A Raspberry Pi Cluster Instrumented for Fine-Grained Power Measurement

被引:31
作者
Cloutier, Michael F. [1 ]
Paradis, Chad [1 ]
Weaver, Vincent M. [1 ]
机构
[1] Univ Maine, Elect & Comp Engn, Orono, ME 04469 USA
关键词
Raspberry Pi; embedded supercomputers; GFLOPS/W; cluster construction; power measurement; ARM; PERFORMANCE; X86;
D O I
10.3390/electronics5040061
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页数:19
相关论文
共 35 条
[1]   Affordable and Energy-Efficient Cloud Computing Clusters: The Bolzano Raspberry Pi Cloud Cluster Experiment [J].
Abrahamsson, Pekka ;
Helmer, Sven ;
Phaphoom, Nattakarn ;
Nicolodi, Lorenzo ;
Preda, Nick ;
Miori, Lorenzo ;
Angriman, Matteo ;
Rikkilae, Juha ;
Wang, Xiaofeng ;
Hamily, Karim ;
Bugoloni, Sara .
2013 IEEE FIFTH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING TECHNOLOGY AND SCIENCE (CLOUDCOM), VOL 2, 2013, :170-175
[2]  
Almasi G, 2008, IBM J RES DEV, V52, P199
[3]  
[Anonymous], STREAM: Sustainable memory bandwidth in high performance computers
[4]  
[Anonymous], P 11 WORKSH PAR DIST
[5]   Towards green data centers: A comparison of x86 and ARM architectures power efficiency [J].
Aroca, Rafael Vidal ;
Garcia Goncalves, Luiz Marcos .
JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING, 2012, 72 (12) :1770-1780
[6]  
Balakrishnan N., 2012, THESIS
[7]  
Bedard D., 2009, POWERMON
[8]  
Blem E, 2013, INT S HIGH PERF COMP, P1, DOI 10.1109/HPCA.2013.6522302
[9]   Iridis-pi: a low-cost, compact demonstration cluster [J].
Cox, Simon J. ;
Cox, James T. ;
Boardman, Richard P. ;
Johnston, Steven J. ;
Scott, Mark ;
O'Brien, Neil S. .
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, 2014, 17 (02) :349-358
[10]  
Dongarra J., 2012, P 2012 IEEE C HIGH P