[FEA] Batched indexes
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Description
I have a use case where there are multiple indexes on one device. The queries are also batched. For example, if there are N indexes, the query matrix has shape (N, Q, D). The expected return reshape is (N, Q, K).
The brute-force algorithm is pretty easy with numpy/cupy/torch. But is there a plan to implement this for IVF or more algorithms? Also, is there a guide for parallelizing this process using CPU threads?
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
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Research direction
Start by clarifying whether the requested scope covers batched IVF and other index algorithms, or only the brute-force case described with numpy/cupy/torch. Define the expected (N, Q, D) to (N, Q, K) behavior and whether CPU-thread parallelization belongs in this feature before identifying an implementation entry point.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- numpy
- Domain
- data
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100