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(Nov 8) Scientific Computing at the Edge: Sensors, Learning, and Adaptation


Scientific Computing at the Edge: Sensors, Learning, and Adaptation


2018.11.08 (Thu) 13:30-


Dr. Daniel Reed, Provost, Univ. of Utah, USA


Wooribyul Seminar Room (B/D E3-2, #2201)


Big data and deep learning are the memes of the day, as we shift from a world where data was rare, precious, and expensive to one where it is ubiquitous, commonplace, and inexpensive. Massive digital data (from scientific instruments and IoT devices), powerful multilayer classification networks, and inexpensive hardware accelerators are bringing new data-driven approaches, challenging some long held beliefs and illuminating old questions in new ways.  Like any new tool or technology, big data challenges and reshapes both our social and technical expectations. Likewise, the end of semiconductor Dennard scaling poses new technology challenges in designing ever-faster computing systems. This talk will examine the challenges of continuum computing, fusing edge sensors and machine learning with exascale computing and big data analytics, when computations must increasingly respond to real-time events. As an example, consider the research and scholarship questions that might be explored via powerful analytics applied to data streaming from thousands of sensors placed on human structures (buildings, public utility poles, automobiles) and the environment (air, water, soil, …).


Daniel A. Reed is the Senior Vice President for Academic Affairs (Provost) at the University of Utah. Previously, he was Vice President for Research and Economic Development at the University of Iowa, as well as Professor of Computer Science, Electrical and Computer Engineering, and Medicine. He has also served as Microsoft’s Corporate Vice President for Technology Policy and Extreme Computing, and he was the founding director of the Renaissance Computing Institute (RENCI), a multidisciplinary institute that spanned the University of North Carolina at Chapel Hill, North Carolina State University, and Duke University, where he held the Chancellor’s Eminent Professorship. At the University of Illinois, he was Head of Computer Science, holder of the Edward and Jane Marr Gutgsell chair, Director of the National Center for Supercomputing Applications, and chief architect for the NSF TeraGrid. Dr. Reed has served as a member of the U.S. President’s Council of Advisors on Science and Technology (PCAST), the President’s Information Technology Advisory Committee (PITAC). He currently chairs the Department of Energy’s Advanced Scientific Computing Advisory Committee (ASCAC), serves on Argonne National Laboratory’s Scientific Advisory Committee, and is a member of the National Center for Optical-Infrared Astronomy Oversight Committee (NMOC), and chairs the National Academies computational science review panel for the Army Research Laboratory. Dr. Reed is a Fellow of the ACM, the IEEE and the AAAS. He received his Ph.D. from Purdue University.