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Samples for Intel® C++ Composer XE

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Intel® C++ compiler is an industry-leading C/C++ compiler, including optimization features like auto-vectorization and auto-parallelization, OpenMP*, and Intel® Cilk™ Plus multithreading capabilities; plus the highly optimized performance libraries.

We have created a list of articles with samples explaining the features in detail and how or when to use in the source code. There are:

By installing or copying all or any part of the sample source code, you agree to the terms of the Intel(R) Sample Source Code License Agreement.

Auto-vectorization articles and samples
Article NameDescriptionDownload
A Guide to Auto-vectorization with Intel® C++ CompilersThis article provides guidelines for enabling Intel C++ compiler auto-vectorization using the sample source code; it targets the Intel® processors or compatible non-Intel processors that support SIMD instructions such as Intel® Streaming SIMD Extensions (Intel® SSE).Source Code in C/C++

Intel® Cilk™ Plus
Article NameDescriptionDownload
Monte Carlo Sample

The Monte Carlo sample code is updated with "Intel® Cilk™ Plus" language feature.  The Monte Carlo algorithm is implemented with:

  • serial loops
  • Intel Cilk Plus' cilk_for keyword
  • Intel Cilk Plus' array notations to allow vectorization for the SIMD instruction
  • using both cilk_for and the array notations

The sample demonstrates the great performance improvement with very little coding changes through both data-parallelism and task-parallelism.

The Monte Carlo Sample Code in C/C++
AOBench Sample

The AOBench sample is another example implemented with "Intel® Cilk™ Plus" language feature.  The Ambient Occlusion algorithm is implemented with:

  • serial loops
  • using Intel Cilk Plus' cilk_for keyword to implement parallelism
  • using Intel Cilk Plus' array notations to allow vectorization for the SIMD instruction
  • using both cilk_for and the array notations

The sample demonstrates great performance with very little coding changes through both data-parallelism and task-parallelism.

AOBench Sample code in C/C++
Black-Scholes Sample

The Black-Scholes sample is updated with the Intel® Cilk™ Plus language feature. The code of black-scholes call/put calculation is implemented in

  • a serial version
  • one using Intel Cilk Plus' elemental functions to allow vectorization of a user-defined function

The sample demonstrates great performance with very little coding changes through both data-parallelism.

Black-Scholes Source code in C/C++
Sepia Filter Sample

This article explains how to improve the performance of a graphics processing program using Intel Cilk Plus.  The sample demonstrates the performance increase using the three new keywords to implement task parallelism and an array notation syntax to express data parallelism. 

SepiaFilter Sample Source Code in C/C++

Building Open Source Applications using Intel C++ Compiler
Article NameDescriptionPlatforms
How to Building POV-Ray* with Intel C++ Compiler on WindowsThe article provided detail instructions on building Povray* using the Intel® C++ Compiler for Windows.
Version information
  • Povray* beta version 3.7
  • Intel(R) C++ for Windows: 11.0
Windows
Building Boost C++ Libraries with Intel® C++ Compiler on Windows XPBoost is a set of libraries for the C++ language, visit www.boost.org for more information. The article provides detail instructions on how to build Boost* library with Intel C++ Compiler on Windows.
Version information
  • Boost: v1.39.0
  • Intel C++ Compiler for Windows: 11.1
Windows
Building Open MPI* with the Intel compilersThe article is to help Intel® compiler customers build and use the Open MPI* library with Intel C++ and Fortran Compilers for Linux and OS X.
Version information
  • Open MPI: 1.2
  • Intel(R) C++ and Fortran Compilers for Linux* or Mac OS* X: 10.0
Linux*, OS X*
Building UPC* to utilize the Intel C++ CompilerThe Berkeley* Unified Parallel C* (UPC) is a programming language that adds parallelization extensions to the C language. The article explains how to build UPC* compiler with Intel C++ Compiler and configure it for use with symmetric multiprocessing (SMP) machines.
Version information
  • UPC: version 2.4.0
  • Intel(R) C++ Compiler for Linux*: 10.0
Linux
Building Quantlib with Intel C++ CompilerQuantlib is a free/open-source library for modeling, trading, and risk management in real-life writting in C++. The article explains how to configure and build the Quantlib* library (http://quantlib.org/) and an example provided with Quantlib.
Version information
  • Quantlib: Quantlib-0.3.13.tar.gz
  • Boost*: boost_1_33_1
  • Intel(R) C++ Compiler for Linux*: 10.0
Linux
Building Xerces with Intel C++ CompilerThe article describes how to build the Xerces-C++ with the Intel® C++ Compiler for Linux*
Version information
  • Xerces: 2.7.0
  • Intel(R) C++ Compiler for Linux*: 10.0
Linux
Building FFTW* With the Intel CompilersThe FFTW library is used for high performance computation of the Discrete Fourier Transform (DFT). The article describles how to build the FFTW* library on Linux* using Intel C++ Compiler for Linux.
Version information
  • FFTW* library v3.1.2
  • Intel(R) C++ Compiler for Linux*: 10.0
Linux
Building PGPLOT* with the Intel compilersPGPLOT is a library for creating two-dimensional plots and graphs. The article provides instructions on how to build the PGPLOT* graphics library using Intel C++ and Fortran Compilers for Linux.
Version information
  • PGPLOT* graphics library v5.2.2
  • Intel(R) C++ and Fortran Compilers for Linux*: 10.x
Linux
Building WRF v2.x with the Intel compilersThe Weather Research and Forecasting (WRF) Model (http://wrf-model.org/index.php) is a next-generation mesoscale numerical weather prediction system designed to serve both operational forecasting and atmospheric research needs. The article is created to help users of WRF make use of the Intel C++ and Fortran compiler.
Version information
  • WRF: version 2.2 and 2.2.1
  • Intel(R) C++ and Fortran Compilers for Linux* or Mac OS* X: 10.x, 11.x
Linux
Building WRF v3.1.1 with the Intel compilersThe article is created to help users of WRF v3.1.1 make use of the Intel C++ and Fortran compiler.
Version information
  • WRF: version 3.1.1
  • Intel(R) C++ and Fortran Compilers for Linux* or Mac OS* X: 11.1
Linux
Building the HPCC* benchmark with Intel C++ and Fortran CompilersThe HPC Challenge (HPCC) benchmark is used to evaluate and test a wide variety of performance parameters for high-performance computing system. The article provides instructions on how to build the HPCC* benchmark.
Version information
  • HPCC: 1.0.0
  • Intel(R) C++ and Fortran Compilers for Linux* or Mac OS* X: 10.0
  • Intel(R) Math Kernel Library: 9.1
Linux, OS X
Building HDF5* with Intel® compilersThe article provides instructions on how to build and use the HDF5 library with Intel C++ and Fortrna Compilers on Linux* or OS X*. HDF5 (http://www.hdfgroup.org/HDF5/) is the latest generation of the HDF libraries, a general purpose library and associated file formats for storing and sharing scientific data.
Version information
  • HDF5 1.8.9
  • Intel C++ and Fortran Compiler for Linux* or Mac OS* X: 13.0 Update 1
Linux, OS X
  • Developers
  • Linux*
  • Microsoft Windows* (XP, Vista, 7)
  • OS X*
  • C/C++
  • Intermediate
  • Intel® C++ Composer XE
  • Intel® Advanced Vector Extensions
  • Intel® Streaming SIMD Extensions
  • OpenMP*
  • Optimization
  • Parallel Computing
  • Vectorization
  • URL
  • Code Sample

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