Intel® Cilk Plus Software Development Kit

Efficient Parallelization

Document

 

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

  • Entwickler
  • Linux*
  • C/C++
  • Fortran
  • Experten
  • Intel® C++-Compiler
  • Intel® C++ Composer XE
  • Intel® Composer XE
  • Intel® Fortran Compiler
  • Intel® Fortran Composer XE
  • Intel® Threading Building Blocks
  • Intel® Cilk Plus Software Development Kit
  • OpenMP*
  • Intel® Many Integrated Core Architektur
  • Optimierung
  • Parallel Computing
  • 高效并行化

    Efficient Parallelization Document

    高效并行化文档

    面向英特尔® 集成众核架构的编译器方法

    高效并行化

    概述

    本章介绍并行化。其中有各种并行化方法与资源的链接以及如何获取最佳并行化性能的技巧。

  • Entwickler
  • Linux*
  • C/C++
  • Fortran
  • Experten
  • Intel® C++-Compiler
  • Intel® C++ Composer XE
  • Intel® Composer XE
  • Intel® Fortran Compiler
  • Intel® Fortran Composer XE
  • Intel® Threading Building Blocks
  • Intel® Cilk Plus Software Development Kit
  • OpenMP*
  • Intel® Many Integrated Core Architektur
  • Optimierung
  • Parallel Computing
  • 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++
  • Fortgeschrittene
  • Intel® C++-Compiler
  • Intel® Parallel Composer
  • Intel® Parallel Studio
  • Intel® Parallel Studio XE
  • Intel® Cilk Plus Software Development Kit
  • Intel® Parallel Debugger Extension for Microsoft Visual Studio
  • OpenMP*
  • Debugging
  • Parallel Computing
  • 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.

    Intel® Cilk Plus Software Development Kit abonnieren