Title: "Divide & Recombine (D&R) with Tessera for Big and Complex Data: High Performance Computing for Deep Data Analysis (HPC-DDA)"
Speaker: William S. Cleveland; Department of Statistics, Purdue University

Place: BEERING 2280
Date: February 23, 2016; Tuesday
Time: 4:30pm


The widely used term "big data" carries with it a notion of computational performance for the analysis of big datasets. But for data analysis, computational performance depends very heavily, not just on size, but on the computational complexity of the analytic routines used in the analysis. Datasets that have big computational challenges have a very wide range of sizes. Furthermore, the hardware power available to the data analyst is also an important factor. High performance computing for data analysis can be provided for wide ranges of dataset size, computational complexity, and hardware power by the (D&R) statistical approach, and the Tessera D&R software implementation that makes programming D&R easy.

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