Comments (3)
jegou
commented on May 27, 2024
1
Right. Yet, for this size of the problem (very small considering that Faiss is typically designed for dozen millions to billions of vectors), brute-force will certainly be the fastest way to compute the ClosestPairOfPoints, especially if you use the GPU implementation.
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jegou
commented on May 27, 2024
Faiss is not specifically designed for this, but you can easily use it to compute
min d(a,b) for all a,
and then task the min over a
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vadimkantorov
commented on May 27, 2024
Thanks for the lightning-fast answer :) Sure, I was wondering if one can do it in sub-linear time.
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Related Issues (20)
- Is it possible to lazy load index from disk? HOT 1
- Binary embeddings score normalization HOT 1
- No conda package for faiss-cpu 1.8.0 for osx-64 on pytorch channel HOT 5
- Static library libfaiss_gpu.a not installed HOT 1
- faiss_gpu object is not linked to static library libfaiss.a HOT 3
- Error when building static library for AVX2 and GPU HOT 2
- Cannot debug similarity search HOT 1
- Add a tutorial for IndexHNSW HOT 3
- Segfault error on faiss.IndexIVFFlat().train HOT 1
- knn_gpu should use raft when raft is compiled in HOT 2
- ImportError: /lib64/libstdc++.so.6: version `GLIBCXX_3.4.20' not found HOT 1
- Remove lapack dependency? HOT 1
- Faiss imported after Torch leads to segfault HOT 2
- Suggestions on implementing multi-scale quantization HOT 3
- The similarity results obtained from the index.faiss file are significantly different from those obtained from previous versions HOT 1
- inquiry related to DistanceComputer HOT 2
- Failed to install via poetry HOT 1
- Update the raft handle through StandardGpuResourcesImpl::setDefaultStream
- [Feature Request] GPU indices Provide Interface to Access Resource HOT 2
- faiss index and retriever not able to save HOT 1
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