Asynchronous parallel algorithm for mining association rules on a shared-memory multi-processors
David Wing-Shing Cheung, Kan Hu, Shaowei Xia · 1998
Mining association rules from large databases is an important problem in data mining.There is a need to develop parallel algorithm for this problem because it is a very costly computation process.However, all proposed parallel algorithms for mining association rules follow the conventional level-wise approach.On a sharedmemory multi-processors, they will impose a synchronization in every iteration which degrades greatly their performance.The deficiency comes from the contention on the shared I/O channel when all processors are accessing their database partitions in the shared storage synchronously.An asynchronous algorithm APM has been proposed for mining association rules on shared-memory multiprocessors.All participating processors in APM generate candidates and count their supports independently without synchronization.Furthermore, it can finish the computation with less I/O than required in the level-wise approach.The algorithm has been implemented on a Sun Enterprise 4000 multi-processors with 12 nodes.The experiments show that APM has super performance than other proposed synchronous algorithms.