Parallel processing in epidemiology typically involves dividing a large computational task into smaller, independent tasks that can be executed concurrently. This can be achieved through various methods, including:
Data Parallelism: Distributing subsets of the data across multiple processors to perform the same operation on each subset. Task Parallelism: Different processors perform different tasks on the same or different data sets.
These methods are implemented using specialized software and hardware designed for high-performance computing.
