Libraries

Intel® INDE Media for Mobile Tutorials - Running Samples for Android*

This tutorial describes how to run Intel® INDE Media for Mobile sample application for Android* on a device right from Eclipse* IDE.

Before getting started, download and install Intel® INDE Media for Mobile by visiting http://intel.com/software/inde. For additional assistance visit the Intel INDE forum.

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  • Intel® INDE Media for Mobile Tutorials - Building Samples for Android

    This tutorial outlines the steps needed to build the Intel® Integrated Native Developer Experience (Intel® INDE) Media for Mobile Samples for Android* in Eclipse* or Android Studio*.

    Before getting started, download the Intel® INDE at http://intel.com/software/inde and install Media for Mobile component, then download Media for Mobile samples from GitHub repository https://github.com/INDExOS/media-for-mobile

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  • Enhancing In-Vehicle-Infotainment Application Reliability and Performance using Intel® System Studio

    Intel based solution is available to reduce the time and cost of developing in-vehicle technologies by providing application-ready solutions consisting of compute modules, automotive middleware and development kits. Intel® System Studio can be used in various stages of In-Vehicle-Infotainment development right from debugging BIOS in hardware layer to performance tuning of HMI layer.
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    In this article we’d like to write about H.264 video processing on Intel GPUs on Linux and the experience our company, Inventos, got in the process of enhancing  StreamBuilder — our streaming media server.

     

    Introduction

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  • Intel® System Studio - Multicore Programming with Intel® Cilk™ Plus

    Intel System Studio not only provides a variety of signal processing primitives via Intel® Integrated Performance Primitives (Intel® IPP), and Intel® Math Kernel Library (Intel® MKL), but also allows developing high-performance low-latency custom code (Intel C++ Compiler with Intel Cilk Plus). Since Intel Cilk Plus is built into the compiler, it can be used where it demands an efficient threading runtime in order to extract parallelism. Therefore it's possible to effectively introduce multicore parallelism even without introducing it into each of the important algorithms e.g., by employing a parallel pattern called pipeline. For custom code (e.g., code that's not reused via a library), one can rely (in addition to auto-vectorization) on an extended Array Notation incl. elemental functions (kernels) to explicitly vectorize at a higher level compared to ISA-specific intrinsic functions.
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