👉 Cycling computing, also known as distributed or parallel computing, is a method of processing data by dividing tasks among multiple interconnected computers or processors working in a coordinated manner. This approach leverages the collective power of many machines to handle complex computations more efficiently than a single, powerful computer could manage alone. Each processor in the network performs its own part of the task, and the results are then combined to produce the final output. This technique is particularly useful for tasks that require massive computational resources, such as scientific simulations, big data analysis, and machine learning. By distributing the workload, cycling computing not only accelerates processing times but also enhances fault tolerance and scalability, allowing for the handling of larger datasets and more intricate problems than would be feasible with traditional computing methods.
