Scalability and Flexibility Imparted by the Parallel Processing Models for Computing HCF and LCM of Large Volume of Numeric Data

Software Parallelism imparts scalability and flexibility for proposing solution models of computational problems. For achieving the same, problems shall be suitable to be split recursively into several easily manageable sub problems and their solutions prepared by several computers are to be merged together to get the ultimate solutions. Software Parallelism plays a major role when the volume of data to get processed is large. HCF and LCM are frequently used in large volumes for solving a wide variety of real world problems ranging from simplification of fractional values as well as contribution based profit sharing up to complex solution models in cryptography and cryptanalysis. This is a study on the scalability and flexibility imparted by the parallel processing model for computing HCF and LCM with the examples from puzzles involving divisibility by several numbers.