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https://github.com/aaditya29/parallel-computing-and-cuda
Learning about Parallel Computing and GPU programming using CUDA.
https://github.com/aaditya29/parallel-computing-and-cuda
c cpp cuda cuda-kernels cuda-programming nvidia-cuda openmp openmpi parallel-computing parallel-programming
Last synced: 6 days ago
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Learning about Parallel Computing and GPU programming using CUDA.
- Host: GitHub
- URL: https://github.com/aaditya29/parallel-computing-and-cuda
- Owner: aaditya29
- Created: 2024-07-13T07:19:24.000Z (7 months ago)
- Default Branch: main
- Last Pushed: 2024-07-31T13:29:26.000Z (7 months ago)
- Last Synced: 2024-12-14T07:16:35.028Z (2 months ago)
- Topics: c, cpp, cuda, cuda-kernels, cuda-programming, nvidia-cuda, openmp, openmpi, parallel-computing, parallel-programming
- Language: C++
- Homepage:
- Size: 47.9 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: readme.md
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README
# Parallel Computing and CUDA Learning Repository
Welcome to the Parallel Computing and CUDA Learning Repository! This repository is designed as a comprehensive reference for anyone interested in learning about Parallel Computing and GPU programming using CUDA.
## Table of Contents
- [Introduction](#introduction)
- [Prerequisites](#prerequisites)
- [Getting Started](#getting-started)
- [Core Concepts](#core-concepts)
- [CUDA Programming](#cuda-programming)
- [Advanced Topics](#advanced-topics)
- [Projects](#projects)
- [Additional Resources](#additional-resources)
## Introduction
Parallel computing allows you to perform many calculations simultaneously, leveraging the power of modern multi-core processors and GPUs. CUDA (Compute Unified Device Architecture) is a parallel computing platform and application programming interface (API) model created by NVIDIA. It allows developers to use GPUs for general purpose processing.
This repository aims to provide a structured path to learn parallel computing and CUDA programming from scratch. Whether you're a beginner or have some experience, you'll find valuable resources and practical examples to enhance your understanding.
## Prerequisites
Before you begin, ensure you have the following:
- Basic understanding of programming concepts
- Familiarity with C/C++ programming languages
- Basic understanding of computer architecture
- Familiarity with algorithms and data structures
- A CUDA-capable NVIDIA GPU
## Getting Started
To get started with this repository:
1. **Clone the repository**:
```bash
git clone https://github.com/aaditya29/Parallel-Computing-And-CUDA
cd Parallel-Computing-And-CUDA
```
2. **Set up your development environment:** Configure your IDE or text editor for CUDA development.
3. **Explore the tutorials and examples**:
- Navigate through the directories and start with the basic tutorials to get a grasp of fundamental concepts.
## Core Concepts
This section covers fundamental concepts in parallel computing:
- Parallel vs. Sequential Computing
- Amdahl's Law and Gustafson's Law
- Types of Parallelism (Data, Task, Pipeline)
- Parallel Architectures (SIMD, MIMD)
- Synchronization and Communication
## CUDA Programming
Learn the basics of CUDA programming:
- CUDA Programming Model
- Thread Hierarchy (Grid, Block, Thread)
- Memory Hierarchy (Global, Shared, Local, Constant)
- Kernel Functions
- Device Management
- Error Handling
## Advanced Topics
Explore more advanced concepts in CUDA:
- Stream Processing
- Dynamic Parallelism
- Unified Memory
- Multi-GPU Programming
- CUDA Libraries (cuBLAS, cuDNN, Thrust)
- Performance Optimization Techniques
## Projects
## Additional Resources
- [NVIDIA CUDA Documentation](https://docs.nvidia.com/cuda/)
- [Parallel Computing: Theory and Practice](https://www.cs.cmu.edu/~guyb/paralg/)
- [CUDA by Example: An Introduction to General-Purpose GPU Programming](https://developer.nvidia.com/cuda-example)
- [Introduction to Parallel Programming in Open MP](https://www.youtube.com/playlist?list=PLp6ek2hDcoNBAyEJmxsOowMYNTKsUmTZ8)
- [Parallel C++](https://youtube.com/playlist?list=PLxNPSjHT5qvsGKsAhirvZn7W73pXhXpfv)
- [Practical Parallelism in C++](https://www.youtube.com/playlist?list=PLxNPSjHT5qvugVNYwtQwnvSQyvlbzAML3)
- [Introduction to Parallel Programming with CUDA](https://newfrontiers.illinois.edu/news-and-events/introduction-to-parallel-programming-with-cuda/)
- [CUDA Crash Course](https://www.youtube.com/playlist?list=PLxNPSjHT5qvtYRVdNN1yDcdSl39uHV_sU)
- **Jeremy Howard Lectures**
- **Programming Massively Parallel Processors: A Hands-on Approach Book**