The Intel® PCLMULQDQ instruction is a new instruction available beginning with the Intel® Core™ processor family. The PCLMULQDQ instruction performs a carry-less multiplication of two 64-bit operands.
Intel CPU已经自带集成显卡，软件通过Intel MSDK能够开启硬件的编解码加速功能。下表根据市场上的主流CPU（i3/i5/i7）绘制了一张编解码的实际硬件能力参考图，便于CODEC开发人员参考。
GPU Detect is a short graphics code sample demonstrates a way to detect the primary graphics hardware present in a system (including the 6th Generation Intel® Core™ processor family).
The fundamental shift in processor performance from clock speed to multi-cpu means game designs must evolve to effectively utilize the available processor cycles. This article discusses key features of the Intel® Core™ i7 processor for game development.
Optimizing graphics for Intel® Core™ processors as well as Intel® Atom™ processors is rapidly becoming a strategic imperative for game developers. This article describes how Funcom developed LEGO* Minifigures Online (LMO)to provide exceptional graphical experiences and improved battery life on both platforms.
Wolfgang Engel, CEO of Confetti, describes how to pick different resource binding mechanisms to run an application efficiently on specific Intel’s GPUs, folowing the release of Windows* 10 and the 6th generation Intel® Core™ processor family (code-name Skylake). Microsoft DirectX* 12
The Kyoto University team recognized that the performance of the open source Theano C++ multi-core code could be significantly improved. They worked with Intel to improve Theano multicore performance using a dual-socket Intel® Xeon®processor based system as the next generation Intel® Xeon Phi™ processors were not available at that time
This article, aimed at developers, will provide a glimpse into this 64-bit, multi-core SOC processor, with an overview of the available Intel technologies, including Intel® HD Graphics 5300.
The computer learning code Caffe* has been optimized for Intel® Xeon Phi™ processors. This article provides detailed instructions on how to compile and run this Caffe* optimized for Intel® architecture to obtain the best performance on Intel Xeon Phi processors.
The latest version of MXNet includes built-in support for the Intel® Math Kernel Library (Intel® MKL) 2017. The latest version of the Intel MKL includes optimizations for Intel® Advanced Vector Extensions 2 (Intel® AVX2) and AVX-512 instructions which are supported in Intel® Xeon® processor and Intel® Xeon Phi™ processors.