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Efficient Bloom filters for OCaml

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Bloomf - Efficient Bloom filters for OCaml Build Status

Benchmarks

Micro benchmarks are provided for create, add and mem operations. Expected error rate is 0.01.

name major-allocated minor-allocated monotonic-clock
bloomf/add 10000 0.0045 mw/run 26.0055 w/run 469.9798 ns/run
bloomf/add 100000 0.0044 mw/run 26.0054 w/run 468.8711 ns/run
bloomf/add 1000000 0.0044 mw/run 26.0054 w/run 465.9688 ns/run
bloomf/create 10000 1548.2850 mw/run 225.1115 w/run 10004.2279 ns/run
bloomf/create 100000 15464.1941 mw/run 261.4265 w/run 52229.0413 ns/run
bloomf/create 1000000 154617.1529 mw/run 217.6108 w/run 584479.5283 ns/run
bloomf/find (absent) 10000 0.0017 mw/run 8.0038 w/run 354.4163 ns/run
bloomf/find (absent) 100000 0.0017 mw/run 8.0038 w/run 358.0275 ns/run
bloomf/find (absent) 1000000 0.0025 mw/run 11.0044 w/run 401.7930 ns/run
bloomf/find (present) 10000 0.0048 mw/run 26.0060 w/run 525.7296 ns/run
bloomf/find (present) 100000 0.0046 mw/run 26.0057 w/run 480.7180 ns/run
bloomf/find (present) 1000000 0.0044 mw/run 26.0054 w/run 465.8766 ns/run

They preform OLS regression analysis using the development version of bechamel. To reproduce them, pin bechamel then run make bench.