This paper examines software performance optimization for an implementation of a non-library version of DGEMM executing on the Intel® Xeon Phi™ processor (code-named Knights Landing, with acronym KNL) running the Linux* Operating System (OS).
This tutorial and code sample shows you how to send a video stream from the Intel® Aero Compute Board that has an Intel® RealSense™ camera (R200) attached to it. This video stream will be broadcast over the compute board’s Wi-Fi* network to a machine that is connected to the Wi-Fi network. The video stream will be displayed in the QGroundControl* internal video window.
The Transportation in a Box solution is based on a previous IoT path-to-product connected transportation solution, which involved a comprehensive development process that began from ideation and prototyping, through productization. Taking advantage of that prior work, which was demonstrated at Intel® Developer Forum 2016, the Transportation in a Box solution demonstrates how path-to-product solutions can provide a point of departure that streamlines the development of IoT solutions.
The sample code for takeoff and landing in simulation with software-in-the-loop (SITL) for a quadcopter under autonomous control via the Intel Aero compute board. The sample, takeoff.cpp, uses MAVLink and PX4 commands and messages to affect the takeoff and landing of the quadcopter under the control of a C++ application.
Learn how to write an MPI program in Python*, and take advantage of Intel® multicore architectures using OpenMP threads and Intel® AVX512 instructions.
Cython* is a superset of Python* that additionally supports C functions and C types on variable and class attributes. Cython generates C extension modules, which can be used by the main Python program using the import statement.
本文将介绍自适应屏幕空间环境光遮蔽 (ASSAO) 效果的最新实施方法，该技术经过精心设计，只需实施外观、设置和质量统一、符合行业标准的方法，就可从低能耗设备和场景扩展至高分辨率的高端台式机。
Realistic cloth movement can bring a great amount of visual immersion into a game. Using PhysX* Clothing* is one way to do this without the need of hand animating. Incorporating these simulations into Unreal Engine* 4 is easy, but as it is a taxing process on the CPU, it’s good to understand their performance characteristics and how to optimize them.