PHUI-GA: GPU-Based Efficiency Evolutionary Algorithm for Mining High Utility Itemsets

Abstract

Evolutionary algorithms (EAs) have been used in high utility itemset mining (HUIM) to address the problem of discovering high utility itemsets (HUIs) in the exponential search space. EAs have good running and mining performance, but they still require huge computational resource and may miss many HUIs. Due to the good combination of EA and graphics processing unit (GPU), we propose a parallel genetic algorithm (GA) based on the platform of GPU for mining HUIM (PHUI-GA). The evolution steps with improvements are performed in central processing unit (CPU) and the CPU intensive steps are sent to GPU to evaluate with multi-threaded processors. Experiments show that the mining performance of PHUI-GA outperforms the existing EAs. When mining 90% HUIs, the PHUI-GA is up to 188 times better than the existing EAs and up to 36 times better than the CPU parallel approach.