GPU Puzzles is an educational project designed to teach GPU programming concepts through interactive coding exercises and puzzles. Instead of presenting traditional lecture-style explanations, the project immerses learners directly in hands-on programming tasks that demonstrate how GPU computation works. The exercises are implemented using Python with the Numba CUDA interface, which allows Python code to compile into GPU kernels that run on CUDA-enabled hardware. By solving progressively more complex puzzles, learners gain a practical understanding of how parallel algorithms operate on graphics processing units. The project emphasizes experimentation and problem solving, encouraging learners to discover GPU programming techniques through trial and exploration. It can be run in cloud environments such as Google Colab, making it easy for beginners to start experimenting without configuring local GPU hardware.
Features
- Interactive coding puzzles for learning GPU programming
- Exercises implemented with Python and Numba CUDA kernels
- Hands-on approach to understanding parallel computation
- Notebook format designed for execution in Google Colab
- Progressive challenges covering key GPU programming concepts
- Educational environment for learning algorithms used in deep learning