• DocumentCode
    1915497
  • Title

    Tight Coupling of R and Distributed Linear Algebra for High-Level Programming with Big Data

  • Author

    Schmidt, Dan ; Ostrouchov, George ; Wei-Chen Chen ; Patel, Pragati

  • Author_Institution
    Remote Anal. & Visualization Center, Univ. of Tennessee, Knoxville, TN, USA
  • fYear
    2012
  • fDate
    10-16 Nov. 2012
  • Firstpage
    811
  • Lastpage
    815
  • Abstract
    We present a new distributed programming extension of the R programming language. By tightly coupling R to the well-known ScaLAPACK and MPI libraries, we are able to achieve highly scalable implementations of common statistical methods, allowing the user to analyze bigger datasets with R than ever before. Early benchmarks show great optimism for the project and its future.
  • Keywords
    distributed programming; linear algebra; message passing; programming languages; statistical analysis; MPI library; R programming language; ScaLAPACK library; big data; distributed linear algebra; distributed programming; high-level programming; message passing interface; statistical method; Big data; Distributed computing; Large scale analytics; MPI; R; ScaLAPACK;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    High Performance Computing, Networking, Storage and Analysis (SCC), 2012 SC Companion:
  • Conference_Location
    Salt Lake City, UT
  • Print_ISBN
    978-1-4673-6218-4
  • Type

    conf

  • DOI
    10.1109/SC.Companion.2012.113
  • Filename
    6495895
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1915497