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Parallelized K-means clustering and BFS algorithms using OpenMP and MPI.

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Parallel Computing Project

Overview

This project explores the parallelization of K-means clustering and Breadth-First Search (BFS) algorithms using OpenMP and MPI. The implementation and analysis were conducted on a laptop with an Intel Core i5-1035G4 processor, 15.6 GB RAM, running Windows, utilizing Visual Studio Code and MPI SDKs for C/C++.

Contents

  • .kmeans_openmp: Source code for K-means clustering with OpenMP.
  • .kmeans_mpi: Source code for K-means clustering with MPI.
  • .bfs_openmp: Source code for BFS with OpenMP.
  • .bfs_mpi: Source code for BFS with MPI.
  • ./data: Results from experiments with varying data sizes.

Usage

  1. Clone the Repository:
    git clone https://github.com/your-username/parallel-computing-project.git
    cd parallel-computing-project

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Parallelized K-means clustering and BFS algorithms using OpenMP and MPI.

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