Abstract
We present implementations of two data-mining algorithms on a CELL processor, and on a low-cost CBEA (CELL Broadband Engine Architecture) cluster using multiple PlayStation3 consoles. Typical batch-processing environments are often unsuitable for interactive data-mining processes that require repeated adjustments to parameters, pre-processing steps, and data, while contemporary desktops do not offer sufficient resources for the large datasets available today. Our implementations for the k Nearest Neighbour algorithm and the Decision Tree scale linearly with the number of samples in the training data and the number of processors, and demonstrate runtimes of under a minute for up to 500 000 samples.
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McConnell, S., Patton, D., Hurley, R., Blight, W., Young, G. (2010). Interactive Data Mining on a CBEA Cluster. In: Mewhort, D.J.K., Cann, N.M., Slater, G.W., Naughton, T.J. (eds) High Performance Computing Systems and Applications. HPCS 2009. Lecture Notes in Computer Science, vol 5976. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12659-8_20
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DOI: https://doi.org/10.1007/978-3-642-12659-8_20
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