This repository aims to benchmark classical vs. learned hash functions. For this purpose, it contains various state of the art implementations as well as benchmarking code.
For further information, see our collaborative google doc
The repository is setup as a monorepo c++ project using CMake.
convenience/contains an interface library comprised of convenience code (e.g., forceinline macros), used throughout the repositorydata/is meant to contain datasets. Also contains a python script for generating synthetic datasets and debug/test data. NOTE: datasets should under no circumstances be uploaded to github (licensing, large file size). Real world datasets from our results may be found herehashing/contains an interface library exposing various classical hash function implementations, optimized and tuned for small, fixed size keyslearned_models/contains an interface library exposing learned models, prepared to be used as a replacement for classical hash functionsreduction/contains an interface library implementing several methods for reducing hash values from [0, 2^p] to [0, N]results/contains benchmark results (csv) as well as plots and python code for generating said plotssrc/contains the actual benchmarking targets. Each target is implemented as a single .cpp file, linking against interface libraries from this repository aswell as shared convenience code found insrc/includethirdparty/contains an interface library exposing third party libraries used by this project, e.g., cxxopts for parsing benchmark cli arguments
Either clone with submodules in one command:
git clone --recurse-submodules <repo-url>
Or clone regularily and then perform
git submodule update --init --recursive
All benchmarks are implemented as single ".cpp" executable targets, located in src/. To run them, compile the corresponding target with cmake and execute the resulting binaries. To see the inline help text describing how to work with the benchmarks, simply execute the binary without arguments or with "-h" or with "--help".
Alternatively you may use the build.sh or benchmark.sh scripts. The latter will execute build.sh automatically.
See the results/ folder or, more specifically, the folders contained therein.