The article explores the workings of GPUs, focusing on key performance factors such as compute and memory hierarchy, performance regimes, and strategies for optimization. It highlights the imbalance between computational speed and memory bandwidth, using the NVIDIA A100 GPU as a case study, and discusses techniques like data fusion and tiling to enhance performance. Additionally, it addresses the importance of arithmetic intensity in determining whether operations are memory-bound or compute-bound.