Hardware built to run many calculations at once, powering AI training and inference.
A GPU is like a cafeteria kitchen at lunch rush. Not chatty, but it flips a thousand pancakes at once.
It trains big models. It runs AI replies. It helps make images. That is why GPU time can cost so much.
Pretraining
Pretraining depends more on GPU clusters as it gets larger.
Inference
GPU power often decides Inference speed and capacity.
Compute-race
Tight GPU supply can make the Compute-race more intense.
Foundation-model
A Foundation-model often needs many GPUs for a long training run.