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This paper reports the research on using GPUs as accelerators for Business Intelligence(BI) analytics. The paper is particularly interested in analytics on very large data sets, which are common in today's real world BI applications. While many published works have shown that GPUs can be used to accelerate various general purpose applications with respectable performance gains, few attempts have been made to tackle very large problems. The goal here is to investigate if the GPUs can be useful accelerators for BI analytics with very large data sets that cannot fit into GPU's onboard memory. Using a popular clustering algorithm, K-Means, as an example, the results have been very positive.
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