Hardware Acceleration: GPUs, TPUs, and Beyond
Hardware Acceleration: GPUs, TPUs, and Beyond Hardware acceleration uses dedicated devices to run heavy tasks more efficiently than a plain CPU. GPUs excel at many simple operations in parallel, while TPUs focus on fast tensor math for neural networks. Other accelerators, such as FPGAs and ASICs, offer specialized strengths. Together, they speed up graphics, data processing, and AI workloads across clouds, desktops, and edge devices. Choosing the right tool means weighing what you need. GPUs are versatile and widely supported, with mature libraries for machine learning and high-performance computing. TPUs deliver strong tensor performance for large models in ideal cloud setups. Other accelerators can cut power use or speed narrow parts of a pipeline, but may require more development work. ...