Parallelized K-means Clustering Algorithm
(using Pthreads and OpenMP API for C)

This is a parallelized implementation of the K-means clustering algorithm using Pthreads and also OpenMP in C.
The project contains the source files, scripts to compile and run, datasets generation files, speedup computation scripts and speedup visualisation scripts (using matplotlib)
A detailed discussion on the parallelization strategy is present in a contained report.
The report also contains the observed performance of the project on different datasets.
The speedup and efficiency plots obtained are in accordance with Amdahl's speedup law.

Name		Name	Last commit message	Last commit date
Latest commit History 56 Commits
datasets		datasets
2014CH10786.zip		2014CH10786.zip
Intro_To_OpenMP_Mattson.pdf		Intro_To_OpenMP_Mattson.pdf
Lab1_Report.pdf		Lab1_Report.pdf
Lab1_suite.zip		Lab1_suite.zip
README.md		README.md
compile_omp.sh		compile_omp.sh
compile_pthread.sh		compile_pthread.sh
compile_sequential.sh		compile_sequential.sh
dataset.py		dataset.py
lab1_io.c		lab1_io.c
lab1_io.h		lab1_io.h
lab1_omp.c		lab1_omp.c
lab1_omp.h		lab1_omp.h
lab1_pthread.c		lab1_pthread.c
lab1_pthread.h		lab1_pthread.h
lab1_sequential.c		lab1_sequential.c
lab1_sequential.h		lab1_sequential.h
main_omp.c		main_omp.c
main_pthread.c		main_pthread.c
main_sequential.c		main_sequential.c
openmp.pdf		openmp.pdf
run_omp.sh		run_omp.sh
run_pthread.sh		run_pthread.sh
run_sequential.sh		run_sequential.sh
time_script.py		time_script.py
time_script_speedup.py		time_script_speedup.py

arneish/parallel-k-means