Allow SparseArrays to catch lu(::WrappedSparseMatrix)
#51161
Merged
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
|
Ping @vtjnash. |
|
I haven't the slightest idea how this is designed currently, but I assume this is similar to your work on |
ViralBShah
pushed a commit
that referenced
this pull request
Sep 7, 2023
This is a follow-up to #51161. It introduces one level in the promotion pipeline which allows to call out-of-place versions of `cholesky` and `qr` for arguments whose `similar` copy yields a `SparseMatrixCSC`.
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Over the
AbstractMatrixrelaxation in v1.9, we missed a potential indirection for wrapped sparse matrices. Instead, by default, asimilarcopy is created (hence a sparse matrix) and thenlu!with a pivot argument is called. Such a method, however, does not exist in SparseArrays.jl, which means that thegeneric_lufact!method gets called, which is probably really bad performance-wise, due to heavy reading and writing into the sparse matrix. This PR introduces one more level at which SparseArrays.jl (and perhaps other external packages) may interfere and redirect to their own implementations, in-place or out-of-place.