Threading Intel® Integrated Performance Primitives Image Resize with Intel® Threading Building BlocksThreading Intel® IPP Image Resize with Intel® TBB.pdf (157.18 KB) :
We demonstrate how to create a Sierpinski Carpet in OpenCL* 2.0
The code samples for the webinar "Further Vectorization Features of the Intel® Compiler" given on 4/7/2015 are attached below.
While Image convolution is not as effective with the new Read-Write images functionality, any image processing technique that needs be done in place may benefit from the Read-Write images. One example of a process that could be used effectively is image composition. In OpenCL 1.2 and earlier, images were qualified with the “__read_only” and __write_only” qualifiers. In the OpenCL 2.0, images can...
If printf or fprintf functions cause transaction aborts, use Intel® Processor Trace as a work-around.
The Storage Performance Development Kit (SPDK) is an open source set of tools and libraries hosted on GitHub that helps you create high-performance and scalable storage applications. This tutorial focuses on the userspace NVMe driver provided by SPDK and illustrates a Hello World example.
You can use LibRealSense and OpenCV* to stream RGB and depth data from your connected Intel® RealSense™ camera. This tutorial and code sample shows how to do this, based on the Ubuntu* operating system. In the end you will have a nice starting point where you use this code base to build upon to create your own LibRealSense / OpenCV applications.
DEFLATE compression algorithms traditionally use either a dynamic or static compression table, with tradeoffs in processing time. The Intel® Intelligent Storage Acceleration Library (Intel® ISA-L) semi-dynamic compression comes close to getting the best of both worlds. Learn how.
The attached code sample compares memcpy and SKDK + Intel I/OAT DMA performance when moving different size data chunks in memory.