Process-and-Thread-Management-in-C

This repository contains a C program that demonstrates matrix multiplication using different approaches, highlighting the impact of optimization techniques such as multiprocessing and multithreading. We will compare the performance of:

1. Naive Matrix Multiplication: A straightforward, single-threaded implementation.
2. Multiprocessing: Matrix multiplication divided across multiple processes.
3. Multithreading (Joinable Threads): Parallel matrix multiplication using joinable threads.
4. Multithreading (Detached Threads): Parallel matrix multiplication using detached threads.

Features

• Naive Implementation: The traditional approach to matrix multiplication, iterating over the rows and columns in a nested loop structure.
• Multiprocessing: Utilizes multiple processes to handle different portions of the matrix multiplication task, improving performance by distributing the workload.
• Multithreading:
  • Joinable Threads: Threads are created to perform matrix multiplication concurrently, and the main thread waits for them to finish.
  • Detached Threads: Threads run independently without requiring the main thread to wait, increasing potential parallelism but requiring careful management of resources.

Performance Comparison

For each method, the program measures the execution time and throughput, demonstrating the advantages and trade-offs of using multiprocessing and multithreading.

Results

The program will output the time taken for matrix multiplication using each method, allowing you to observe the impact of process and thread management on performance.