A low-cost computer cluster for high-performance computing education

Pfalzgraf, Aaron M.; Driscoll, Joseph A.

doi:10.1109/eit.2014.6871791

Cited by 31 publications

(15 citation statements)

References 8 publications

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“…Pfalzgraf and Driscoll [14] assembled in 2014 at the Bradley University a cluster of 25 Raspberry Pi nodes and used a single 600 W PC power supply to power the cluster nodes. This work does not provide any power measurements results.…”

Section: Related Workmentioning

confidence: 99%

Lessons Learned From Implementing a Scalable PAAS Service by Using Single Board Computers

Baun

2017

IJCCSA

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Section: Related Workmentioning

confidence: 99%

Lessons Learned From Implementing a Scalable PAAS Service by Using Single Board Computers

Baun

2017

IJCCSA

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“…In those research Beowulf cluster computing by using the Pentium 3 for the master nodes and Pentium 2 for the slaves nodes, and the student learned about HPC thourgh the material provided in course [8]. The newest trend of HPC lesson is shown in 2014, where the course is likely to implement the low cost system to perform the high performance computing for solving the simple mathematical process [9] [10], where these lesson use the embedded system to build a clustered computer for solving the simple computation such as matrices calculation. The timeline of how HPC has been known and implemented shown in Figure 1.…”

Section: Introductionmentioning

confidence: 99%

An Embedded System for applying High Performance Computing in Educational Learning Activity

Rachmawan

Fahmi

Widodo

et al. 2016

emitter

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HPC (High Performance Computing) has become more popular in the last few years. With the benefits on high computational power, HPC has impact on industry, scientific research and educational activities. Implementing HPC as a curriculum in universities could be consuming a lot of resources because well-known HPC system are using Personal Computer or Server. By using PC as the practical moduls it is need great resources and spaces. This paper presents an innovative high performance computing cluster system to support education learning activities in HPC course with small size, low cost, and yet powerful enough. In recent years, High Performance computing usually implanted in cluster computing and require high specification computer and expensive cost. It is not efficient applying High Performance Computing in Educational research activiry such as learning in Class. Therefore, our proposed system is created with inexpensive component by using Embedded System to make High Performance Computing applicable for leaning in the class. Students involved in the construction of embedded system, built clusters from basic embedded and network components, do benchmark performance, and implement simple parallel case using the cluster. In this research we performed evaluation of embedded systems comparing with i5 PC, the results of our embedded system performance of NAS benchmark are similar with i5 PCs. We also conducted surveys about student learning satisfaction that with embedded system students are able to learn about HPC from building the system until making an application that use HPC system.

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“…None of them are instrumented for per-node power measurements like ours is. Pfalzgraf and Driscoll [35] create a 25-node Raspberry Pi cluster, but do not provide power or FLOPS results. Kiepert [36] builds a 32-node Raspberry Pi cluster.…”

Section: Raspberry Pi Clustersmentioning

confidence: 99%

A Raspberry Pi Cluster Instrumented for Fine-Grained Power Measurement

2016

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Abstract: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.

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A low-cost computer cluster for high-performance computing education

Cited by 31 publications

References 8 publications

Lessons Learned From Implementing a Scalable PAAS Service by Using Single Board Computers

Lessons Learned From Implementing a Scalable PAAS Service by Using Single Board Computers

An Embedded System for applying High Performance Computing in Educational Learning Activity

A Raspberry Pi Cluster Instrumented for Fine-Grained Power Measurement

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