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DSIMBench: A Benchmark for Microarray Data Using R

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Big Data Benchmarks, Performance Optimization, and Emerging Hardware (BPOE 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8807))

Abstract

Parallel computing in R has been widely used to analyse microarray data. We have seen various applications using various data distribution and calculation approaches. Newer data storage systems, such as MySQL Cluster and HBase, have been proposed for R data storage; while the parallel computation frameworks, including MPI and MapReduce, have been applied to R computation. Thus, it is difficult to understand the whole analysis workflows for which the tool kits are suited for a specific environment. In this paper we propose DSIMBench, a benchmark containing two classic microarray analysis functions with eight different parallel R workflows, and evaluate the benchmark in the IC Cloud testbed platform.

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Acknowledgment

This research was partially supported by the Innovative R&D Team Support Program of Guangdong Province (NO. 201001D0104726115), China, Johnson & Johnson Pharmaceutical and Research Comp, and Innovative Medicines Initiative (IMI), EU Grant Code 115446.

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Authors and Affiliations

  1. Data Science Institute, William Penney Laboratory, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK

    Shicai Wang, Ioannis Pandis, Ibrahim Emam, David Johnson, Florian Guitton, Axel Oehmichen & Yike Guo

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  1. Shicai Wang
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  2. Ioannis Pandis
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  3. Ibrahim Emam
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  4. David Johnson
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  5. Florian Guitton
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  6. Axel Oehmichen
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  7. Yike Guo
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Corresponding author

Correspondence to Yike Guo .

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Editors and Affiliations

  1. ICT, Chinese Academy of Sciences, Beijing, China

    Jianfeng Zhan

  2. ICT, Chinese Academy of Sciences, Beijing, China

    Rui Han

  3. Shannon (IT) Lab., Huawei, China

    Chuliang Weng

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Wang, S. et al. (2014). DSIMBench: A Benchmark for Microarray Data Using R. In: Zhan, J., Han, R., Weng, C. (eds) Big Data Benchmarks, Performance Optimization, and Emerging Hardware. BPOE 2014. Lecture Notes in Computer Science(), vol 8807. Springer, Cham. https://doi.org/10.1007/978-3-319-13021-7_4

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  • DOI: https://doi.org/10.1007/978-3-319-13021-7_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13020-0

  • Online ISBN: 978-3-319-13021-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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