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Computational Science Challenges In Extreme Scale CFD / Kenneth Jansen

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ABSTRACT: Parallel, adaptive, implicit computational fluid dynamics solvers have recently been shown to scale to the full machine at several of the largest computer facilities (e.g., 92 billion unstructured finite elements on over 3 million processes). To accomplish this, a number of computational science challenges were overcome including; load balancing, parallel I/O and implicit equation solution. These challenges and new ones such as extreme scale data analytics will be discussed within the context of real-world applications stemming from aerodynamic flow control.

BIO: Kenneth Jansen joined the faculty of Aerospace Engineering Sciences in January 2010 after 13.5 years at Rensselaer Polytechnic Institute, where he held appointments in Mechanical, Aerospace and Nuclear Engineering (home) and Computer Science (joint). Prior to this, he was a post-doctoral fellow at the Center for Turbulence Research (NASA/Stanford University). He received his Ph.D. in Mechanical Engineering, Division of Applied Mechanics, from Stanford University in 1993. His research balances the computational science challenges with the physical modeling challenges of massively parallel/adaptive computational fluid dynamics and has been funded by NSF (CISE), DOE (SciDAC), DOD and several companies. Applications span diverse fields of aerodynamics, cardiovascular flow and multiphase flow.
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