Image Processing Acceleration Techniques using Intel® Streaming SIMD Extensions and Intel® Advanced Vector ExtensionsThis article details optimized implementations of data transformations and algorithms together with analysis comparing performance and providing speedup measurements for Intel® SSE optimized code and estimates for Intel® AVX optimized code.
Introduction A Brief History of Quicksort
We demonstrate how to create a Sierpinski Carpet in OpenCL* 2.0
General Matrix Multiply
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...
In this tutorial, we will give an in-depth presentation of the architecture and micro-architecture of the media and graphics accelerator. We will explain the tradeoff between general purpose compute and hardware fixed functions. We will discuss the advantages and disadvantages of on-die integration. We will present the various programming models that are supported. We will present some...