Intel® Many Integrated Core Architecture

New tool available in beta: Vectorization Advisor

Software must be both threaded and vectorized to get the full performance benefit from today’s and tomorrow’s hardware.  Vectorization Advisor is a vectorization analysis tool that lets you identify loops that will benefit most from vectorization, identify what is blocking effective vectorization, explore the benefit of alternative data reorganizations, and increase the confidence that vectorization is safe.  

Vectorization Advisor is now available for beta test as a part of Intel® Advisor XE 2016. 

The Intel® Parallel Studio XE 2016 Beta program is now available!

Intel Parallel Studio XE 2016 is being made available now as part of a beta test program. In this beta test, you will have early access to Intel® Parallel Studio XE 2016 products and the opportunity to provide feedback to help make our products better. Registration is easy through the pre-Beta survey site

This suite of products brings together exciting new technologies along with improvements to Intel’s existing software development tools:

Intel® Xeon Phi™ Coprocessor code named “Knights Landing” - Application Readiness

As part of the application readiness efforts for future Intel® Xeon® processors and Intel® Xeon Phi™ coprocessors (code named Knights Landing), developers are interested in improving two key aspects of their workloads:

  1. Vectorization/code generation
  2. Thread parallelism

This article mainly talks about vectorization/code generation and lists some helpful tools and resources for thread parallelism.

  • 开发人员
  • 服务器
  • 中级
  • 英特尔® C++ 编译器
  • Intel® AVX-512
  • Knights Landing
  • Intel SDE
  • Intel® IMCI
  • Intel® Many Integrated Core Architecture
  • 并行计算
  • 矢量化
  • Troubleshooting HOWTO: Bad hardware? MPSS? Configuration?

    Are you having problems with your hardware (Cannot see your Intel(R) Xeon Phi(tm) coprocessor?  Sporadic accessibility?) or with the Intel(R) Manycore Platform Software Stack (Intel(R) MPSS) running reliably?

    Attached to this post are PDF "flowcharts" that explain how you can troubleshoot the problem (note:  Both Linux and Windows flowcharts are available), and shows what information you will want to collect if you need to escalate your issue to your OEM provider or Intel.

    What collateral/documentation do you want to see?

    Do you have questions that you are not finding the answers for in our documentation?  Need more training, source code examples, on what specifically?   Help us understand what's missing so that we can make sure we develop documentation you care about (what is important, and what is nice to have)!   Thank you

    FAQS: Compilers, Libraries, Performance, Profiling and Optimization.

    In the period prior to the launch of Intel® Xeon Phi™ coprocessor, Intel collected questions from developers who had been involved in pilot testing. This document contains some of the most common questions asked. Additional information and Best-Known-Methods for the Intel Xeon Phi coprocessor can be found here.

    The Intel® Compiler reference guides can be found at:

    different performance on nativ and offload modes


    • host: Xeon E5-2690, 2,9 GHz, 64 Gb
    • mic: Intel Xeon Phi 7110X, 1,1 GHz, 8 Gb
      • OS Version                      : 2.6.32-220.el6.x86_64
      • Driver Version                 : 5889-16
      • MPSS Version                 : 2.1.5889-16
      • Host Physical Memory    : 65868 MB
    • ICC: 14.0.1 (composer_xe_2013_sp1.1.106

    I took the test from this subject ( and modified it to run in offload mode.

    OpenMP 4.0 Fortran -> $omp target map(to:x) Does not copy scalars

    Hello. Ever since I tried switching over to openMP 4.0 from LEO my code was not working properly. Finally figured out that during the offload transfer the map clause copies arrays but DOES NOT COPY SCALARS. 

    The only way to get scalars copied to the device is to call target update to(scalar)

    Can someone please explain this behaviour?

    Using icc 15.0.1

    EDIT: Scalars created in the same file are copied, but scalars imported from a different file using USE do not get copied. Arrays get copied no matter where they originate from.

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