Graduate Seminar March 4th with John Tencer
Abstract: The last few years have seen an explosion in surrogate modeling methodologies for scientific computing. However, many issues remain when attempting to utilize these tools at scale for real-world applications. Our research group at Sandia National Laboratories is interested in deploying these technologies across the various laboratory mission areas and tackling the challenges that arise, particularly at the interfaces between surrogate models and legacy tooling. In order to achieve their promised impact, these surrogates must be made to fit within an established framework with legacy software codes. This is largely accomplished by creating surrogates which augment, leverage, or replicate legacy code. In this talk, I’ll overview work at Sandia National Laboratories utilizing each of these approaches to surrogate modeling. I’ll focus especially on the Pressio project for enabling minimally intrusive projection-based ROMs and the API we’ve developed for interfacing with a diverse suite of high-performance computing applications.
Bio: John Tencer is a Principal Member of Technical Staff at Sandia National Laboratories (SNL) in Albuquerque, New Mexico. His research interests are in the areas of thermal and computational sciences with particular interest in thermal radiation, reduced-order modeling, machine learning, and uncertainty quantification. Dr. Tencer received his B.S. in Mechanical Engineering from the University of Tennessee, Knoxville in 2009. He then received M.S. and Ph.D. degrees in Mechanical Engineering from the University of Texas at Austin in 2011 and 2013. He joined the Thermal Sciences and Engineering Department at Sandia National Laboratories in 2013. He chairs the computational heat transfer technical committee for ASME.