👉 Cop computing, or cooperative parallel computing, is a paradigm where multiple processors or computing nodes work together to solve a single problem, often by dividing the computational workload into smaller tasks that can be executed concurrently. This approach enhances efficiency, reduces execution time, and allows for better utilization of resources, especially in large-scale data processing or complex simulations. In cop computing, communication and synchronization between nodes are crucial to ensure that the tasks are coordinated effectively, and results are integrated accurately. This model is particularly useful in scenarios like big data analytics, machine learning, and scientific simulations where tasks can be naturally partitioned and executed in parallel.
