Parallel Association Rule Algorithm using Hybrid Parallel Computing

with massive amount of data continuously being collected and stored, many industries are becoming interested in mining such patterns from their databases. The discovery of interesting correlation relationship among huge amount of business transactions records can help in many business decision-making process. Simply adding more processors will not magically improve the performance of the vast majority of serial programs. Clearly, parallel computing can have an enormous impact on application performance, and OpenMP and MPI facilitates aces to this enhanced performance. Having them work in a hybrid model, will result in a better efficiency supporting each other. As an example this paper is intended to provide an insight of hybrid parallel implementation for mining an association rule called Apriori.