jtibshirani edited a comment on issue #1314: LUCENE-9136: Coarse quantization that reuses existing formats. URL: https://github.com/apache/lucene-solr/pull/1314#issuecomment-608645326 **Benchmarks** In these benchmarks, we find the nearest k=10 vectors and record the recall and queries per second. For the number of centroids, we use the heuristic num centroids = sqrt(dataset size). sift-128-euclidean: a dataset of 1 million SIFT descriptors with 128 dims. ``` APPROACH RECALL QPS LuceneExact() 1.000 6.425 LuceneCluster(n_probes=5) 0.756 604.133 LuceneCluster(n_probes=10) 0.874 323.791 LuceneCluster(n_probes=20) 0.951 166.580 LuceneCluster(n_probes=50) 0.993 68.465 LuceneCluster(n_probes=100) 0.999 35.139 ``` glove-100-angular: a dataset of ~1.2 million GloVe word vectors of 100 dims. ``` APPROACH RECALL QPS LuceneExact() 1.000 6.764 LuceneCluster(n_probes=5) 0.681 642.247 LuceneCluster(n_probes=10) 0.768 343.067 LuceneCluster(n_probes=20) 0.836 177.037 LuceneCluster(n_probes=50) 0.908 73.256 LuceneCluster(n_probes=100) 0.951 37.302 ``` These benchmarks were performed using the [ann-benchmarks repo](https://github.com/erikbern/ann-benchmarks). The branch and instructions for benchmarking can be found here: https://github.com/jtibshirani/ann-benchmarks/pull/2.
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