• DocumentCode
    1298769
  • Title

    Transformer: A New Paradigm for Building Data-Parallel Programming Models

  • Author

    Wang, Peng ; Meng, Dan ; Han, Jizhong ; Zhan, Jianfeng ; Tu, Bibo ; Shi, Xiaofeng ; Wan, Le

  • Author_Institution
    Inst. of Comput. Technol., Chinese Acad. of Sci., Beijing, China
  • Volume
    30
  • Issue
    4
  • fYear
    2010
  • Firstpage
    55
  • Lastpage
    64
  • Abstract
    Cloud computing drives the design and development of diverse programming models for massive data processing. the transformer programming framework aims to facilitate the building of diverse data-parallel programming models. transformer has two layers: a common runtime system and a model-specific system. using transformer, the authors show how to implement three programming models: dryad-like data flow, MapReduce, and All-Pairs.
  • Keywords
    parallel programming; All-Pairs processing; MapReduce processing; cloud computing; common runtime system; data-parallel programming models; dryad-like data flow processing; model-specific system; transformer programming framework; Computational modeling; Data models; Libraries; Load modeling; Programming; Receivers; Runtime; All-Pairs; MapReduce; actor model; cloud computing; data flow; data intensive computing; programming model;
  • fLanguage
    English
  • Journal_Title
    Micro, IEEE
  • Publisher
    ieee
  • ISSN
    0272-1732
  • Type

    jour

  • DOI
    10.1109/MM.2010.75
  • Filename
    5551001
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1298769