Три возможности Intel® RealSense™ Unity* Toolkit

Из этого руководства вы узнаете, как работать с префабами и образцами, идущими в комплекте с Unity* Toolkit в Intel® RealSense™ SDK R2 (v4.0).  Предполагается, что вы уже импортировали Toolkit в среду Unity и умеете применять сценарий RealSense к объекту Unity. Если вы используете Unity 5, добавьте в проект две 64-битные библиотеки, которые находятся в папке \RSSDK\bin\x64.

The New Parallel Universe Magazine is Out: All About Vectorization

Parallel Universe is Intel's quarterly magazine that explores inroads and innovations in software development. The new issue takes a deep dive into the subject of vectorization and what it can do for you. Our first feature article looks at the SIMD directives for explicit vector programming now available in OpenMP. The second article walks you through Vectorization Advisor, a new tool in the latest version of Intel® Advisor XE that can help answer your questions about vectorization.

No Cost Options for Intel Integrated Performance Primitives Library (IPP), Support Yourself, Royalty-Free

Intel® IPP is an extensive library which includes thousands of optimized functions covering frequently used fundamental algorithms including those for creating digital media, enterprise data, embedded, communications, and scientific/technical applications. Intel IPP includes routines for Image Processing, Computer Vision, Data Compression, Signal Processing and (with an optional add-on) Cryptography. Intel IPP is available for Linux*, OS X* and Windows*.

新版unity中如何配置Android X86平台

从unity4.6版本开始,unity已经对Android系统支持x86平台的编译构建了,同时也支持了通用二进制 (通用二进制作为默认的编译选项)。




2.单击unity菜单栏的File->build settings


Getting Started with Intel® RealSense™ App Development - Detailed Install Instructions

Getting started developing an application using Intel® RealSense™ technology? Here are detailed instructions on how to do it, using the Intel® RealSense™ SDK version R4 or above. Includes information on getting a camera and how to install the SDK.

The JITter Conundrum - Just in Time for Your Traffic Jam

In interpreted languages, it just takes longer to get stuff done - I earlier gave the example where the Python source code a = b + c would result in a BINARY_ADD byte code which takes 78 machine instructions to do the add, but it's a single native ADD instruction if run in compiled language like C or C++. How can we speed this up? Or as the performance expert would say, how do I decrease pathlength while keeping CPI in check? There is one common short cut around this traffic jam of interpreted languages. If you were going to run this line of code repeatedly, say in a loop, why not translate it into the super-efficient machine code version?

NEW Intel® Iris™, Iris™ Pro, and HD Graphics Production Driver for Windows* 7, 8.1, 10

Note: Operating system support varies by platform. Please see the associated ReadMe's for more details. The Windows 10* production driver has been posted to Intel Download Center at the following direct links to the driver: This driver is in self installing format (exe) intended for end users. This driver is in zip format intended for developers and IT professionals.
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