Due to the exponential growth of data, today there is an ever increasing need to process and analyze big data. The huge size of the available data and their high-heterogeneity and high-dimensionality make large-scale data mining applications computationally very demanding. Moreover, the quality of the data mining results often depends directly on the amount of computing resources available. In fact, data mining applications are poised to become the dominant consumers of supercomputing in the near future. There is a necessity to develop e?ective parallel algorithms for various data mining techniques. However, designing such algorithms is challenging. In this sub-topic, we try to develop and experiment data mining algorithms that are able to benefit from the capabilities of HPC infrastructures.
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