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How does a GPU work?
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Quick answer
A GPU works by splitting a task into thousands of small calculations and running them all at the same time across thousands of simple cores. This massive parallelism makes it ideal for rendering graphics and for training and running AI models.
Step by step
- It has thousands of small cores, versus a handful of large cores in a CPU.
- It excels at doing the same operation on huge batches of data simultaneously (parallelism).
- It was originally built to render pixels, where each pixel can be computed independently.
- That same parallel math now powers modern AI — training and running neural networks.
- It works alongside the CPU, which hands it the heavy parallel workloads.
People also ask
Why are GPUs used for AI?
Neural networks are mostly matrix math — the same operation repeated across enormous data — which maps perfectly onto a GPU's thousands of parallel cores.
Is a GPU faster than a CPU?
For parallel workloads like graphics or AI, far faster. For varied, sequential logic, a CPU's powerful cores are usually better.
What is VRAM?
Video memory on the GPU that holds the data it is working on — textures or model weights — close to the cores for fast access.
What does a graphics card do?
It rapidly performs the many parallel calculations needed to render images, video, and 3D graphics.
What's the difference between a CPU and a GPU?
A CPU handles varied tasks one or a few at a time; a GPU does thousands of similar calculations at once.