👉 Marilyn computing, also known as parallel computing, is a method of processing data where multiple processors or computing units work simultaneously on different parts of a problem, significantly speeding up computation times. This approach is particularly useful for tasks involving large datasets or complex calculations, such as simulations, data analysis, and machine learning. In Marilyn computing, a problem is divided into smaller sub-problems that can be solved independently by different processors, which then combine their results to form the final solution. This parallelism can dramatically reduce execution time compared to sequential computing, where each processor works on a single part of the problem at a time. Marilyn computing is widely used in fields like scientific research, engineering, and big data analytics to handle computationally intensive tasks more efficiently.
