Optimization Project

This project was developed as part of a university course on Parallel Programming. The primary objective is to explore and implement optimization techniques in C, both in sequential and parallelized contexts, while maintaining accuracy and efficiency.

Project Overview

This project focuses on optimizing a dummy application that simulates real-world data processing. The goal was to improve runtime performance through both algorithmic and parallel computing strategies. The project involves:

• Reading and processing datasets containing IDs and numerical values.
• Filtering and combining data based on specific rules.
• Using advanced data structures like hash tables for efficient lookups.
• Parallelizing computationally intensive tasks using OpenMP.

The results are saved in a CSV file with processed and sorted data.

Repository Structure

The repository is organized into the following directories:

optimization_project/
├── db/                # Contains database files and generator script
│   ├── db.c           # Code to generate the dataset
│   ├── A.txt          # Dataset A
│   ├── B.txt          # Dataset B
│   ├── ids.txt        # Dataset of IDs
├── src/               # Source code files for the project
│   ├── seq.c          # Baseline sequential implementation
│   ├── main.c         # Optimized implementation using hash tables and pre-filtering
│   ├── mainParalel.c  # Parallelized implementation using OpenMP
│   ├── filters.c      # Filtering logic
│   ├── ids.c          # ID processing and hash table logic
├── doc/               # Documentation directory
│   ├── solution.md    # Detailed explanation of the solution
├── tutorial/          # Compilation and execution tutorial
│   ├── tutorial.md    # Step-by-step guide for setup and usage
└── README.md          # Repository overview (this file)

How to Use

1. Clone the Repository:

   git clone https://github.com/your-username/optimization_project.git
   cd optimization_project

2. Compile the Code: Follow the instructions in the tutorial/tutorial.md file to compile and execute the project.

3. Understand the Implementation: Refer to the doc/solution.md file for an in-depth explanation of the project’s implementation and optimization techniques.

About

This project demonstrates the application of parallel programming concepts, including optimization techniques and the trade-offs involved in parallelizing computations. It highlights the benefits and challenges of parallel execution while showcasing algorithmic improvements for sequential processing.