GPU Puzzles (2021) (github.com)

A new interactive notebook titled "GPU Puzzles" has been launched to enhance the understanding of GPU programming for beginners in the AI/ML community. This resource provides a hands-on approach to learning GPU kernel coding using NUMBA, which bridges Python code to CUDA—essential for creating efficient machine learning algorithms. Users can immediately dive into coding exercises that challenge them to build kernels for tasks such as adding elements in arrays and implementing convolution operations, while also gaining insight into the underlying algorithms that power most deep learning frameworks. This initiative is significant because it addresses a gap in GPU programming education, allowing individuals, especially those new to the field, to grasp complex concepts without getting overwhelmed by theoretical content. By leveraging platforms like Google Colab, the notebook makes it easy for users to experiment with GPUs, fostering a deeper understanding of parallel computation and memory management—crucial skills in AI development. As more machine learning applications require efficient processing, this resource could help cultivate a new generation of developers well-versed in GPU programming and its applications in AI.