The rapid growth in computing power has presented both opportunities and challenges for high-fidelity simulations of turbulent reacting flows. The advent of petascale supercomputers has made it possible to glean fundamental physical insight into fine-grained ‘turbulence-chemistry' interactions in canonical laboratory-scale turbulent flames with direct numerical simulations (DNS). The unique benchmark DNS data are also used to develop and validate predictive models used to design future fuel-efficient combustors utilizing alternative fuels for transportation and power generation. Such simulations are costly, requiring several million cpu-hours on a petascale computer, over a billion grid points, and generating 100's of terabytes of data. The turbulent combustion simulation enterprise involves collaborations with computer scientists in the performance monitoring and optimization of the software on petascale architectures, on automating workflow for providing runtime diagnostics, and in-situ feature detection/tracking/ visualization of time-varying multi-scale, multi-variate data. Aspects of these interdisciplinary collaborations will be described along with reactive flow examples that illustrate the science role of DNS. Outstanding challenges with extracting salient information from 100's of terabytes of data, and strategies for mapping DNS solvers to heterogeneous petascale architectures with accelerators will also be discussed.
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