Artificial Intelligence (AI) applications require massive computational power to handle complex mathematical operations like matrix multiplications, deep learning model training, and inference. Over the last decade, three major hardware architectures have become central to AI workloads: Field-Programmable Gate Arrays (FPGAs), Graphics Processing Units (GPUs), and Tensor Processing Units (TPUs). Each of these platforms offers distinct advantages and trade-offs in terms of speed, flexibility, … [Read more...]