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Performance: upgrade to latest ann-benchmarks #655

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merged 7 commits into from
Mar 25, 2024
Merged

Performance: upgrade to latest ann-benchmarks #655

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bb48ac7
Performance: upgrade to latest ann-benchmarks
alexklibisz Mar 23, 2024
94aba39
Updated benchmarks
Mar 23, 2024
cb75d06
Merge remote-tracking branch 'origin/main' into upgrade-ann-benchmarks
alexklibisz Mar 24, 2024
57eda0f
Merge branch 'upgrade-ann-benchmarks' of github.com:alexklibisz/elast…
alexklibisz Mar 24, 2024
de36373
benchmarks
Mar 25, 2024
02ec7ef
Benchmark
Mar 25, 2024
f90dc46
Benchmarks
Mar 25, 2024
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4 changes: 2 additions & 2 deletions .gitmodules
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Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
[submodule "ann-benchmarks/ann-benchmarks"]
path = ann-benchmarks/ann-benchmarks
url = https://github.com/alexklibisz/ann-benchmarks.git
branch = fix-get-algorithm-definitions
url = https://github.com/erikbern/ann-benchmarks.git
branch = main
2 changes: 1 addition & 1 deletion ann-benchmarks/ann-benchmarks
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Submodule ann-benchmarks updated 166 files
2 changes: 1 addition & 1 deletion docs/pages/performance/fashion-mnist/plot.b64
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16 changes: 8 additions & 8 deletions docs/pages/performance/fashion-mnist/results.md
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|Model|Parameters|Recall|Queries per Second|
|---|---|---|---|
|eknn-l2lsh|L=100 k=4 w=1024 candidates=500 probes=0|0.378|382.992|
|eknn-l2lsh|L=100 k=4 w=1024 candidates=1000 probes=0|0.446|322.386|
|eknn-l2lsh|L=100 k=4 w=1024 candidates=500 probes=3|0.634|301.434|
|eknn-l2lsh|L=100 k=4 w=1024 candidates=1000 probes=3|0.716|266.643|
|eknn-l2lsh|L=100 k=4 w=2048 candidates=500 probes=0|0.767|340.303|
|eknn-l2lsh|L=100 k=4 w=2048 candidates=1000 probes=0|0.847|294.373|
|eknn-l2lsh|L=100 k=4 w=2048 candidates=500 probes=3|0.922|233.123|
|eknn-l2lsh|L=100 k=4 w=2048 candidates=1000 probes=3|0.960|207.765|
|eknn-l2lsh|L=100 k=4 w=1024 candidates=500 probes=0|0.379|392.939|
|eknn-l2lsh|L=100 k=4 w=1024 candidates=1000 probes=0|0.447|334.503|
|eknn-l2lsh|L=100 k=4 w=1024 candidates=500 probes=3|0.635|308.154|
|eknn-l2lsh|L=100 k=4 w=1024 candidates=1000 probes=3|0.717|270.359|
|eknn-l2lsh|L=100 k=4 w=2048 candidates=500 probes=0|0.767|347.401|
|eknn-l2lsh|L=100 k=4 w=2048 candidates=1000 probes=0|0.847|296.976|
|eknn-l2lsh|L=100 k=4 w=2048 candidates=500 probes=3|0.922|238.273|
|eknn-l2lsh|L=100 k=4 w=2048 candidates=1000 probes=3|0.960|210.018|
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