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Intel® INDE 2015 Release Notes and Installation Guide

INDE 2015 Update 1 is available now!

If you are an existing user, you will receive a notification in your Intel Software Manager tool on how to update your installation. If you are a new user, please visit  https://software.intel.com/en-us/intel-inde to see various packages available and download INDE.

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  • 在英特尔® 架构的设备上优化 Android* 应用

    在英特尔® 架构的设备上优化 Android*应用

    概要介绍:

    多年来英特尔®一直致力于帮助第三方软件商在 Windows 平台做性能和功耗的优化.软件优化后在性能和功耗上得到了大幅的改善。随着 Android*成为一个更大的市场平台,软件商都相应推出了自己在 Android 上的软件。然而,这些软件仍然有着比较大的优化空间.软件尤其是多媒体应用软件在性能和功耗方面提升空间非常大.事实上,同一款软件在同一 Intel 硬件平台上在 Window 上的性能甚至会远远好过在 Android*上的性能.这篇白皮书介绍了开发优化 Android 应用程序的一些工具和方法以及媒体应用程序的优化实例。这篇白皮书旨在面向  ISVs,  OEMs,  和其他技术相关人士。

    点击此处下载白皮书>>

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  • Using L1/L2 cache as a scratchpad memory

    Dear all,

    Explicitly cache control is a one of important feature in Xeonphi (MIC). How could I use the L1 or L2 as scratchpad memory and also sharing them data between the cores?

    In addition,  is there any way to hack the MESI state of the cache line in the distributed tag directory (DTD)? 

    Thanks in advance.

    Regards

    Intel® Math Kernel Library (Intel® MKL) 11.2 Update 2 for Linux*

    Intel® Math Kernel Library (Intel® MKL) is a highly optimized, extensively threaded, and thread-safe library of mathematical functions for engineering, scientific, and financial applications that require maximum performance.Intel MKL 11.2 Update 2 packages are now ready for download. Intel MKL is available as part of the Intel® Parallel Studio XE 2015 . Please visit the Intel® Math Kernel Library Product Page .

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  • Intel® Math Kernel Library (Intel® MKL) 11.2 Update 2 for Windows*

    Intel® Math Kernel Library (Intel® MKL) is a highly optimized, extensively threaded, and thread-safe library of mathematical functions for engineering, scientific, and financial applications that require maximum performance.Intel MKL 11.2 Update 2 packages are now ready for download. Intel MKL is available as part of the Intel® Parallel Studio XE 2015 . Please visit the Intel® Math Kernel Library Product Page .

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  • Device Emulator Tutorial

    Use the EMULATE tab to quickly see the results of changes you make to your project files using either your favorite code editor or the Brackets* editor built into the Develop tab. Check the functionality and layout of your hybrid app on a collection of virtual mobile devices. This tab lets you open a version of the Google Chrome* Developer Tools (CDT) debugger and directly debug your app's JavaScript* code, CSS rules and DOM elements. After you test and debug your app with the EMULATE tab, run and test your app on a real mobile device.

    Performance comparison between Intel TBB task_list, openMP task and parallel for

    I am planning on parallelizing a hotspot in a project. And I would like to know your opinion between the performance evaluation between parallel for, omp single followed by task and intel TBB task_list, under ideal conditions where number of threads are equal to computation items and when computation are much greater than available threads to see scheduling overhead(in order to evaluate the most efficient scheduler). I will also, be writing some sample test programs to evaluate myself but I also wanted to know if anybody had previously made these evaluations.

    Thanks in advance.

    Further information about different barrier algorithms

    Hi!

    I'm researching on barrier algorithms using SIMD instructions and I'm trying to deeply understand the different versions included in the RTL.

    I've noticed that there is a new barrier algorithm (hierarchical) since the last time I had a look.

    Where could I find a further description of them? Could someone from Intel provides me with further information?

     

    Thank you in advance.

    Kind regards.

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