Ever since the invention of the computer, it's been clear that there are two types of people: those who would like to have their applications run faster and those who are content to wait. Now, there is a third type of person: those who want their applications to run faster and want to run on the world's most efficient processing unit: the GPU. Now if you are one of those who wants the best or nothing on your computer, you should know about this one. GPU-accelerated computing is the employment of a graphics processing unit (GPU) and a computer processing unit (CPU) to facilitate processing-intensive operations such as deep learning and engineering applications. Developed by NVIDIA in 2007, the GPU provides far superior application performance by removing processing-intensive application sections of the GPU. GPU-accelerated computing deployment is growing in popularity due to the large variety of applications in which it could be used, from artificial intelligence and drones to robots or autonomic cars. Did you know that your computer has a super-powered graphics card in it? It's true! Your GPU is designed to handle large amounts of data quickly and efficiently. It can also be used to run parallel calculations, which means that if you're running an application on your computer, the GPU can help speed it up. If you think about it, this makes sense. Your CPU comprises specialized cores for sequential serial processing, which means they can only do one thing at a time. On the other hand, your GPU is made up of smaller cores designed to handle multiple tasks in parallel. So if an application needs to do something complicated and uses a lot of RAM or processing power, it might need some help from your GPU.