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jackie chen

Tuesday, October 3, 2017
10:50 AM – 12:00 PM
Phoenix Convention Center

Jacqueline H. Chen
is a Distinguished Member of Technical Staff at the Combustion Research Facility at Sandia National Laboratories. She has contributed broadly to research in petascale direct numerical simulations (DNS) of turbulent combustion focusing on fundamental turbulence-chemistry interactions. These benchmark simulations provide fundamental insight into combustion processes and are used by the combustion modeling community to develop and validate turbulent combustion models for engineering CFD simulations. In collaboration with computer scientists and applied mathematicians she was the founding Director of the Center for Exascale Simulation of Combustion in Turbulence (ExaCT). She led an interdisciplinary team to co-design DNS algorithms, domain-specific programming environments, scientific data management and in situ uncertainty quantification and analytics, and architectural simulation and modeling with combustion proxy applications. She is also the PI of a DOE Exascale Simulation Project on Combustion. She received the DOE INCITE Award in 2005-2017, the DOE ALCC Award in 2012, and the 34th International Combustion Symposium Distinguished Paper Award 2012. She is a member of the DOE Advanced Scientific Computing Research Advisory Committee (ASCAC) and Subcommittees on Exascale Computing, and Big Data and Exascale. She was the editor of Flow, Turbulence and Combustion, the co-editor of the Proceedings of the Combustion Institute, volumes 29 and 30, the Co-Chair of the Local Organizing Committee for the 35th Intl Combustion Symposium, and a member of the Board of Directors of the Combustion Institute.

Analytics Inspired Visualization: a Holistic In-situ Scientific Workflow at Extreme Scale
Combustion and turbulence simulations involve highly intermittent localized phenomena that generate high volumes of spatially and temporally varying field and particle data. The current paradigm of posthoc analysis and visualization will become increasingly infeasible as data volumes continue to increase. In the exascale era this problem will be further exacerbated by the difficulty of moving large volumes of data through deep complex memory hierarchies and across the machine network to hard disks on a heterogeneous supercomputer. I will discuss recent advances in in situ massively parallel volume and particle visualization algorithms coupled with analytics – e.g. topological feature segmentation/tracking, distance field construction, multi-variate statistics and eigensolutions of the reaction rate Jacobian - as an integral part of a scientific discovery from high-fidelity combustion simulations. The role of asynchronous task based programming models and runtimes to facilitate an extensible, performance portable computational science workflow at extreme scale will also be discussed in the context of recent turbulent ignition simulations.