Enable build_sorted_mst with data on host memory
#997
Conversation
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
jinsolp
added
feature request
7 tasks
divyegala
reviewed
Jun 10, 2025
cpp/src/cluster/detail/mst.cuh
Outdated
Comment on lines
201
to
205
| cuvs::distance::pairwise_distance(handle, | ||
| raft::make_const_mdspan(data_u.view()), | ||
| raft::make_const_mdspan(data_v.view()), | ||
| pairwise_dist.view(), | ||
| metric); |
There was a problem hiding this comment.
Based on your answer to my previous question, if using omp, I would also create new handles with streams picked from a pool for this call to saturate the GPU with concurrency (pairwise distance of 1 row at a time on the GPU will likely be slower than doing this on the CPU)
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Outdated suggestions cannot be applied.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.
Connecting knn graph requires the entire data to be on device memory to use
cuvs::sparse::neighbors::cross_component_nn.This PR enables connecting knn graph with data on host by randomly choosing edges between components. Thus, it ends up selecting
n_components-1number of edges and adds that to the msf to make an mst.