Welcome to your comprehensive CUDA programming journey! This guide provides everything you need to start programming with CUDA. You will learn how to utilize the power of GPU programming through clear lessons and examples.
To begin using the application, follow these steps:
- Visit the Releases Page: Go to the Releases page to find the latest version of the software.
- Download the Required Files: Click on the version that interests you and download the necessary files to your computer.
- Extract the Files: Once downloaded, locate the zipped file in your Downloads folder. Right-click on it and select "Extract All".
- Run the Application:
- Open your terminal or command line interface.
- Navigate to the directory where you extracted the files using the following command:
cd ~/cuda-learning
- Run the application with this command:
./START
You are now ready to start your journey into CUDA programming!
- Lesson 01: First Kernel - Your first GPU program. This lesson introduces you to the basic structure of a CUDA program and guides you through your first GPU kernel.
- Lesson 02: Thread & Blocks - Understanding parallelism. Learn how to organize and manage threads for better performance.
- Lesson 03: Array Operations - Parallel data processing. Explore how to handle arrays efficiently across threads.
- Lesson 04: Memory Model - GPU memory hierarchy. Understand the types of memory available and how to optimize your memory usage.
- Lesson 05: Vector Addition - Complete application. Build a simple yet complete application to reinforce the basics you've learned.
- Lesson 06: Shared Memory - Fast on-chip memory. Discover the power of shared memory to speed up your applications.
- Lesson 07: Parallel Reduction - Tree-based algorithms. Understand how to efficiently reduce data using parallel algorithms.
- Lesson 08: CUDA Streams - Explore how streams enhance the performance of your CUDA applications by allowing multiple operations to run concurrently.
To get started, download the application from the Releases page.
- Operating System: Compatible with Windows, macOS, and Linux.
- CUDA Toolkit: Ensure you have the CUDA Toolkit installed on your system. The latest version is recommended for optimal performance.
- GPU: A CUDA-capable GPU is required. Check with NVIDIA for a list of supported GPUs.
- Follow the steps in the "Getting Started" section to download and set up the application.
- Refer to the curriculum structure to navigate through the lessons and apply your new skills.
- CUDA Documentation: For a deeper understanding, you can visit the NVIDIA CUDA documentation.
- Community Forums: Join CUDA forums or Discord channels to interact with fellow learners and get help when needed.
With this guide, you should feel confident in your ability to start programming with CUDA.