In addition, the GPU, by virtue of its architecture (many vector execution units), is much better suited to the execution of a certain type of tasks-image processing that is, in fact, any operations of the same type on data arrays. That is what the central processor is about.īut it is worth noting that the performance of Intel integrated GPUs over the past decade has grown much more in percentage terms than corresponding CPU performance, and this trend will certainly continue with the advent of new, discrete graphics cards from Intel.

Of course, the CPU performance of a typical system usually significantly exceeds the GPU performance in terms of gigaflops, and that is reasonable and expected. How can it be used effectively? This paper helps to explain.įirst, let’s briefly see why it is worth using an Intel® GPU. Intel® Graphics Technology is essentially a full-fledged processor and, accordingly, capable of not only displaying an image on the screen and accelerating video, but also is capable of performing ordinary general-purpose calculations. From the majority of entry level devices with Intel Atom® processors, to some servers with Intel® Xeon® E3 processors, and the whole range of Intel® Core™ processors, have the integrated graphics core onboard. How many Intel processor cores do you have on your computer? If you use an Intel® CPU-based system, in the vast majority of cases you will need to add one to your answer.

This article provides an introduction to the Intel® C for Metal Development Package, a software development package that is available publicly.

C for Metal is a general graphics processing unit (GPU) programming language with an explicit single instruction, multiple data (SIMD) programming model that lets users achieve maximal performance on Intel® Processor Graphics.

Gpu with metal support