👉 Strips computing is an innovative approach to computing that involves breaking down complex tasks into smaller, more manageable "strips" or components, each designed to perform specific functions. These strips can be physical, like specialized hardware modules, or virtual, such as software-defined units running on a common platform. By dividing a problem into these strips, systems can leverage parallel processing to enhance performance and efficiency, allowing for faster execution of tasks that would otherwise be computationally intensive. This modular approach also facilitates scalability and flexibility, as additional strips can be added or existing ones optimized to handle increased loads or new functionalities. Strips computing is particularly beneficial in scenarios requiring high computational power, such as machine learning, scientific simulations, and data-intensive applications, where it can significantly reduce processing times and improve overall system responsiveness.
