A parallelized version of the Jacobi Method
Master Degree (Artificial Intelligence)
SPM course, Academic Year: 2021/2022, University of Pisa, Italy.
🔍 Abstract
The Jacobi Method is an algorithm for finding the solution of a system of linear equations Ax = b. This C++ project aims to implement a sequential version of this algorithm, a parallelized version using native threads, and finally a parallel version with Fast Flow.
🔧 Setup
To make compilation and execution easier and faster, you can run the bash script:
./run.sh
If necessary, you can still change any parameter by first compiling the program by running the command: make and then:
./main.out <params>
where parameters are the following:
| parameter | domain | default value |
|---|---|---|
| n | integer ≥ 0 | 5000 |
| num_of_worker | integer > 0 | 100 |
| num_of_iterations | integer > 0 | 10 |
| calculate_results | boolean (∈ {0, 1}) | 0 |
| early_stopping | boolean (∈ {0, 1}) | 1 |
| execute_unit_test | boolean (∈ {0, 1}) | 1 |
Main Files
📦
┣ 📂 calculate_results
┣ 📂 setup
┣ 📂 solutions
┣ 📂 unit_test
┣ 📂 utils
┗ 📜 main.cpp