Auto-vectorization

Vectorization Essentials

 

Compiler Methodology for Intel® MIC Architecture

Vectorization Essentials

Overview

This chapter covers topics in vectorization. Vectorization is a form of data-parallel programming. In this, the processor performs the same operation simultaneously on N data elements of a vector ( a one-dimensional array of scalar data objects such as floating point objects, integers, or double precision floating point objects).

  • Développeurs
  • Linux*
  • C/C++
  • Fortran
  • Avancé
  • Compilateur Intel® C++
  • Compilateur Intel® Fortran
  • OpenMP*
  • Auto-vectorization
  • Intel® Xeon Phi™ Coprocessor
  • vectorization
  • compiler methodology
  • MIC
  • Intel® Cilk™ Plus
  • openmp
  • Intel® Many Integrated Core Architecture
  • 矢量化要点

    面向英特尔® MIC 架构的编译器方法

    矢量化要点

    概述

    本章节涵盖了关于矢量化的一些课题。矢量化是一种数据并行编程形式。处理器在矢量的 N 个数据元素上同时执行相同的操作(标量数据对象的一维数组,如浮点对象、整数或双精度浮点对象)。

  • Développeurs
  • Linux*
  • C/C++
  • Fortran
  • Avancé
  • Compilateur Intel® C++
  • Compilateur Intel® Fortran
  • Auto-vectorization
  • Intel® Many Integrated Core Architecture
  • -Mr Compiler, may I help you with the loop vectorization? -Not a disservice, please.

    Any parent knows the simple rule: "Never help a child with a task he can succeed at himself. Otherwise you don't make any good for the kid,  for you and for the whole planet".
    While a compiler is not a child (actually it is - because Intel  C/C++ Compiler is less than 16 years  old yet), the rule is fully applicable to it as well.



    To prove it let's look at the following simple code from the open source OpenCV library.

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