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VLDB
2007
ACM

Optimization of Frequent Itemset Mining on Multiple-Core Processor

9 years 3 months ago
Optimization of Frequent Itemset Mining on Multiple-Core Processor
Multi-core processors are proliferated across different domains in recent years. In this paper, we study the performance of frequent pattern mining on a modern multi-core machine. A detailed study shows that, even with the best implementation, current FP-tree based algorithms still under-utilize a multi-core system due to poor data locality and insufficient parallelism expression. We propose two techniques: a cache-conscious FP-array (frequent pattern array) and a lock-free dataset tiling parallelization mechanism to address this problem. The FP-array efficiently improves the data locality performance, and makes use of the benefits from hardware and software prefetching. The result yields an overall 4.0 speedup compared with the state-of-the-art implementation. Furthermore, to unlock the power of multi-core processor, a lockfree parallelization approach is proposed to restructure the FP-tree building algorithm. It not only eliminates the locks in building a single FP-tree with fine-gr...
Eric Li, Li Liu
Added 09 Jun 2010
Updated 09 Jun 2010
Type Conference
Year 2007
Where VLDB
Authors Eric Li, Li Liu
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