What is a GPU?

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What is a GPU?

GPUs aren't just good for gaming - there's business applications too

Computers are complicated pieces of technology, but one of the most complex components is the graphics processing unit (or GPU). This chip is largely responsible for rendering everything that's displayed by a PC's monitor, from the user interface all the way up to video files and games.

It's not just a luxury for gaming PCs, either; having a strong GPU is a necessity for many business tasks.

What does a GPU do?

Although it had been in use for a number of years previously, the term 'GPU' was popularised in the 1990s by manufacturer Nvidia. The company's GeForce range of graphics cards helped to pioneer now-standard technologies like hardware acceleration, programmable shading and stream processing.

In short, a GPU is a processor that is specially-designed to handle intensive graphics rendering tasks.

Computer-generated graphics - such as those found in videogames or other animated mediums - require each separate frame to be individually 'drawn' by the computer, which requires a large amount of power.

Most high-end desktop PCs will feature a dedicated graphics card, which occupies one of the motherboard's PCIe slots. These usually have their own dedicated memory allocation built into the card, which is reserved exclusively for graphical operations. Some particularly advanced PCs will even use two GPUs hooked up together to provide even more processing power.

Laptops, meanwhile, often carry smaller mobile ships, which are smaller and less powerful than their desktop counterparts. This allows them to fit an otherwise bulky GPU into a smaller chassis, at the expense of some of the raw performance offered by desktop cards.

What are GPUs used for?

GPUs are most commonly used to drive high-quality gaming experiences, producing life-like digital graphics. However, there are also several business applications that rely on powerful graphics chips.

3D modelling software like AutoCAD, for example, uses GPUs to render models. Because the people that work with this kind of software tend to make multiple small changes in a short period of time, the PC they're working with needs to be able to quickly re-render the model.

Video editing is another common use-case; while some powerful CPUs can handle basic video editing, if you're working with large amounts of high-resolution files - particularly 4K or 360-degree video - a high-end GPU is a must-have in order to transcode the files at a reasonable speed.

GPUs are often favoured over CPUs for use in machine learning too, as they can process more functions in a given period of time than CPUs. This makes them better-suited to creating neural networks, due to the volume of data they need to deal with.

Not all GPUs are created equal, however - manufacturers like AMD and Nvidia commonly produce specialised enterprise versions of their chips, which are designed specifically with these kinds of applications in mind and come with more in-depth support provided.

This article originally appeared at itpro.co.uk

Copyright © ITPro, Dennis Publishing
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