Data-centric HPC Accelerates Statistical Inference and Machine Learning

San Jose, CA — The University of Michigan (U-M) announced it has selected IBM to develop and deliver “data-centric” supercomputing systems designed to increase the pace of scientific discovery in fields as diverse as aircraft and rocket engine design, cardiovascular disease treatment, materials physics, climate modeling and cosmology. Traditionally, scientific computations have been performed on high performance computing (HPC) infrastructure while modern data parallel architectures have mostly focused on web analytics and business intelligence applications. Systems that enable HPC applications for physics to interact in real time with big data to improve quantitative predictability have not yet been developed. IBM’s systems use a data-centric approach, integrating massive datasets seamlessly with HPC computing power resulting in new predictive simulation techniques that will expand the limits of scientific knowledge. Working with IBM,…


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