👉 "Little computing" refers to the practice of breaking down complex computational tasks into smaller, more manageable sub-tasks or "micro-programs" that can be executed independently or in parallel. This approach leverages the power of modern computing architectures, such as multicore processors and distributed systems, to enhance efficiency and performance. By dividing a problem into these smaller units, it allows for concurrent execution, reducing overall processing time and improving resource utilization. This method is particularly useful in scenarios where tasks can be decomposed into parallelizable components, such as data processing, machine learning, and real-time analytics. It also makes it easier to optimize individual parts of a system for specific tasks, leading to more efficient and scalable solutions.
