This repository provides a comprehensive, self-paced tutorial for learning CUDA high-performance programming, targeting individuals from beginners to advanced users. It offers a structured learning path with practical examples and optimization techniques for GPU computing, aiming to demystify complex CUDA concepts and accelerate development.

How It Works

The tutorial is organized into progressive learning modules, starting with environment setup and basic kernel development, moving through performance analysis with nvprof, and delving into advanced optimization strategies for common operations like matrix multiplication (GEMM) and convolutions. It emphasizes hands-on implementation and practical optimization techniques, including thread distribution, memory access patterns, bank conflict resolution, and vectorized operations.

Quick Start & Requirements

• Installation: No explicit installation command is provided; the content is primarily documentation-based.
• Prerequisites: A CUDA-capable GPU and the CUDA Toolkit are required.
• Resources: Access to the web version is available at https://cuda.keter.top/.
• Documentation: Detailed guides are available within the ./docs/ directory.

Highlighted Details

• Covers foundational CUDA concepts and advanced optimization techniques.
• Includes practical implementations and performance tuning for GEMM and convolutions.
• Features in-depth analysis of LLM inference technologies like Flash Attention, Continuous Batching, and vLLM internals.
• Offers a structured learning path from beginner ("Newbie Village") to advanced ("Master") levels.

Maintenance & Community

The project is hosted on GitHub under the PaddleJitLab organization. Star history is available via a provided SVG link. Further community or maintenance details are not specified in the README.

Licensing & Compatibility

The repository's license is not explicitly stated in the provided README.

Limitations & Caveats

The "Master Series" and some "Advanced Series" topics are marked as "to be supplemented," indicating incomplete content in those areas. The project's primary focus is on learning and understanding, not necessarily providing production-ready libraries.