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Speaker: Valerio Pascucci; Director, Center for Extreme Data Management Analysis and Visualization (CEDMAV)

Title: Extreme Data Management Analysis and Visualization for Exascale Supercomputers and Experimental Facilities

Effective use of data management techniques for analysis and visualization of massive scientific data is a crucial ingredient for the success of any supercomputing center and cyberinfrastructure for data-intensive scientific investigation. In the progress towards exascale computing, the data movement challenges have fostered innovation leading to complex streaming workflows that take advantage of any data processing opportunity arising while the data is in motion.
In this talk, I will present a number of techniques developed at the Center for Extreme Data Management Analysis and Visualization (CEDMAV) that allow building a scalable data movement infrastructure for fast I/O while organizing the data in a way that makes it immediately accessible for analytics and visualization. Also, I will present an advanced in-situ data analytics framework that allows processing data on parallel supercomputers without requiring advanced user knowledge of parallel computing or advanced runtime systems. In particular, the data analytics include a topological framework that achieve massive data reductions while maintaining the ability to explore the full parameter space for feature selection in addition to enabling intuitive exploration of high dimensional spaces.

Overall, this leads to a flexible data streaming workflow that allows working with massive simulation models or data from high-resolution experimental facilities without compromising the interactive nature of the exploratory process that is characteristic of the most effective data analytics and visualization environment.

Valerio Pascucci is the Inaugural John R. Parks Endowed Chair of the University of Utah and the founding Director of the Center for Extreme Data Management Analysis and Visualization (CEDMAV) of the University of Utah. Valerio is also a Faculty of the Scientific Computing and Imaging Institute, a Professor of the School of Computing, University of Utah, and a Laboratory Fellow, of PNNL and a visiting professor in KAUST. Before joining the University of Utah, Valerio was the Data Analysis Group Leader of the Center for Applied Scientific Computing at Lawrence Livermore National Laboratory, and an Adjunct Professor of Computer Science at the University of California Davis. Valerio's research interests include Big Data management and analytics, progressive multi-resolution techniques in scientific visualization, discrete topology, geometric compression, computer graphics, computational geometry, geometric programming, and solid modeling. Valerio is the coauthor of more than two hundred refereed journal and conference papers and is an Associate Editor of the IEEE Transactions on Visualization and Computer Graphics.