Iterative CAGRA build temp memory space for graph
Nobody has claimed this yet.
- Dominant language
- Cuda
- Stars
- 854
- Forks
- 236
- Avg merge
- 3d 3h
- Merged PRs (30d)
- 62
Description
Tracking issue for PR discussion https://github.com/NVIDIA/cuvs/pull/1810#discussion_r3656926784
CAGRA's iterative build method needs to allocate a large temp array to store the matrix.
It is expected that we fit into device memory, but the allocation size is still large (n_rows * graph degree).
Is large_workspace_resource the right memory resource to allocate this?
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with the linked PR discussion and inspect the CAGRA iterative build path that allocates the temporary matrix. Determine whether large_workspace_resource is appropriate for the n_rows × graph-degree allocation. Done means the memory-resource choice is settled and reflected in the relevant implementation or discussion.
Written by the indexing model from the issue text.
Assessment
- Domain
- performance, search
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 30/100