Performance analysis of single board computer clusters
Performance analysis of single board computer clusters
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DOI：
10.1016/j.future.2019.07.040
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发表时间：
2020-01-01
影响因子：
7.5
通讯作者：
Cox, Simon J.
中科院分区：
文献类型：
--
作者：
Basford, Philip J.;Johnston, Steven J.;Cox, Simon J.
在过去的几年中，单板计算机(SBC)的硬件功能有了显著的发展。SBCS的这些进步直接转化为SBC集群的改进。2018年，单个SBC的性能是2013年节点SBC集群的四倍多。在业绩提高的同时，能源效率(GFLOPS/W)和物有所值(GFLOPS/美元)也有所提高。我们对三个不同的SBC集群分别由Raspberry PI 3 Model B、Raspberry PI 3 Model B+和Odroid C2节点组成的这些度量进行了系统分析。一个16节点的SBC集群可以实现高达60 GFLOPS，运行功率为80W。我们认为，这些改进带来了新的计算机会，无论这是因为为便携式集群提供固定数量的计算能力所需的物理容量的减少，还是源于在可消耗性计算场景中给定固定预算时可以安装的计算能力的数量。我们还提出了一种名为PI Stack的新的SBC集群构建形式因子；它被设计为支持边缘计算应用程序，而不是以前方法所偏爱的教育用例。SBC集群性能和构建技术的改进意味着，这些SBC集群正在实现其作为有价值的开发边缘计算设备的潜力，而不仅仅是教育方面的新奇事物。(C)2019年提交人。爱思唯尔出版公司(Elsevier B.V.)
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 80W. 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. (C) 2019 The Authors. Published by Elsevier B.V.