kaivalnp commented on PR #14178:
URL: https://github.com/apache/lucene/pull/14178#issuecomment-2622946390

   > FAISS with this vector dimension does seem about 20% faster at search
   
   I should add here that Lucene was using vectorized instructions via Panama, 
but the C_API of Faiss was not..
   I tweaked the offline build to use AVX512 instructions from Faiss as well 
(basically link it to `libfaiss_avx512.so` instead of `libfaiss.so`):
   
   Lucene:
   ```
   recall  latency (ms)    nDoc  topK  fanout  maxConn  beamWidth  quantized  
index s  index docs/s  force merge s  num segments  index size (MB)  vec disk 
(MB)  vec RAM (MB)
    0.812         1.424  200000   100      50       32        200         no   
145.30       1376.49           0.01             1           236.93        
228.882       228.882
   ```
   
   Faiss:
   ```
   recall  latency (ms)    nDoc  topK  fanout  maxConn  beamWidth  quantized  
index s  index docs/s  force merge s  num segments  index size (MB)  vec disk 
(MB)  vec RAM (MB)
    0.811         1.127  200000   100      50       32        200         no   
129.18       1548.20           0.01             1           511.20        
228.882       228.882
   ```
   
   ..and we do see slightly faster indexing times
   
   > number of vectors it must visit when searching the graph
   
   Faiss has an 
[`HNSWStats`](https://github.com/facebookresearch/faiss/blob/1334d169b9279a8c581835ef6025f4752b246ce8/faiss/impl/HNSW.h#L234)
 struct exposed via a [global 
variable](https://github.com/facebookresearch/faiss/blob/1334d169b9279a8c581835ef6025f4752b246ce8/faiss/impl/HNSW.h#L256)
 -- I'll try to access this from Java somehow


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