https://github.com/duyanh711/parallel_programing
https://github.com/duyanh711/parallel_programing
Last synced: 4 months ago
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- Host: GitHub
- URL: https://github.com/duyanh711/parallel_programing
- Owner: duyanh711
- Created: 2024-12-18T12:11:30.000Z (6 months ago)
- Default Branch: main
- Last Pushed: 2024-12-19T10:53:12.000Z (6 months ago)
- Last Synced: 2024-12-19T11:33:40.069Z (6 months ago)
- Language: Cuda
- Size: 15.6 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Neural Network Implementation with CUDA
## Team Members
- 21120409 - Nguyễn Đức Duy Anh
- 21120167 - Cao Thị Yến Vy
- 21120451 - Lê Bảo Hiếu
## Project Description
This project implements a neural network using CUDA for parallel processing. The neural network consists of:
- Input layer: 784 neurons
- Two hidden layers: 128 neurons each
- Output layer: 10 neurons
The implementation includes:
- Forward and backward propagation
- Batch processing
- ReLU activation function
- Softmax output layer
- Cross-entropy loss function
## Requirements
- CUDA Toolkit (>= 10.0)
- GPU with compute capability >= 3.0
- GCC/G++ compiler
- Make build system
## Project Structure
```
Parallel_Programing/
├── device/
│ ├── neural_network.cuh
│ ├── cuda_utils.cuh
│ ├── data_loader.cuh
│ ├── kernels.cuh
│ ├── training.cuh
│ ├── neural_network.cu
│ ├── cuda_utils.cu
│ ├── data_loader.cu
│ ├── kernels.cu
│ ├── training.cu
│ └── main.cu
├── Makefile
└── README.md
```
## Building and Running
### Local Machine
1. Make sure CUDA toolkit is installed:
```bash
nvcc --version
```
2. Clone the repository:
```bash
git clone https://github.com/duyanh711/Parallel_Programing.git
cd Parallel_Programing
```
3. Build the project:
```bash
make
```
4. Run the project:
```bash
./main
```
### Google Colab
1. Create a new notebook and select GPU runtime
2. Mount your Google Drive (optional)
3. Clone the repository or upload project files
4. Install required dependencies:
```bash
!nvcc --version
```
5. Build and run:
```bash
!make
!./main
```