GPU vs CPU

A companion page to Workshop 1 Hardware and Networks.

When you cracked open a laptop in Workshop 1, you spotted the CPU — the brain of the computer. It fetches instructions, does the maths, and keeps everything running. A modern CPU has a handful of very fast, very clever cores (usually 4 to 16). It can juggle lots of different jobs, but it tackles them roughly one at a time per core.

The GPU sits on a separate chip, often right next to the CPU. It was originally built to push pixels onto your screen — millions of tiny colour calculations every frame. To do that, it doesn't need a few brilliant cores; it needs thousands of simple ones all working at once. Each individual core is slower than a CPU core, but when thousands fire together the total throughput is enormous.

Here's an analogy: imagine you need to deliver 1 000 parcels across town. A CPU is like one very fast truck — it zooms between addresses, but it still visits them one by one. A GPU is like 1 000 cyclists who each grab a parcel and pedal off at the same time. No single cyclist is as fast as the truck, but the whole fleet finishes the job far sooner.

This is exactly why AI researchers love GPUs. Training an AI model means doing millions of simple maths operations (multiply, add, multiply, add — over and over). A CPU would grind through them in a long queue. A GPU spreads them across thousands of cores and finishes in a fraction of the time.

You've already seen the CPU inside a laptop. The GPU sits right next to it — and after watching the video below, you'll never forget what makes them different.

The Video

In this clip, the Mythbusters team up with NVIDIA to demonstrate the difference using paintball guns. One gun fires one ball at a time (the CPU). A massive wall of guns fires thousands at once (the GPU). The result: the Mona Lisa, painted in about 80 milliseconds.

What to Watch For

The single-gun pass vs the wall of guns — notice how the single gun is accurate but painfully slow, while the wall completes the whole image almost instantly. That's the core trade-off: few fast cores vs many parallel ones.
How the final image comes together — the GPU rig doesn't paint one row at a time. Every part of the picture appears at once. That's parallelism in action.
The size of the rig — look at how many barrels are in the GPU wall. A real GPU has even more cores than that (modern ones have over 10 000).
Why accuracy per core matters less — each paintball lands roughly where it should, not perfectly. GPUs work the same way: individually simple, collectively powerful.

Last updated: April 2026.