👉 Targeted computing, also known as focused or precision computing, is a computational paradigm designed to optimize the use of computational resources by focusing on specific tasks or subsets of data, rather than processing all available data uniformly. This approach aims to reduce energy consumption, minimize waste, and enhance performance by tailoring algorithms and hardware operations to the precise requirements of the task at hand. By concentrating computational efforts on relevant data or problem domains, targeted computing can achieve higher efficiency and effectiveness, particularly in scenarios involving large datasets or complex computations, such as machine learning models or scientific simulations. This method leverages techniques like data pruning, model quantization, and specialized hardware accelerators to ensure that only necessary computations are performed, thus optimizing the overall system performance.
