Interactive Data Mining on a CBEA Cluster

摘要

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, preprocessing 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.