https://github.com/arya2004/parallel-computing
Parallel Computing Uni Course
https://github.com/arya2004/parallel-computing
cuda
Last synced: 20 days ago
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Parallel Computing Uni Course
- Host: GitHub
- URL: https://github.com/arya2004/parallel-computing
- Owner: arya2004
- License: mit
- Created: 2025-09-17T17:43:39.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2025-10-29T18:45:13.000Z (7 months ago)
- Last Synced: 2025-12-31T21:44:30.771Z (5 months ago)
- Topics: cuda
- Language: Cuda
- Homepage:
- Size: 30.3 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
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README
# Parallel Computing
Works only on systems with NVIDIA GPU and proper CUDA drivers.
This repository contains CUDA/C++ source codes for all major practicals and assignments of the undergraduate Parallel Computing course, covering topics such as Amdahl’s Law, vector and matrix operations, shared memory, reduction, texture memory, image processing, and lightweight scientific applications.
---
## Installation (Ubuntu)
1. **Install CUDA Toolkit**
```bash
sudo apt update
sudo apt install nvidia-cuda-toolkit
nvcc --version
```
2. **Install OpenCV (for image processing codes)**
```bash
sudo apt install libopencv-dev
pkg-config --modversion opencv4
```
3. **Install Build Essentials**
```bash
sudo apt install build-essential cmake git pkg-config
```
---
## Compilation and Execution
Compile a CUDA file:
```bash
cd src
nvcc 02_vector_addition_1d.cu -o vector_add
./vector_add
```
Compile a CUDA file using OpenCV:
```bash
nvcc -std=c++17 06_image_processing.cu -o image_proc `pkg-config --cflags --libs opencv4`
./image_proc
```