Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

8-bit allgather support #722

Open
yaroslavvb opened this issue Sep 19, 2024 · 1 comment
Open

8-bit allgather support #722

yaroslavvb opened this issue Sep 19, 2024 · 1 comment
Labels
type/question An issue that's a question

Comments

@yaroslavvb
Copy link

❓ The question

Is there plan or any partial work done towards supporting 8-bit AllGather in Olmo?
https://dev-discuss.pytorch.org/t/enabling-float8-all-gather-in-fsdp2/2359

Authors observe 50% improvement in throughput for training Llama 70B with on-par numerics, which seems significant (depending on what "on par numerics" means)

@yaroslavvb yaroslavvb added the type/question An issue that's a question label Sep 19, 2024
@dirkgr
Copy link
Member

dirkgr commented Oct 19, 2024

My understanding is that 8 bit all_gather is something you would only do if you're already doing compute in 8 bit. We have an experimental branch for 8 bit compute here: https://github.com/allenai/OLMo-core/tree/epwalsh/float8-investigation. This is using the new, faster trainer. So far it is faster by an impressive margin (not 50% though), but we have not vetted it at larger scales.

8 bit all_gather would be another step after that.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
type/question An issue that's a question
Projects
None yet
Development

No branches or pull requests

2 participants