How does a graphics card work? The role of the GPU explained simply.
Learn how a graphics card works, the role of GPU, VRAM, and the differences between CPU and GPU.
COMPUTER SCIENCE
Lucas GRANDIER
10/13/20267 min read
If you want to better understand how a computer works overall, check out our article How does a computer work?
Table of Contents
2. How does a graphics card create an image?
3. What is video memory (VRAM) used for?
4. What is the difference between a CPU and a GPU?
5. Why are graphics cards essential to artificial intelligence?
6. How to choose a graphics card adapted to your needs?
FAQs: Frequently asked questions about graphics cards
When you play a video game, watch a video, or use artificial intelligence, billions of calculations can be required to produce the result displayed on the screen.
But how does a computer transform data into images? And why can a graphics card perform certain calculations much faster than a conventional processor?
Behind these operations is an essential component: the GPU, or graphics processor. Combined with its memory and other graphics card components, it allows large amounts of data to be processed in parallel.
Let's find out how a graphics card works, what its components do, and why it's become indispensable for both video games and artificial intelligence.
1. What is a graphics card?
A graphics card is a computer component responsible for producing the images you see on a screen. It can also speed up certain scientific and computer calculations.
It is mainly based on an electronic circuit called a GPU, for Graphics Processing Unit.
A distinction must be made between these two concepts:
The GPU is the chip that performs the graphics calculations and parallel operations.
The graphics card is the assembly that houses this chip, its video memory, its power system, its cooling and the connections to communicate with the computer and the screen.
Not all graphics cards are separate components, however. Many processors directly integrate a graphics chip, which is sufficient for common tasks.
A dedicated graphics card usually has additional resources. It is particularly useful for demanding video games, 3D creation, video editing and some artificial intelligence processing.
2. How does a graphics card create an image?
To understand how a GPU works, let's take the example of a three-dimensional video game.
When you move your character, the computer has to calculate the position of the objects, determine what the virtual camera sees, apply the textures and lighting, and then transform the result into an image made up of pixels.
These operations are carried out through several steps:
Step 1: Receive instructions from the processor
The central processor, or CPU, runs the game program. In particular, he manages the logic, the player's actions and part of the preparation of the scene.
It then transmits to the GPU the information needed to render graphics, such as display objects, positions, textures, and lighting settings.
The GPU can then start its work.
Step 2: Calculate the geometry of the objects
In a 3D environment, objects are typically represented by sets of points, lines, and triangles.
The GPU performs mathematical calculations to determine how these items should appear on the screen.
It takes into account their position, the orientation of the camera and the perspective, among other things. A distant object thus appears smaller than a nearby object.
These calculations make it possible to transform a virtual scene into a representation adapted to the player's point of view.
Step 3: Apply textures and lighting
A geometric shape is not enough to make an object realistic. It must also be given an appearance.
Textures can be used, for example, to represent the colour of a wall, the details of a skin or the patterns of a garment. The lighting calculations then determine how the light interacts with the surfaces.
This allows the GPU to simulate shadows, reflections, and different lighting conditions.
Some advanced techniques, such as ray tracing, seek to reproduce the behavior of light more accurately by simulating the path of light rays in a scene.
Step 4: Turn the result into pixels
Once the graphic calculations have been performed, the image must be represented as a grid of pixels.
Each pixel has color information and, depending on the processing, other data useful for rendering.
The GPU then produces an image that can be sent to the screen. This process repeats continuously to create a smooth animation.
For example, a game running at 60 frames per second should produce a new frame approximately every 16.7 milliseconds.
The higher the resolution and the more complex the graphical effects, the greater the calculations that can be required.
3. What is video memory (VRAM) used for?
The GPU doesn't work alone. It relies on a specific memory called VRAM, for Video Random Access Memory.
This memory temporarily stores the data necessary for graphic calculations, such as textures, images being processed and various information related to the 3D scene.
Let's take an example: in a video game, a character can wear very detailed clothes. The corresponding textures must be accessible quickly for the GPU to use them when rendering.
VRAM allows this data to be stored close to the GPU.
Does more VRAM always mean more performance?
No. The amount of video memory is just one of the things that determines the performance of a graphics card.
