Infrastructure & Compute
GPU
Graphics processing unit
A processor well suited to the parallel calculations used in training and running many AI models.
Example
A GPU trains a neural network by performing many matrix calculations in parallel.
Why it matters
It can speed up the many simultaneous calculations used by AI.
You'll hear it
“The calculation is fast, but the model doesn't fit in memory.”
Can you control it?
Set by the team
The people building or running the AI choose this setup. An everyday user generally needs their help to change how this part works.
Common questions
- Does every AI task need a GPU?
- No. Some work can run effectively on other processors.
- Does a newer GPU automatically speed up every application?
- No. Software support and other system limits can determine the benefit.
- Can several users share a GPU?
- Yes, depending on the setup, though competing work can affect performance.