• DocumentCode
    680231
  • Title

    HPC+Azure environment for bioinformatics applications

  • Author

    Sidhu, Amandeep S. ; Balakrishnan, Suresh Reuben ; Dhillon, Sarinder K.

  • Author_Institution
    Sch. of Eng. & Sci., Curtin Univ., Miri, Malaysia
  • fYear
    2013
  • fDate
    18-21 Dec. 2013
  • Firstpage
    12
  • Lastpage
    15
  • Abstract
    In the past 20 years, huge flow of data, produced by the nonstop rise of computational power has led to a paradigm shift in large scale data processing mechanisms and computing architecture. As a result, human and computational resources are needed to aid data-intensive operations which will cause the high degree of storage and management expenses. An organized and standard approach is important to manage these issues with an architecture that able to scale into the predictable future. Instead of the fastest and largest single computer solution, economical clusters of computers can better manage and process all data. Most of the high-performance computing (HPC) systems need a huge amount of processing power and Windows Azure is capable of providing a huge quantity of processing power on demand. As the Windows HPC server and Windows Azure combine, the cloud and on-premises world are now able to function together. In this paper we explore a HPC+Azure implementation model and demonstrate by running a genome sequence assembly application.
  • Keywords
    bioinformatics; cloud computing; parallel processing; HPC-Azure environment; HPC-Azure implementation model; bioinformatics applications; computational power; computing architecture; data flow; data-intensive operations; high-performance computing systems; large scale data processing mechanisms; paradigm shift; single computer solution; window HPC server; Assembly; Benchmark testing; Cloud computing; Computer architecture; Computers; Servers; Cloud Computing; Microsoft Azure; Windows HPC;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedicine (BIBM), 2013 IEEE International Conference on
  • Conference_Location
    Shanghai
  • Type

    conf

  • DOI
    10.1109/BIBM.2013.6732615
  • Filename
    6732615