Nowadays we need increasingly powerful hardware to keep up with the constant development of technology. Software becomes more complicated, images and videos now weigh a ton — even online casino games now have such a high quality of graphics that not every device can handle them! The new era requires high-performance embedded SOCs and discrete GPUs. Take a look at the graphics of the slots on Snabbare — they are modern and optimized for the capabilities of a variety of GPUs. 

How do GPUs help in our technology-heavy world and what are they used for? Find out in our article.

What Does a GPU Do?

GPU is a graphics processing unit. Basically,  it is a hardware component responsible for computer graphics. That is why it is also called a graphic or video card. It was designed for parallel processing, which means that the GPU supports the main processor of the computer. It performs a fast mathematical calculation, so the main processor can do other tasks meanwhile.

As a result, GPU speeds up the work of the computer and reduces the time it takes to render files. Additional support from GPU is needed for gaming consoles, computers, and laptops when performing graphic-intensive tasks (for example, 3D gaming). For instance, by using advanced techniques of lighting with GPUs, developers can produce highly engaging visual effects. 

Usually, a GPU consists of a memory card (this depends on the type), a processing unit, a motherboard, and a cooling mechanism.

GPUs can be divided into two types:

1. Integrated

This type of GPU has to be embedded into the main processor. It does not have a separate memory card.

2. Discrete

An autonomous processing unit whit its memory card. It is usually installed externally.

Given the possibilities of a GPU, now it is indispensable for completing certain tasks.

What Are GPUs Used For?

In the beginning, GPUs were used by gamers. With the development of real 3D games, the old PCs could not handle the game. Their processors were not able to proceed with that amount of information, so games were not working properly. But after installing a GPU, you could increase the threshold of processing information.  

However, over the last decade, scientists came to the realization that GPUs can manage a broader spectrum of tasks. Today, embedded GPUs are used in most electronic devices such as mobile phones, laptops, workstations, and so on. With some programming changes, modern video cards can improve productivity in video design. The full list of where GPUs are used:   

• Gaming
• Video Editing
• Machine learning
• Driverless cars
• Cryptomining

GPUs are very effective when it comes to image processing, manipulating computer graphics, or complicated calculations.

GPUs for Gaming

Video cards are widely used by players and are considered the most important unit in PC gaming. Modern games are demanding and need the power that GPUs can provide. But in return, the gamer has a realistic game graphing in 2D and 3D dimensions. And with a more advanced video card, a 4K screen, or VR glasses, it will feel like a total dive into the game.

Better graphic means that the game will work at a higher resolution and have faster frame rates. It is important for both regular computer games and online ones.

Yes, online casinos also use GPUs, as it enables the games to run smoother. Most cloud gambling providers tend to use video cards for every player. So, it does not matter if the player has a strong GPU on the device or not. The game still will be displayed in high resolution, because the stream will be coming from the cloud. Such a system allows playing your favorite game using a desktop, tablet, or mobile phone.

Remember that to be able to play at an online casino, a player needs to ensure stable access to a high-speed internet connection.

GPUs for Video Editing

Another field where using GPUs is a must-have is video encoding. It is possible to work with video under 4K and 8K using only the CPU. But it takes more time and gives a much more intensive load on the system than the average usage of PC. If you want to work faster and reduce overburdening of the system, you might want to buy a video card.

Yet, GPU is mandatory if you work with videos above the 1080p resolution. But for best performance, it is not enough to buy a graphic card, you also need a powerful processor. If the CPU is slow, it will play a role of a “bottleneck,” so you will not be able to work quickly and properly with high resolutions.

GPUs for Machine Learning

Rendering video and graphics is not the only mission of GPU. It also plays a crucial role in artificial intelligence and machine learning. With the help of GPU, the latter allows recognizing images. It is also used to automate the process of creating analytic models. This form of analytic analysis searches for certain patterns in data and systemizes them. The process conducted by GPUs is faster and more accurate if compared to human work.

The algorithms of GPUs build sample data. Furthermore, based on the obtained data, it is possible to make predictions without human input. This kind of data analysis is used in medicine, demography, statistics, even email filtering, and others.

To Summarize

Today GPUs are used in different fields. GPUs significantly accelerate data analysis in machine learning. Video rendering became smoother and faster because of GPUs. Finally, it is an indefeasible part of modern gaming. In particular, remote video cards made it possible to enjoy online games in high resolution regardless of the processor capacity.