A larger amount of VRAM can be useful when games use detailed textures, high resolution, or particularly complex scenes.
On the other hand, if a graphics card already has enough memory for a given task, increasing its capacity does not guarantee an increase in performance.
The computing power of the GPU, memory bandwidth, and board architecture also play an important role.
Therefore, VRAM should be considered as a resource necessary for the proper functioning of the GPU, and not as a direct measure of its power.
4. What is the difference between a CPU and a GPU?
The CPU and GPU are both processors, but they are designed to meet different needs.
The CPU, or central processor, is versatile. He executes program instructions, manages system operations, and coordinates many of the computer's tasks.
The GPU, on the other hand, is particularly suitable for operations that can be spread over a large number of similar calculations.
This is called parallel computing.
Imagine that you have to perform thousands of independent multiplications. A CPU can handle several of them efficiently, but a GPU is designed to run a very large number of them simultaneously when the work is right.
This distinction doesn't mean that a GPU is consistently faster than a CPU. It all depends on the nature of the work to be done.
The two components are complementary: the CPU prepares and coordinates many operations, while the GPU takes care of the calculations for which its architecture is particularly efficient.
To learn more about how the CPU works, you can also check out our article on how a CPU works.
5. Why are graphics cards essential to artificial intelligence?
Graphics cards are no longer just for displaying images. They also play an important role in the development and use of artificial intelligence.
Many AI models rely on repeated mathematical operations on a large scale, including matrix multiplications. These calculations can often be spread across many compute units.
The parallel architecture of GPUs is therefore particularly suitable for certain machine learning and deep learning tasks.
Training AI models
During the training of a neural network, the system processes data, calculates predictions, and then adjusts the model's parameters to reduce its errors.
These operations must be repeated over large amounts of data. Suitable GPUs can significantly speed up this process.
Running models
GPUs can also be used once the model has been trained, when it needs to produce results from new data. This phase is called inference.
It is used, for example, in image generation, language processing or certain visual recognition applications.
Modern GPUs can integrate specialized units into certain AI calculations. Combined with sufficiently fast memory and suitable software, they help to improve performance.
However, not all artificial intelligence models need a dedicated graphics card. Conventional processors, specialized chips or embedded systems can also run many models, depending on their size and constraints.
6. How to choose a graphics card adapted to your needs?
Not all graphics cards are designed for the same purpose. The choice therefore depends mainly on the tasks you want to perform.
For office automation, Internet browsing and video playback, an integrated graphics chip is often sufficient.
For video games, you have to consider the power of the GPU, the targeted resolution, the desired frame rate and the graphics effects used.
For 3D creation, video editing or artificial intelligence, the amount of video memory and computing capabilities can become particularly important.
Finally, power consumption, cooling, price, and compatibility with the rest of the computer should also be considered.
A more expensive or powerful graphics card is therefore not necessarily the best choice for all users. The goal is to balance performance, actual needs, and budget.
FAQs: Frequently asked questions about graphics cards
Can you use a computer without a dedicated graphics card?
Yes. Many computers have a graphics chip built into the processor. It is generally sufficient for office automation, Internet browsing and common multimedia uses.
What is the difference between a GPU and a graphics card?
The GPU is the chip responsible for graphics calculations and other parallel operations. The graphics card is the hardware package that includes this chip, its video memory, and the components needed to run it.
Why does a graphics card have its own memory?
VRAM stores the data needed for graphics processing, including textures and images being calculated. It allows the GPU to quickly access this information without relying solely on the computer's main RAM.
Does a graphics card improve the performance of all software?
No. It mainly accelerates tasks that can take advantage of its computing capabilities. For some programs, performance is more dependent on the CPU, RAM, storage, or other components.
Conclusion
A graphics card transforms data and instructions into images thanks to a set of calculations performed by its GPU. It relies on video memory to quickly access the necessary information and works in addition to the central processor.
Its architecture, adapted to parallel computing, explains why it is particularly effective for video games, graphic creation and many artificial intelligence applications.
Understanding how it works allows us to better understand the mechanisms of a modern computer and the role of each of its components.
To go deeper and understand how the GPU, CPU, RAM, SSD, and other components work together, check out our article How does a computer work?, which shows how a PC works as a whole.
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