Performance analysis of single board computer clusters

Basford, P. J., Johnston, S. J., Perkins, C. S. , Garnock-Jones, T., Tso, F. P., Pezaros, D. , Mullins, R. D., Yoneki, E., Singer, J. and Cox, S. J. (2019) Performance analysis of single board computer clusters. Future Generation Computer Systems, (doi:10.1016/j.future.2019.07.040) (In Press)

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Abstract

The past few years have seen significant developments in Single Board Computer (SBC) hardware capabilities. These advances in SBCs translate directly into improvements in SBC clusters. In 2018 an individual SBC has more than four times the performance of a 64-node SBC cluster from 2013. This increase in performance has been accompanied by increases in energy efficiency (GFLOPS/W) and value for money (GFLOPS/$). We present systematic analysis of these metrics for three different SBC clusters composed of Raspberry Pi 3 Model B, Raspberry Pi 3 Model B+ and Odroid C2 nodes respectively. A 16-node SBC cluster can achieve up to 60 GFLOPS, running at 80 W. We believe that these improvements open new computational opportunities, whether this derives from a decrease in the physical volume required to provide a fixed amount of computation power for a portable cluster; or the amount of compute power that can be installed given a fixed budget in expendable compute scenarios. We also present a new SBC cluster construction form factor named Pi Stack; this has been designed to support edge compute applications rather than the educational use-cases favoured by previous methods. The improvements in SBC cluster performance and construction techniques mean that these SBC clusters are realising their potential as valuable developmental edge compute devices rather than just educational curiosities.

Item Type:Articles
Status:In Press
Refereed:Yes
Glasgow Author(s) Enlighten ID:Tso, Dr Fung Po and Perkins, Dr Colin and Pezaros, Dr Dimitrios and Garnock-Jones, Dr Anthony and Singer, Dr Jeremy
Authors: Basford, P. J., Johnston, S. J., Perkins, C. S., Garnock-Jones, T., Tso, F. P., Pezaros, D., Mullins, R. D., Yoneki, E., Singer, J., and Cox, S. J.
College/School:College of Science and Engineering > School of Computing Science
Journal Name:Future Generation Computer Systems
Publisher:Elsevier
ISSN:0167-739X
ISSN (Online):1872-7115
Published Online:22 July 2019
Copyright Holders:Copyright © 2019 The Authors
First Published:First published in Future Generation Computer Systems 2019
Publisher Policy:Reproduced under a Creative Commons License

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