1. bookVolume 25 (2020): Issue 2 (December 2020)
Journal Details
License
Format
Journal
First Published
16 Apr 2015
Publication timeframe
2 times per year
Languages
English
access type Open Access

Design of Raspberry PI Parallel Processor

Published Online: 17 Dec 2020
Page range: 63 - 74
Journal Details
License
Format
Journal
First Published
16 Apr 2015
Publication timeframe
2 times per year
Languages
English

As data centers have increased in size, there has been a need to create clusters out of cheaper, more affordable commodity parts that can easily be replaced upon failure, and that create more affordable data centers overall. However, such large clusters are still outside of feasibility for individuals and small businesses. It is a worthwhile exercise to see if much smaller clusters could be created for such applications, and to compare their performance / price measure to that of the previous traditional data centers. For this paper, such a cluster is created using Raspberry Pis which are small-sized, single-board computers. A data sharing model is built in Python using message passing interface (MPI) that ran on the cluster of the four Raspberry Pis. So as to evaluate the performance of the system, some greedy algorithms are created. During the implementation process, previously unknown skills, including how to create a cluster, programming the infrastructure are learnt.

Keywords

Cloutier, M., Paradis, C., & Weaver, V. (2016). A Raspberry Pi cluster instrumented for fine-grained power measurement. Electronics, Vol. 5, No. 4.Search in Google Scholar

Jacobus, B., & Podeschi, R. (2017). Low-cost cluster computing using Raspberry Pi with mathematica. Proceedings of the EDSIG Conference, USA.Search in Google Scholar

Matthews, S. et al. (2018). Portable parallel computing with the Raspberry Pi. Proceedings of the 49th ACM Technical Symposium on Computer Science Education, USA.Search in Google Scholar

Mitrović, D., Marković, D., & Ranđić, S. (2018). Raspberry Pi module clustering and cluster application capabilities. 7th International Scientific Conference Technics and Informatics in Education, Serbia.Search in Google Scholar

Saffran, J. et al. (2016). A low-cost energy-efficient Raspberry Pi cluster for data mining algorithms. European Conference on Parallel Processing, France.Search in Google Scholar

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