Inside FAISS: Billion-Scale Similarity Search
How Facebook AI Research solved the problem of finding similarity at billion-scale. An interactive exploration of IVF, HNSW, and Product Quantization.
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Author here. I wrote this as a visual companion to the 2017 FAISS paper (https://arxiv.org/abs/1702.08734), focused on the parts I found hardest to grok from text alone.
The article covers a subset of what FAISS does, with the paper as the source of truth. NSG, FastScan, IMI are not covered here, they'll get their own articles. I'd be especially interested in feedback on:
- the IVFPQ / IVFADC explanation, particularly the LUT reuse argument
- whether the GPU part captures enough of the actual complexity
Happy to answer questions.
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