Parallel K-Means - Parallel Computing Project

Project for Parallel Computing course. Sequential and parallel implementations of K-Means algorithm in C++ with OpenMP and CUDA. The sequential K-Means version is compared with two parallel versions, tests include execution times and the speedup of each version.

More information can be found in the report of the project: Report.

Installation

1. Clone the repo.

git clone https://github.com/elia-mercatanti/parallel-k-means

2. Build with CMake.

Usage

• For testing K-Means algorithm with all implementations to search clusters on a dataset, pass two arguments:

parallel_kmeans <dataset file path> <number of clusters>

• For generating random datasets according to global variables, pass no arguments:

parallel_kmeans <>

Authors

• Elia Mercatanti - GitHub: elia-mercatanti
• Marco Calamai - GitHub: marcocalamai

License

Licensed under the term of MIT License.