One major run-time bottleneck in multi-GPU training happens during GPU synchronization.

For instance, in multi-GPU training via data parallelism:

– The same model is distributed to different GPUs.
– Each GPU processes a different subset of the whole dataset.

Check this 👇 pic.twitter.com/3YwSo3L7gh

— Akshay 🚀 (@akshay_pachaar) 17 août 2025

One major run-time bottleneck in multi-GPU training happens during GPU synchronization. For instance, in multi-GPU training via data parallelism: – The same model is distributed to different GPUs.
– Each GPU processes a different subset of the whole dataset. Check this

→ View original post on X — @akshay_pachaar