Parallel mining of frequent closed patterns: harnessing modern computer architectures

Inspired by emerging multi-core computer architectures, in this paper we present MT CL O S E D, a multi-threaded algorithm for frequent closed itemset mining (FCIM). To the best of our knowledge, this is the first FCIM parallel algorithm proposed so far. We studied how different duplicate checking techniques, typical of FCIM algorithms, may affect this parallelization. We showed that only one of them allows to decompose the global FCIM problem into independent tasks that can be executed in any order, and thus in parallel. Finally we show how MT CL O S E D efficiently harness modern CPUs. We designed and tested several parallelization paradigms by investigating static/dynamic decomposition and scheduling of tasks, thus showing its scalability w.r.t. to the number of CPUs. We analyzed the cache friendliness of the algorithm. Finally, we provided additional speed-up by introducing SIMD extensions.