• DocumentCode
    1918097
  • Title

    A Platform for Parallel R-based Analytics on Cloud Infrastructure

  • Author

    Patel, Ishan ; Rau-Chaplin, Andrew ; Varghese, Blesson

  • Author_Institution
    Risk Analytics Lab., Dalhousie Univ., Halifax, NS, Canada
  • fYear
    2012
  • fDate
    10-13 Sept. 2012
  • Firstpage
    188
  • Lastpage
    193
  • Abstract
    Analytical workloads abound in application domains ranging from computational finance and risk analytics to engineering and manufacturing settings. In this paper we describe a Platform for Parallel R-based Analytics on the Cloud (P2RAC). The goal of this platform is to allow an Analyst to take a simulation or optimization job (both the code and associated data) that runs on their personal workstations and with minimum effort have them run on large-scale parallel cloud infrastructure. If this can be facilitated gracefully, an Analyst with strong quantitative but perhaps more limited development skills can harness the computational power of the cloud to solve larger analytically problems in less time. P2RAC is currently designed for executing parallel R scripts on the Amazon Elastic Computing Cloud infrastructure. Preliminary results obtained from an experiment confirm the feasibility of the platform.
  • Keywords
    cloud computing; optimisation; parallel processing; Amazon Elastic Computing Cloud infrastructure; P2RAC; analytical workloads; application domains; computational finance; development skills; large-scale parallel cloud infrastructure; optimization job; parallel R scripts; personal workstations; platform for parallel R-based analytics on the cloud; risk analytics; Computational modeling; Libraries; Optimization; Protocols; Snow; Switches; Syntactics; Amazon Cloud Services; Cloud computing; Parallel Analytics; R and Snow;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel Processing Workshops (ICPPW), 2012 41st International Conference on
  • Conference_Location
    Pittsburgh, PA
  • ISSN
    1530-2016
  • Print_ISBN
    978-1-4673-2509-7
  • Type

    conf

  • DOI
    10.1109/ICPPW.2012.27
  • Filename
    6337479