Aims to showcase the power of concurrency and multithreading across different programming environments by implementing matrix multiplication.
The project will demonstrate how to leverage the concurrency features of Java, C++, Go, and Python to improve the performance of a computationally intensive task like matrix multiplication.
- Concurrent multiplication of two matrices.
- Dynamic input of matrix sizes and values or generation of matrices with random values.
- Performance metrics comparing concurrent and sequential implementations.
- Multi-language support: Java, C++, Go, and Python.
- Java: Utilizing ExecutorService and Future for managing concurrent tasks.
- C++: Leveraging std::thread and std::future for multithreading.
- Go: Implementing goroutines and channels for concurrent execution.
- Python: Using concurrent.futures for threading or multiprocessing.
- Clone the Repository:
git clone https://github.com/siddhant-vij/Concurrent-Matrix-Multiplication.git
- Navigate to Language Directory:
cd Concurrent-Matrix-Multiplication/[language] - Install Dependencies: Standard instructions to be followed for each language, if any external dependency.
- Build and Run the Application: Standard instructions to be followed for each language.
Contributions are what make the open-source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.
- Fork the Project
- Create your Feature Branch:
git checkout -b feature/AmazingFeature
- Commit your Changes:
git commit -m 'Add some AmazingFeature' - Push to the Branch:
git push origin feature/AmazingFeature
- Open a Pull Request
Distributed under the MIT License. See LICENSE for more information.