K-Nearest Neighbors Implementation in Parallel Programming and Cloud Computing

This project represents our culminating work for the CSS534: Parallel Programming in Grid and Cloud course. Our chosen focus was to develop a parallel application using a diverse set of tools and frameworks: mpiJava, MapReduce, Spark, and the Multi-Agent Spatial Simulation (MASS) library. Our task was to examine their programmability and execution performance. We chose to work with the k-nearest neighbors (KNN) algorithm, implementing parallel versions of it using each of the aforementioned technologies.

Term: Autumn 2022

Author

• Warren Liu
• Chris Ma
• Chengjun Xi

Project Division

1. MPIJava: Warren Liu
2. MapReduce: Chris Ma
3. Spark: Chengjun Xi
4. MASS: Together