A Raspberry Pi Cluster Instrumented for Fine-Grained Power Measurement

Power consumption has become an increasingly important metric when building large supercomputing clusters. One way to reduce power usage in large clusters is to use low-power embedded processors rather than the more typical high-end server CPUs (central processing units). We investigate various powe...

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Bibliographic Details
Main Authors: Michael F. Cloutier, Chad Paradis, Vincent M. Weaver
Format: Article
Language:English
Published: MDPI AG 2016-09-01
Series:Electronics
Subjects:
Online Access:http://www.mdpi.com/2079-9292/5/4/61
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spelling doaj-82bcfdac7232486a8aa6c77654afc5972020-11-24T23:16:28ZengMDPI AGElectronics2079-92922016-09-01546110.3390/electronics5040061electronics5040061A Raspberry Pi Cluster Instrumented for Fine-Grained Power MeasurementMichael F. Cloutier0Chad Paradis1Vincent M. Weaver2Electrical and Computer Engineering, University of Maine, Orono, ME 04469, USAElectrical and Computer Engineering, University of Maine, Orono, ME 04469, USAElectrical and Computer Engineering, University of Maine, Orono, ME 04469, USAPower consumption has become an increasingly important metric when building large supercomputing clusters. One way to reduce power usage in large clusters is to use low-power embedded processors rather than the more typical high-end server CPUs (central processing units). We investigate various power-related metrics for seventeen different embedded ARM development boards in order to judge the appropriateness of using them in a computing cluster. We then build a custom cluster out of Raspberry Pi boards, which is specially designed for per-node detailed power measurement. In addition to serving as an embedded cluster testbed, our cluster’s power measurement, visualization and thermal features make it an excellent low-cost platform for education and experimentation.http://www.mdpi.com/2079-9292/5/4/61Raspberry Piembedded supercomputersGFLOPS/Wcluster constructionpower measurement
collection DOAJ
language English
format Article
sources DOAJ
author Michael F. Cloutier
Chad Paradis
Vincent M. Weaver
spellingShingle Michael F. Cloutier
Chad Paradis
Vincent M. Weaver
A Raspberry Pi Cluster Instrumented for Fine-Grained Power Measurement
Electronics
Raspberry Pi
embedded supercomputers
GFLOPS/W
cluster construction
power measurement
author_facet Michael F. Cloutier
Chad Paradis
Vincent M. Weaver
author_sort Michael F. Cloutier
title A Raspberry Pi Cluster Instrumented for Fine-Grained Power Measurement
title_short A Raspberry Pi Cluster Instrumented for Fine-Grained Power Measurement
title_full A Raspberry Pi Cluster Instrumented for Fine-Grained Power Measurement
title_fullStr A Raspberry Pi Cluster Instrumented for Fine-Grained Power Measurement
title_full_unstemmed A Raspberry Pi Cluster Instrumented for Fine-Grained Power Measurement
title_sort raspberry pi cluster instrumented for fine-grained power measurement
publisher MDPI AG
series Electronics
issn 2079-9292
publishDate 2016-09-01
description Power consumption has become an increasingly important metric when building large supercomputing clusters. One way to reduce power usage in large clusters is to use low-power embedded processors rather than the more typical high-end server CPUs (central processing units). We investigate various power-related metrics for seventeen different embedded ARM development boards in order to judge the appropriateness of using them in a computing cluster. We then build a custom cluster out of Raspberry Pi boards, which is specially designed for per-node detailed power measurement. In addition to serving as an embedded cluster testbed, our cluster’s power measurement, visualization and thermal features make it an excellent low-cost platform for education and experimentation.
topic Raspberry Pi
embedded supercomputers
GFLOPS/W
cluster construction
power measurement
url http://www.mdpi.com/2079-9292/5/4/61
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