A small, header-only, parallel implementation of kmeans clustering for arbitrary-long byte vectors.
The code is inspired by the dkm library.
The code is tested on Linux with gcc and on MacOS with clang.
To build the code, CMake is required.
First clone the repository with
git clone --recursive https://github.com/jermp/kmeans.git
If you forgot --recursive when cloning, do
git submodule update --init --recursive
before compiling.
To compile the code for a release environment (see file CMakeLists.txt for the used compilation flags), it is sufficient to do the following, within the parent kmeans directory:
mkdir build
cd build
cmake ..
make -j
For a testing environment, use the following instead:
mkdir debug_build
cd debug_build
cmake .. -D CMAKE_BUILD_TYPE=Debug -D KMEANS_USE_SANITIZERS=On
make -j
Parallelism is achieved via OpenMP. To install it, do
brew install libomp
on a Mac, or
sudo apt install libomp
on Linux.
The tool tools/cluster can be used to cluster a collection of byte vectors.
We assume the input collection vectors.bin is a binary file where: the
first 8 bytes encode the number of bytes per vector, say p; the next 8 bytes encode the number
of vectors in the collection, say n; we have then p bytes for vector (a total of np bytes).
./cluster -i vectors.bin -k 16 -d 0.0 -s 13 > labels.txt
./cluster -i vectors.bin -m 7 -d 0.001 -s 13 --mse 500 --mcs 10 > labels.txt
./cluster -i vectors.bin -m 7 -d 0.001 -s 13 --mse 50 --mcs 1 > labels.txt