ASSOCIATION RULE MINING WITH THE MICRON AUTOMATA PROCESSOR

摘要

The present invention discloses a heterogeneous computation framework, of Association. Rule Mining (ARM) using Micron's Autotmata Processor (AP). This framework is based on the Apriori algorithm. Two Automaton designs are proposed to match and count the individual itemset. Several performance improvement strategies are proposed including minimizing the number of reporting vectors and reduce reconfiguration delays. The experiment results show up to 94× speed ups of the proposed AP-accelerated Apriori on six synthetic and real-world datasets, when compared with the Apriori single-core CPU implementation. The proposed AP-accelerated Apriori solution also outperforms the state-of-the-art multicore and GPU implementations of Equivalence Class Transformation (Eclat) algorithm on big datasets.

主权项

1. A processor for discovering a pattern of frequently associated items in large datasets, the processor comprises functional elements comprising:
a plurality of state transition elements based on memory columns implemented in DRAM (Dynamic Random-Access Memory) memory technology; a plurality of counters; and a plurality of boolean elements,wherein the processor is capable of fast replacement of symbol sets of the plurality of state transition elements and threshold values of the plurality of counters,wherein the plurality of counters and the plurality of boolean elements are designed to work with the plurality of state transition elements to increase space efficiency of automata implementation, andwherein the pattern includes sets, continuous sequences, and discontinuous sequences in the large datasets.