👉 Parallel Computing, or P Computing, is a computational paradigm that involves dividing a problem into smaller, independent tasks that can be executed simultaneously across multiple processors or computing nodes. This approach leverages the power of parallelism to significantly accelerate computation, making it particularly effective for handling large datasets and complex simulations. By distributing the workload, P Computing can reduce execution time and improve efficiency, often outperforming sequential computing methods. It is widely used in fields such as scientific research, data analytics, machine learning, and high-performance computing, where tasks can be naturally decomposed into parallelizable components.
