Top 10 Data Analytics Problems in Science, Prabhat
Lawrence Berkeley National Lab and NERSC are at the frontier of scientific research. Historically, NERSC has provided leadership computing for the computational science community, but we now find ourselves tackling Big Data problems from an array of observational and experimental sources. In this talk, I will review the landscape of Scientific Big Data problems at all scales, spanning astronomy, cosmology, climate, neuroscience, bioimaging, genomics, material science and subatomic physics. I will present a list of Top 10 Data Analytics problems from these domains, and highlight NERSCs current Data Analytics strategy and hardware/software resources. I will highlight opportunities for engaging with NERSC, Berkeley Lab and the scientific enterprise.
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