Skip to content
This repository has been archived by the owner on Feb 7, 2023. It is now read-only.

gemm: fp16 tensorcore fixes #1211

Closed

Conversation

lukeyeager
Copy link
Contributor

No description provided.

The algo and compute type must match - you can't try to use
CUBLAS_GEMM_DFALT without also calling
cublasSetMathMode(..., CUBLAS_TENSOR_OP_MATH).
The change is very small if you ignore whitespace changes
@akyrola
Copy link
Contributor

akyrola commented Oct 23, 2017

This one is over one month old, is it still relevant?

@lukeyeager
Copy link
Contributor Author

Yes. I'm surprised nobody has complained about these issues yet. Presumably y'all don't run any tensorcore tests on non-Volta hardware.

Copy link
Contributor

@facebook-github-bot facebook-github-bot left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

@akyrola has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator.

@akyrola
Copy link
Contributor

akyrola commented Oct 23, 2017

Ok, processing it. Thanks!

@orionr
Copy link
Contributor

orionr commented Sep 27, 2018

Thank you for your contribution! PyTorch and Caffe2 are now officially merged with the PyTorch 1.0 preview release. Please submit on https://github.com/pytorch/pytorch if this is still an issue over there.

@orionr orionr closed this Sep 27, 2018
@lukeyeager lukeyeager deleted the gemm-fp16-tensorcore-fixes branch September 27, 2018 21:15
Sign up for free to subscribe to this conversation on GitHub. Already have an account? Sign in.
Projects
None yet
Development

Successfully merging this pull request may close these issues.

4 participants