Intel Composer XE 2011 for Linux 單機版 (下載)

Intel compilers and performance libraries for developers interested in application performance
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Intel Composer XE Products:


Intel compilers and performance libraries for developers interested in application performance

Features:



  • Compiler performance leadership. A simple compile can deliver a 20% gain, or more. Use more features, get more performance!

  • Intel C++ is compatible with Visual C++* on Windows* and gcc on Linux*

  • Intel Fortran supports VAX* Fortran and is compatible with Compaq Visual Fortran*

  • Compilers integrate into Visual Studio* on Windows and are compatible with the gnu tool chain
    Intel? MKL offers math highly optimized, threaded math routines. Includes BLAS, LAPACK, ScaLAPACK1, sparse solvers, fast Fourier transforms, vector math, and more.

  • Intel? IPP is an extensive library of multicore-ready, highly optimized functions for data processing, multimedia, and communications applications

  • Intel? TBB is an award-winning C++ template library for creating reliable, portable, and scalable parallel applications

  • Rogue Wave* IMSL Fortran Library available in a special offering of Intel? Visual Fortran Composer XE for Windows

Benefits:


  • Outstanding application performance gives your applications a competitive edge

  • Integrates into Visual Studio and supports the gnu tools to preserve your
    development environment investment

  • Additional compilers, tools and libraries to enhance app performance.

  • Compatibility enables you to mix/match compilers as your development needs evolve
    Includes parallel programming models in components like Intel? TBB to enhance productivity as you add parallelism to take advantage of today's multicore systems – and tomorrow's.

  • Includes Intel? Integrated Performance Primitives (Intel? IPP), a library of multicore-ready, highly optimized functions that help speed development of digital media and data-processing applications

  • Saves time in delivering app performance with features like auto-parallelization, auto-vectorization and, the new guided auto-parallelization
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