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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
  1. 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

License

Licensed under the term of MIT License.