In this article:
- What is a GPU?
- What Does a GPU Do?
- GPU and CPU: Working Together
- GPU vs. Graphics Card: What’s the Difference?
- What Are GPUs Used For?
- GPUs for Gaming
- GPUs for Video Editing and Content Creation
- GPU for Machine Learning
What is a GPU?
Graphics processing technology has evolved significantly to provide distinct advantages in the computing industry. The newest graphics processing units (GPUs) are enabling innovative opportunities in diverse fields like gaming, content creation and machine learning.
What Does a GPU Do?
The graphics processing unit, or GPU, is a critical technology for personal and business computing. Designed for parallel processing, GPUs are used in a wide range of applications, including graphics and video rendering, creative production and artificial intelligence (AI).
Initially developed to speed up 3D graphics rendering, GPUs have evolved to become highly flexible and programmable, allowing graphics programmers to create sophisticated visual effects and realistic scenes with advanced lighting and shadowing techniques.
In addition, developers are increasingly leveraging the power of GPUs to accelerate high performance computing (HPC), deep learning and other workloads.
GPU and CPU: Working Together
The GPU evolved as a complement to its close cousin, the CPU (central processing unit). While CPUs have continued to deliver performance increases through architectural innovations, faster clock speeds and the addition of cores, GPUs are specifically designed to accelerate computer graphics workloads.
GPU vs. Graphics Card: What’s the Difference?
The terms GPU and graphics card (or video card) are often used interchangeably, but there is a subtle distinction between them. While a motherboard contains a CPU, a graphics card is an add-in board that includes the GPU as well as the components necessary for it to function and connect to the rest of the system.
There are two main types of GPUs: integrated and discrete. An integrated GPU is embedded alongside the CPU and does not come on a separate card. A discrete GPU, on the other hand, is a distinct chip mounted on its own circuit board and is typically attached to a PCI Express slot.
Integrated Graphics Processing Unit
Most of the GPUs available on the market are actually integrated graphics. But what exactly are integrated graphics, and how do they work in your computer?
Integrated graphics refer to a CPU that comes with a fully integrated GPU on its motherboard. This configuration allows for thinner and lighter systems, reduced power consumption and lower system costs.
Discrete Graphics Processing Unit
While integrated GPUs can handle many computing applications well, more resource-intensive applications with extensive performance demands require a discrete GPU (also known as a dedicated graphics card).
Discrete GPUs provide additional processing power, but they also consume more energy and create more heat. For maximum performance, they generally require dedicated cooling.
Modern GPUs are highly programmable, which allows them to be used for a wide range of applications beyond traditional graphics rendering.
What Are GPUs Used For?
Two decades ago, GPUs were primarily used to accelerate real-time 3D graphics applications. However, in the early 21st century, computer scientists discovered that GPUs had the potential to solve some of the world’s most difficult computing problems.
This realisation sparked the general-purpose GPU era, in which graphics technology is applied more extensively to an increasingly wide set of problems. Today’s GPUs are highly programmable, which gives them the flexibility to accelerate a broad range of applications beyond traditional graphics rendering.
GPUs for Gaming
Video games have become increasingly computationally intensive, with hyper-realistic graphics and vast, complicated in-game worlds. Advanced display technologies such as 4K screens and high refresh rates, as well as the rise of virtual reality gaming, are placing ever-increasing demands on graphics processing.
GPUs are capable of rendering graphics in both 2D and 3D, providing better graphics performance and enabling games to be played at higher resolutions, faster frame rates, or both.
GPUs for Video Editing and Content Creation
For years, creative professionals such as video editors and graphic designers have struggled with lengthy rendering times that limit their productivity and creativity. However, the parallel processing power offered by GPUs has made it faster and easier to render high-definition video and graphics.
This technology enables professionals to work more efficiently and effectively, allowing them to produce higher-quality work in less time.
GPU for Machine Learning
GPU technology has opened up a whole new world of possibilities in Artificial Intelligence (AI) and Machine Learning (ML). With their immense computational power, GPUs are able to accelerate complex workloads that benefit from the highly parallel nature of the technology, such as image recognition.
This has led to exciting advancements in deep learning technologies that rely on the combination of GPUs and CPUs.
AI and Machine Learning applications can operate faster and more efficiently, by using GPUs for certain tasks, leading to breakthroughs in fields like natural language processing, computer vision, and more.