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Performance Evaluation of Raspberry Pi 4B Microcomputer: Case Studies on MPICH Cluster, VMware ESXi ARM Fling, and Windows 11 ARM OS

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Information and Communication Technologies in Education, Research, and Industrial Applications (ICTERI 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1698))

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Abstract

The performance of the Raspberry Pi 4B computer was evaluated for three cases. First, a Raspberry Pi heterogeneous MPICH cluster with weight-based load balancing and fuzzy estimation of node computational performance was designed. Fuzzification, formation of fuzzy rules, fuzzy inference, and defuzzification were employed to determine the performance weights. In the cluster with two Raspberry Pi 4B boards with 2 GB RAM and Raspberry Pi 64-bit OS and one Raspberry Pi 3B board with 1 GB RAM and Raspberry Pi 32-bit OS, the recommended performance weights are (5, 5, 1), respectively. The developed Python program for the prime numbers finding algorithm employs the proposed weight-based load balancing, which is approximately five times faster than the basic algorithm with equal loading for the maximum integer of 300000. Second, the MPICH cluster with two nodes in two virtual machines located on two different Raspberry Pi 4B boards with Ubuntu Server for ARM on the hypervisor VMware ESXi ARM Fling shows the mean signed deviation −34.01 s regarding the Raspberry Pi 64-bit OS for the maximum integer of 300000. Third, the performance of the Raspberry Pi 4B 8 GB computer with Windows 11 ARM OS was compared with the laptop Lenovo G510 with Intel Core i7-4700MQ and Windows 10 64-bit OS using the combinatorial optimization algorithm implemented in the 32-bit Windows app. The Raspberry Pi 4B 8 GB consumed approximately six times more power. Thus, the Raspberry Pi 4B single-board computer is recommended for executing low-performance applications and/or short-term processing of high-performance tasks.

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Acknowledgements

This paper and the research behind it have the support of the universities where the authors have been conducting the presented project. The authors sincerely appreciate the management and colleagues of the University of Central Asia (Kyrgyzstan) and Kryvyi Rih National University (Ukraine) for their patience and kind assistance in the completion of this work.

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Authors and Affiliations

  1. University of Central Asia, 138 Toktogul Street, Bishkek, 720001, Kyrgyzstan

    Dmytro Zubov

  2. Kryvyi Rih National University, 11 Matusevycha Street, Kryvyi Rih, 50027, Ukraine

    Andrey Kupin

Authors
  1. Dmytro Zubov
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Correspondence to Dmytro Zubov .

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Editors and Affiliations

  1. Zaporizhzhia National University, Zaporizhzhia, Ukraine

    Vadim Ermolayev

  2. Techforce Infotech Pvt. Ltd., Barcelona, Spain

    David Esteban

  3. University of Warmia and Mazury in Olsztyn, Olsztyn, Poland

    Vitaliy Yakovyna

  4. University of Klagenfurt, Klagenfurt, Austria

    Heinrich C. Mayr

  5. V. N. Karazin Kharkiv National University, Kharkiv, Ukraine

    Grygoriy Zholtkevych

  6. Taras Shevchenko National University of Kyiv, Kyiv, Ukraine

    Mykola Nikitchenko

  7. Kherson State University, Kherson, Ukraine

    Aleksander Spivakovsky

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Zubov, D., Kupin, A. (2022). Performance Evaluation of Raspberry Pi 4B Microcomputer: Case Studies on MPICH Cluster, VMware ESXi ARM Fling, and Windows 11 ARM OS. In: Ermolayev, V., et al. Information and Communication Technologies in Education, Research, and Industrial Applications. ICTERI 2021. Communications in Computer and Information Science, vol 1698. Springer, Cham. https://doi.org/10.1007/978-3-031-20834-8_10

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  • DOI: https://doi.org/10.1007/978-3-031-20834-8_10

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-031-20834-8

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