The big idea: A screen has millions of pixels, and each one needs working out.
The sums are tiny and all the same. There are just an enormous number of them.
CPU — a few clever cores
- A handful of powerful cores
- Handles complicated, varied jobs
- Does them one after another, very fast
GPU — thousands of simple cores
- Thousands of small, simple cores
- Each does the same easy sum
- Does them all at the same time
Painting a wall: One skilled decorator does a whole house, room by room.
A thousand people with rollers do one wall in seconds — but only because every one of them is doing the same simple thing.
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Anything made of many identical calculations suits a GPU. That turns out to include far more than graphics.
Video games
Every frame works out a colour for every pixel — millions of the same small sum, sixty times a second.
The original reason GPUs exist
Machine learning
Training a model multiplies huge grids of numbers over and over.
Same sum, different numbers — ideal for a GPU
Simulations
Weather, crash tests and physics models update millions of points each step.
Each point is independent, so all can run at once
The one-line answer: A GPU is built for many simple calculations at the same time; a CPU is built for fewer, more complicated ones in order.
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The GPU does not replace the CPU: The CPU still runs the program, decides what happens and manages everything else.
When a pile of identical sums comes up, it hands that part to the GPU and carries on.
Why splitting work helps — and why it only helps when the work can actually be split.
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The trap: A GPU is not simply faster than a CPU. Give it one long chain of steps where each needs the answer before it and it performs poorly — its cores are individually weak.
How this is tested — marks come from the ARCHITECTURE and the KIND OF TASK, never from listing devices that contain one. It comes up two ways:
Paper 1 Section A
- Describe the role of a GPU, 2-3 marks
- Compare a GPU with a CPU
- Say why a named application benefits
Paper 1 Section B — case study
- Recommend a processor for the system in the case study
- Justify it from the work that system does
The classic trap: "A GPU handles the graphics" restates the name. Say many simple cores doing the same calculation at once — that is the architecture mark.
Describe the role of a GPU in a modern computer, with reference to one real-world use.
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