PERFORMANCE ANALYSIS OF THE SUPERCOMPUTER BASED ON RASPBERRY PI NODES

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Keywords:

Mobile Arm processor; Raspberry Pi supercomputer cluster; Performance analysis.

Abstract

In this paper, a new Raspberry PI supercomputer cluster architecture is proposed. Generally, to gain speed at petaflops and exaflops, typical modern supercomputers based on 2009-2018 computing technologies must consume between 6 MW and 20 MW of electrical power, almost all of which is converted into heat, requiring high cost for cooling technology and Cooling Towers. The management of heat density has remained a key issue for most centralized supercomputers. In our proposed architecture, supercomputers with highly energy-efficient mobile ARM processors are a new choice as it enables them to address performance, power, and cost issues. With ARM’s recent introduction of its energy-efficient 64-bit CPUs targeting servers, Raspberry Pi cluster module-based supercomputing is now within reach. But how is the performance of supercomputers-based mobile multicore processors? Obtained experimental results reported on the proposed approach indicate the lower electrical power and higher performance in comparison with the previous approaches.

References

[1]. Victor Tangermann. “The Eight most powerful supercomputers in the world”. September 28th, 2017.

[2]. Greenhill, David. "SWaP Space Watts and Power" (PDF). US EPA Energystar. Retrieved 14 November 2013.

[3]. Girish Kumar Patnaik et. al. “Green Computing Metrics, Methods and Models”. International Journal of Engineering Research & Technology (IJERT). ISSN: 2278-0181. Vol. 3 Issue 3, March – 2014.

[4]. “Mont-Blanc. European Modular and Power-Efficient HPC Processor”. Copyright 2011 - 2020 © All Rights Reserved

[5]. “Scalable clusters make HPC R&D easy as Raspberry Pi”. Bitscope.com/cluster

[6]. Gerald Venza. “Building the world’s largest Raspberry Pi cluster”.

[7]. www.pidramble.com/wiki/benchmarks/microsd-cards.

[8]. Nikhil Jain et.al. “Predicting the Performance Impact of Different Fat-Tree Configurations”. Lawrence Livermore National Laboratory.

[9]. Tomohiro Inoue, Fujitsu Limited. “The 6D Mesh/Torus Interconnect of K Computer”.

[10]. G. Bolch, S. Greiner, H. de Meer, and K. S. Trivedi, “Queueing Networks and Markov Chains ”, John Wiley, 2nd edition, 2006.

[11]. Norhazlina Hamid, Robert John Walters, Gary Brian Wills. “An Analytical Model of Multi-Core Multi-Cluster Architecture (MCMCA)”. Open Journal of Cloud Computing (OJCC) Volume 2, Issue 1, 2015. ISSN 2199-1987.

[12]. Xiaoyue Pan. “Performance Modeling of Multicore Systems”. ISSN 1651-6214 ISBN 978-91-554-9451-3.

[13]. Murata, T.: “Petri nets: properties, analysis, and applications”, Proceedings of IEEE, 77 (4), 1989, 541-580.

[14]. Falko Bause, Pieter S. Kritzinger, “Stochastic Petri Nets”. Bause and Kritzinger, 2002.

[15]. M. Ajmone Marsan, Gianfranco Balbo, Gianni Conte, Susanna Donatelli, Giuliana Franceschinis, “Modelling with generalized stochastic Petri nets”. Università degli Studi di Torino.

[16]. Viktor Mashkov & Jiri Barilla & Pavel Similar. “Applying Petri Nets to Modeling of Many-Core Processor Self-Testing when Tests are Performed Randomly”. J Electron Test (2013).

[17]. Mark D. Hill, University of Wisconsin-Madison Michael R. Marty, Google. “Amdahl’s Law in the Multicore Era”.

[18]. Christina Delimitrou, Christos Kozyrakis. “Amdahl’s Law for Tail Latency”. August 2018 | Vol. 61| No. 8| Communications of the ACM.

[19]. Surya Narayanan Natarajan. “Modeling performance of serial and parallel sections of multi-threaded programs in many core era”. pr´epar´ee `a l’unit´e de recherche INRIA – Bretagne Atlantique Institut National de Recherche en Informatique et Automatique Composante Universitaire (ISTIC).

[20]. Philip J. et. al. “Performance analysis of single-board computer clusters”. Future Generation Computer Systems. 102 (2020) 278-291. ELSEVIER.

[21]. Gareth Halfaceree. “Benchmarking the Raspberry Pi 3 B+”. Mar 14, 2018.

[22]. Roy Longbottom, UK Government. “Raspberry Pi 4B 32 Bit Benchmarks”. Technical Report. June 2019.

[23]. https://www.pidramble.com/wiki/benchmarks/power-consumption.

[24]. Lucy Hattersley. “Raspberry Pi 4 vs Raspberry Pi 3B+”. https://magpi.raspberrypi.org/articles/raspberry-pi-4-vs-raspberry-pi-3b-plus

[25]. “Raspberry Pi 4 vs Raspberry Pi 3B+,” The MagPi magazine. https://magpi.raspberrypi.org/articles/raspberry-pi-4-vs-raspberry-pi-3b-plus.

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Published

10-05-2021

How to Cite

Hai. “PERFORMANCE ANALYSIS OF THE SUPERCOMPUTER BASED ON RASPBERRY PI NODES”. Journal of Military Science and Technology, no. 72A, May 2021, pp. 76-86, https://ojs.jmst.info/index.php/jmst/article/view/30.

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Research Articles