https://github.com/pragati-chaturvedi/basic-matrix-multiplication-cuda
This project demonstrates Basic Matrix Multiplication implemented using CUDA to accelerate matrix computations on an NVIDIA GPU. The code is designed to take two square matrices as input and multiply them in parallel, showcasing the power of CUDA in optimizing computational tasks.
https://github.com/pragati-chaturvedi/basic-matrix-multiplication-cuda
cpp cuda-programming gpu-computing nvidia-gpu parallel-programming
Last synced: about 2 months ago
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This project demonstrates Basic Matrix Multiplication implemented using CUDA to accelerate matrix computations on an NVIDIA GPU. The code is designed to take two square matrices as input and multiply them in parallel, showcasing the power of CUDA in optimizing computational tasks.
- Host: GitHub
- URL: https://github.com/pragati-chaturvedi/basic-matrix-multiplication-cuda
- Owner: pragati-chaturvedi
- Created: 2025-03-25T00:06:29.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-03-25T00:08:45.000Z (over 1 year ago)
- Last Synced: 2025-03-25T01:22:28.548Z (over 1 year ago)
- Topics: cpp, cuda-programming, gpu-computing, nvidia-gpu, parallel-programming
- Language: Cuda
- Homepage:
- Size: 321 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Basic Matrix Multiplication using CUDA
This repository demonstrates **Basic Matrix Multiplication*** using ***CUDA*** (Compute Unified Device Architecture), leveraging the parallel processing capabilities of ***NVIDIA GPUs*** to efficiently perform matrix operations. This project is designed to showcase how CUDA can accelerate computation tasks like matrix multiplication, which is fundamental in fields like machine learning, scientific computing, and graphics processing.
## Key Features
- **Matrix Multiplication**: Multiplies two square matrices in parallel.
- **CUDA Implementation**: Utilizes GPU for faster computation, reducing time complexity from \( O(n^3) \) to a more efficient approach using parallel threads.
- **Easy-to-Use**: Run matrix multiplication with minimal setup.
## Technologies Used
- **CUDA**: Parallel computing platform and programming model for NVIDIA GPUs.
- **C++**: Base code to implement the CUDA logic.
- **NVIDIA GPU**: Hardware for acceleration.