Closed
Conversation
|
What is the pr state now ? |
Member
Author
|
recent CUDA.jl PRs improving sparse support haven't made a tagged release yet (maybe they will be on CUDA 4.0?). |
|
Have these been PR's been merged yet? |
Member
Author
|
closing in favor of #220 |
This file contains hidden or 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
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
3 participants
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Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be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.
With JuliaGPU/CUDA.jl#1380 merged in CUDA#master, the possibility to have sparse cuda arrays as graphs' backend and supporting graph algebraic operations on gpu becomes more real.
This PR replaces #66, and adds some workarounds that almost gets us there. Still some tests are failing though.
Related to #134.
Related CUDA issues are
JuliaGPU/CUDA.jl#1402 (fixed)
JuliaGPU/CUDA.jl#1403 (fixed)
JuliaGPU/CUDA.jl#1406
JuliaGPU/CUDA.jl#1407 (fixed)