Awesome

bigann

This mini crate benches the crate hnsw-rs on sampled u8 vectors from the BIGANN benchmark. See BIGANN and IRISA

Files bigann_base.bvecs, bigann_query.bvecs must be dowloaded and installed in some directory (This amounts to 133Gb). Then depending on the size of the data you want to run on the first (10M, 100M, 1B) of the large file bigann_base.bvecs you download the corresponding ground truth as explained in the BIGANN web page.

To run on the first 10M slices of data you download the corresponding ground truth corresponding to this size and extract the file GT_10M/bigann-10M to replace the file public_query_gt100.bin which corresponds to the ground truth on the totality, and check in source the name of file to load ground truth.

commandline

bigann --dir DataDir -hnsw dumpname or bigann --dir DataDir --nbdata 10 (or 100 or 1000) to specify the number million data you want to run.
For more see documentation (cargo doc --no-dpes as usual)

Results for the first 10 Million data points.

Results on Intel E5-2630 v3 @2.4GHz 16 cores 2 thread / core

All parameters are explained in doc of hnsw-rs.

knbn	max_nb_conn	ef_cons	ef_search	extend	keep pruned	recall	req/s	last ratio
10	64	100	128	no	no	0.995	2610	1.0002
100	64	100	128	no	no	0.983	1350	1.0006
10	24	100	128	no	no	0.970	4845	1.001
100	24	100	128	no	no	0.923	2411	1.003

Results on Laptop with i7-10875H CPU @ 2.30GHz 8 core 2 Thread /core

time for Hnsw structure construction user :1370 s, cpu time 21493

knbn	max_nb_conn	ef_cons	ef_search	extend	keep pruned	recall	req/s	last ratio
10	24	100	128	no	no	0.960	5900	1.001
100	24	100	128	no	no	0.907	2800	1.004
10	24	400	128	no	no	0.972	4678	1.001
100	24	400	128	no	no	0.938	2338	1.003
10	24	800	128	no	no	0.975	4313	1.001
100	24	800	128	no	no	0.9428	2151	1.0025