Welcome to the CUDA Developer Guide! This document provides essential information for developers working with NVIDIA's CUDA platform. Whether you're new to GPU programming or looking to optimize your existing workflows, this guide will help you get started.

📌 Overview

CUDA (Compute Unified Device Architecture) is a parallel computing platform and programming model developed by NVIDIA. It enables developers to harness the power of GPUs for general-purpose computing.

NVIDIA_GPU

💻 Installation & Setup

  1. Install CUDA Toolkit: Download from NVIDIA's official website
  2. Set Environment Variables: Configure CUDA_HOME and PATH for system-wide access
  3. Verify Installation: Run nvcc --version in your terminal
Install_Cuda

🔧 Programming Model

CUDA programming involves:

  • Kernels: Functions executed on the GPU
  • Memory Management: Use __global__, __shared__, and __constant__ memory spaces
  • Threads & Blocks: Organize parallel execution with thread hierarchies
Parallel_Processing

📈 Performance Optimization

To maximize GPU performance:

  • Use coalesced memory access
  • Optimize thread block size
  • Leverage CUDA Streams for concurrent execution
Performance_Tuning

📚 Further Reading

For more details, check out:

Cuda_Developer_Guide

Explore the power of GPU computing with CUDA today! 🌟