Kit de développement logiciel Intel® Cilk Plus

Efficient Parallelization

Compiler Methodology for Intel® MIC Architecture

Efficient Parallelization

Overview

This chapter covers topics in parallelization. There are links to various parallelization methods and resources along with tips and techniques for getting optimal parallel performance.

Goals

In this chapter, you will learn techniques for the Intel OpenMP* runtime library provided with the Intel compilers, Intel® MPI, Intel® Cilk™ Plus, and Intel® Threading Building Blocks (Intel® TBB).

  • Développeurs
  • Linux*
  • C/C++
  • Fortran
  • Avancé
  • Compilateur Intel® C++
  • Intel® C++ Composer XE
  • Intel® Composer XE
  • Compilateur Intel® Fortran
  • Intel® Fortran Composer XE
  • Intel® Threading Building Blocks
  • Kit de développement logiciel Intel® Cilk Plus
  • OpenMP*
  • Intel® Many Integrated Core Architecture
  • Optimisation
  • Informatique parallèle
  • Intel® Parallel Debugger Extension

    This whitepaper provides tips and tricks on how to best take advantage of the additional insight into parallel data constructs the Intel® Parallel Debugger Extension brings to the Microsoft Visual Studio* debug environment. In doing so it provides a high-level overview of the Intel® Parallel Debugger Extension for Microsoft Visual Studio* and the key features that enhance the debug experience.
  • Microsoft Windows* (XP, Vista, 7)
  • C/C++
  • Intermédiaire
  • Compilateur Intel® C++
  • Intel® Parallel Composer
  • Intel® Parallel Studio
  • Intel® Parallel Studio XE
  • Kit de développement logiciel Intel® Cilk Plus
  • Intel® Parallel Debugger Extension for Microsoft Visual Studio
  • OpenMP*
  • Débogage
  • Informatique parallèle
  • SIGCSE2012 Workshop 23 Parallelism and Concurrency for Data-Structures & Algorithms courses

    This workshop is inspired by Dan Grossman’s SIGCSE 2011 workshop on Data Abstractions. We review C/C++ conversions of the original Java-based materials and will include material from the Parallel Algorithms course at Kent State. The workshop will appeal to data-structure and algorithms course instructors. Workshop topics will include divide and conquer approaches, work sharing concepts, and a scoped locking scheme in OpenMP for C++ classes.

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