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arXiv · 1510.07787

Redesigning pattern mining algorithms for supercomputers

Kazuki Yoshizoe·Aika Terada·Koji Tsuda
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Abstract

Upcoming many core processors are expected to employ a distributed memory architecture similar to currently available supercomputers, but parallel pattern mining algorithms amenable to the architecture are not comprehensively studied. We present a novel closed pattern mining algorithm with a well-engineered communication protocol, and generalize it to find statistically significant patterns from personal genome data. For distributing communication evenly, it employs global load balancing with multiple stacks distributed on a set of cores organized as a hypercube with random edges. Our algorithm achieved up to 1175-fold speedup by using 1200 cores for solving a problem with 11,914 items and 697 transactions, while the naive approach of separating the search space failed completely.

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Kazuki Yoshizoe, Aika Terada, Koji Tsuda. 2015-10-27. Redesigning pattern mining algorithms for supercomputers. https://arxiv.org/abs/1510.07787

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