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Autor(en): 
  • Ruud Van Der Pas
  • Christian Terboven
  • Eric Stotzer
  • Using OpenMP-The Next Step: Affinity, Accelerators, Tasking, and SIMD 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 7-14 Tagen versandfertig
    Veröffentlichung:  Oktober 2017  
    Genre:  EDV / Informatik 
     
    computer science / COMPUTERS / Computer Science / COMPUTERS / Programming / Parallel / Grid & parallel computing / Grid and parallel computing
    ISBN:  9780262534789 
    EAN-Code: 
    9780262534789 
    Verlag:  MIT Press 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 229 mm / B 203 mm / D 22 mm 
    Gewicht:  756 gr 
    Seiten:  392 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    A guide to the most recent, advanced features of the widely used OpenMP parallel programming model, with coverage of major features in OpenMP 4.5.

    This book offers an up-to-date, practical tutorial on advanced features in the widely used OpenMP parallel programming model. Building on the previous volume, Using OpenMP: Portable Shared Memory Parallel Programming (MIT Press), this book goes beyond the fundamentals to focus on what has been changed and added to OpenMP since the 2.5 specifications. It emphasizes four major and advanced areas: thread affinity (keeping threads close to their data), accelerators (special hardware to speed up certain operations), tasking (to parallelize algorithms with a less regular execution flow), and SIMD (hardware assisted operations on vectors).

    As in the earlier volume, the focus is on practical usage, with major new features primarily introduced by example. Examples are restricted to C and C++, but are straightforward enough to be understood by Fortran programmers. After a brief recap of OpenMP 2.5, the book reviews enhancements introduced since 2.5. It then discusses in detail tasking, a major functionality enhancement; Non-Uniform Memory Access (NUMA) architectures, supported by OpenMP; SIMD, or Single Instruction Multiple Data; heterogeneous systems, a new parallel programming model to offload computation to accelerators; and the expected further development of OpenMP.

      



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