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Computer Research and Modeling, 2015, Volume 7, Issue 3, Pages 581–586
DOI: https://doi.org/10.20537/2076-7633-2015-7-3-581-586
(Mi crm222)
 

This article is cited in 1 scientific paper (total in 1 paper)

СЕКЦИОННЫЕ ДОКЛАДЫ

A cpu benchmarking characterization of ARM based processors

R. G. Reed, M. A. Cox, T. Wrigley, B. Mellado

School of Physics, University of the Witwatersrand. 1 Jan Smuts Avenue, Braamfontein, Johannesburg, 2000, South Africa
Full-text PDF (426 kB) Citations (1)
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Abstract: Big science projects are producing data at ever increases rates. Typical techniques involve storing the data to disk, after minor filtering, and then processing it in large computer farms. Data production has reached a point where on-line processing is required in order to filter the data down to manageable sizes. A potential solution involves using low-cost, low-power ARM processors in large arrays to provide massive parallelisation for data stream computing (DSC). The main advantage in using System on Chips (SoCs) is inherent in its design philosophy. SoCs are primarily used in mobile devices and hence consume less power while maintaining relatively good performance. A benchmarking characterisation of three different models of ARM processors will be presented.
Keywords: High data throughput, Computing, Big Data, ARM System on Chips, Benchmarking.
Received: 30.09.2014
Document Type: Article
UDC: 004.27
Language: English
Citation: R. G. Reed, M. A. Cox, T. Wrigley, B. Mellado, “A cpu benchmarking characterization of ARM based processors”, Computer Research and Modeling, 7:3 (2015), 581–586
Citation in format AMSBIB
\Bibitem{ReeCoxWri15}
\by R.~G.~Reed, M.~A.~Cox, T.~Wrigley, B.~Mellado
\paper A cpu benchmarking characterization of ARM based processors
\jour Computer Research and Modeling
\yr 2015
\vol 7
\issue 3
\pages 581--586
\mathnet{http://mi.mathnet.ru/crm222}
\crossref{https://doi.org/10.20537/2076-7633-2015-7-3-581-586}
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  • https://www.mathnet.ru/eng/crm/v7/i3/p581
  • This publication is cited in the following 1 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Computer Research and Modeling
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    Abstract page:224
    Full-text PDF :150
    References:44
     
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