-
Notifications
You must be signed in to change notification settings - Fork 53
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
Refactoring of QR: try out pure stabilized Gram-Schmidt (split=1) and TS-QR (split=0) #1237
Labels
Comments
Branch features/1237-Try_out_pure_stabilized_Gram-Schmidt_for_QR created! |
This issue is stale because it has been open for 60 days with no activity. |
This was referenced Jan 22, 2024
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
This issue is to suggest refactoring of the code for QR decomposition.
Currently, a quite elaborate algorithm is used for QR. The following suggestions might turn out to be actually faster or at least less prone to errors:
In the case of split=1, a straight-forward block-wise adaptation of stabilized Gram-Schmidt might be faster since this can exploit the highly optimized PyTorch-QR. This applies to split=1.
For split=0, a pure TS-QR might be an option.
The text was updated successfully, but these errors were encountered: