 10.1109/ICITEED.2016.7863250

Gergel V. P. Vysokoproizvoditelnyye vychisleniya dlya mnogoyadernykh mnogoprotsessornykh sistem: uchebnoye posobiye. Nizhniy Novgorod, Izd-vo NNGU im. N. I. Lobachevskogo, 2010, 420 p. ISBN 5-85746-602-4

Cox S., Cox J., Boardman R. et al. Iridis-pi: a low-cost, compact demonstration cluster, Cluster Computing, 2013, Vol. 17, No. 2, pp. 349–358. DOI: 10.1007/s10586-0130282-7

Cloutier M., Paradis C., Weaver V. Design and Analysis of a 32-bit Embedded High-Performance Cluster Optimized for Energy and Performance, Hardware-Software Co-Design for High Performance Computing, 17 November 2014 : proceedings. New Orleans, Co-HPC, 2014, pp. 1–8. DOI: 10.1109/Co-HPC.2014.7

Pajankar A. Raspberry Pi Supercomputing and Scientific Programming. Apress, 2017, 198 р. ISBN: 978-1-48422877-7, DOI: 10.1007/978-1-4842-2878-4

Basford P., Ossont S., Perkins C. et al.] Performance analysis of single board computer clusters, Future Generation Computer Systems, 2019, No. 14, Р. 102. DOI: 10.1016/j.future.2019.07.040

Cerero D., Sevilla U., Fernández-Rodríguez J. et al. SingleBoard-Computer Clusters for Cloudlet Computing in Internet of Things, Sensors, 2019. Vol.19, No. 13, P. 26. DOI: 10.3390/ s19133026

Sagkriotis S., Anagnostopoulos C., Pezaros D. Energy Usage Profiling for Virtualized Single Board Computer Clusters / S. Sagkriotis, // Conference: 2019 IEEE Symposium on Computers and Communications (ISCC), proceedings. Barcelona, IEEE, 2019, P. 326. DOI: 10.1109/ISCC47284.2019.8969611

Papakyriakou D. Benchmarking Raspberry Pi 2 Beowulf Cluster, International Journal of Computer Applications, 2018, No. 179, Р. 21–27. DOI: 10.5120/ijca2018916728

Frantskevich K. E., Demenkovets M. O., Tavtyn R. A. i dr. Issledovaniye klasternoy sistemy na osnove odnoplatnykh kompyuterov Raspberry Pi 3B+, Inzhenernyye resheniya, 2019, No. 9, P. 44. DOI: 10.32743/26586479.2019.9.10.199

Larionov A. M., Mayorov S. A., Novikov G. I. Vychislitelnyye kompleksy, sis-temy i seti: uchebnik dlya vuzov. Leningrad, Energoatomizdat, 1987, 288 p.

Voyevodin V. V., Voyevodin Vl. V. Parallelnyye vychisleniya. SPb, BKhV-Peterburg, 2002, 608 p. ISBN 594157-160-7

Dongarra J., Luszczek P., Padua D. HPC Challenge Benchmark, Encyclopedia of Parallel Computing, 2011, Chapter 26, pp. 844–850. DOI: 10.1007/978-0-387-09766-4_156

Yadav V., Mishra K., Singh P. et al. Home automation system using Raspberry Pi Zero W, International Journal of Advanced Intelligence Paradigms, 2020, Vol. 16, No. 2, P. 216. DOI: 10.1504/IJAIP.2020.107023

Published

2021-04-02

How to Cite

Babchuk , S. M. ., Humeniuk Т. V. ., & Romaniv , I. T. . (2021). MATHEMATICAL MODELS PRODUCTIVITY OF CLUSTER SYSTEM BASED ON RASPBERRY PI 3B+ . Radio Electronics, Computer Science, Control, 1(1), 46–56. https://doi.org/10.15588/1607-3274-2021-1-5

Issue

Section

Mathematical and computer modelling