Building reliable AI models > Insights by CINECA

From natural language processing to computer vision, AI has become an integral part of our daily lives.

However, building reliable AI models requires significant computational power, and that’s where GPUs come in.

More precisely, GPUs can handle:

• massive parallel processing, making AI models training faster and improving accuracy.
• large datasets and complex models due to their significant memory capabilities.

Nowadays, one of the most relevant applications in the AI field is LLM fine-tuning, which can be a computationally intensive process, requiring massive amounts of data and complex calculations. GPUs can accelerate these computations using parallelisation tools, reducing training times from days to hours or even minutes.

For example, a test on Leonardo GPUs (image below) shows that one epoch of fine-tuning using 32 GPUs is nearly 4 times faster than using only 8 GPUs, going from 11 to 3 minutes.