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HowTo – HPL Over Intel MPI

This is a step by step procedure of how to run the High Performance Linpack (HPL)benchmark on a Linux cluster using Intel-MPI. This was done on a Linux cluster of 128 nodes running Intel’s Nehalem processor 2.93 MHz with 12GB of RAM on each node.
  • Développeurs
  • Linux*
  • Serveur
  • Bibliothèque Intel® MPI Library
  • Intel® Cluster Ready
  • Code source libre
  • Informatique parallèle

    • Intel Guide for Developing Multithreaded Applications

    The Intel® Guide for Developing Multithreaded Applications covers topics ranging from general advice applicable to any multithreading method to usage guidelines for Intel® software products to API-specific issues.
  • Linux*
  • Microsoft Windows* (XP, Vista, 7)
  • Apple Mac OS X*
  • Serveur
  • Intermédiaire
  • Compilateur Intel® C++
  • Compilateur Intel® Fortran
  • Intel® Parallel Composer
  • Bibliothèque Intel® Integrated Performance Primitives (IPP)
  • Bibliothèque Intel® Math Kernel Library
  • Intel® Parallel Studio
  • Intel® Parallel Studio XE
  • Intel® Parallel Advisor
  • Intel® Parallel Amplifier
  • Amplificateur Intel® VTune™ XE
  • Intel® Inspector XE
  • Intel® Parallel Inspector
  • synchronization
  • Start Here
  • Parallel Programming
  • memory management
  • programming tools
  • Application Threading
  • Active learning of parallel programming
  • Learning Lab
  • Informatique parallèle

    • Configuring Intel® MKL in Microsoft* Visual Studio*

    Intel MKL in Microsoft Visual Studio
  • Développeurs
  • Partenaires
  • Professeurs
  • Étudiants
  • Microsoft Windows* (XP, Vista, 7)
  • Serveur
  • .NET*
  • C#
  • C/C++
  • Fortran
  • Débutant
  • Outils de cluster
  • Intel® Parallel Composer
  • Bibliothèque Intel® Math Kernel Library
  • Intel® C++ Studio XE
  • Intel® Cluster Studio
  • Intel® Cluster Studio XE
  • Intel® Fortran Studio XE
  • Intel® Parallel Studio XE
  • Intel MKL with visual studio
  • Uisng Intel MKL in Microsoft Visual Studio
  • OpenMP*
  • Outils de développement

    • Elemental functions: Writing data parallel code in C/C++ using Intel® Cilk™ Plus

    Intel® Cilk™ Plus provides simple to use language extensions to express data and task-parallelism to the C and C++ language. This article describes one of these programming constructs: “elemental functions”.
  • Linux*
  • Microsoft Windows* (XP, Vista, 7)
  • Apple Mac OS X*
  • C/C++
  • Compilateur Intel® C++
  • Intel® Cilk™ Plus
  • Intel® Parallel Composer
  • Intel® Cilk™ Plus
  • elemental function
  • __declspec(vector)
  • Optimisation

    • Pages

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