Enabling in situ visualization of petascale time-dependent CFD simulations Scientific Achievement In situ visualization allowed researchers to have immediate visual representation of petascale simulation results. Significance and Impact In situ visualization increases the value of petascale simulations by making more data available to analyze and will be critical to capture enough data at the exascale. Research Details In situ visualization of simulation with hundreds of billions of degrees of freedom was demonstrated on Titan using 5000 GPUs. VTK-m enables scientific visualization algorithms to run accelerated processors alongside the simulation. Images and algorithm configured entirely by simulation witt multiple camera’s tracking different areas of interest. Notes: “The VTK-m based in situ vis technology we developed with Kitware and Nvidia represents an enabling technology for us. Quite simply there is no other way of imaging our extreme-scale time-dependent CFD simulations with hundreds of billions of degrees of freedom. Going forwards we hope it will help accelerate the insight extraction process across a wide range of application areas”. – Peter Vincent, Imperial College The VTK-m based in situ work leveraged the existing ParaView/Catalyst framework to allow for an efficient interconnection between the simulation ( PyFR ) and the visualization ( VTK-m / ParaView ). This connection, the simulation, and the visualization remained entirely on the GPU for maximum efficiency and highest performance. To aid the researchers in producing the most relevant images we designed a in situ pipeline that allowed for the simulation to dictate where to place any number of cameras, and what visualization algorithms should those cameras capture. The production run used multiple cameras tracking different areas of the simulation with each camera rotating through different visualization algorithms. Figure: Visualizing Flow over a Low Pressure Turbine Linear Cascade with PyFR, VTK-m, Paraview, and Catalyst. The image shows the iso-contour of the pressure gradient. Reference: P. Vincent, F. Witherden, B. Vermeire, J. Park, A. Iyer,” Towards Green Aviation with Python at Petascale”, Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis. (2016) DOI: 10.1109/SC.2016.1 Flow over a Low Pressure Turbine Linear Cascade simulation by PyFR, visualized with VTK-m, Paraview, and Catalyst P. Vincent, F. Witherden, B. Vermeire, J. Park, A. Iyer, Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis. DOI: 10.1109/SC.2016.1