Electronic poster: co-visualization of full data and in situ data extracts from unstructured grid cfd at 160k cores

Scalability and time-to-solution studies have historically been focused on the size of the problem and run time. We consider a more strict definition of "solution" whereby a live data analysis (co-visualization of either the full data or in situ data extracts) provides continuous and reconfigurable insight into massively parallel simulations. Specifically, we used the Argonne Leadership Class Facility's (ALCF) BlueGene/P machine with 163,840 cores tightly linked through a high-speed network to 100 visualization nodes that share 800 cores and 200 GPUs. Three meshes with respectively 52M, 416M and 3.3B elements discretize the flow over a full swept wing with an unsteady synthetic jet to evaluate time-to-solution plus insight. On the full machine, the 416M element mesh takes about 2 seconds per flow solve step including the extraction and rendering of a slice or a contour, slowing currently the simulation by only 10 and 15% respectively. The 3.3B element case proved scalable at about 15 seconds per time step, whereas PHASTA's strong scaling could compress the time-to-solution for the 52M element case enough to allow the rendering of one frame (slice or contour) every 0.7 second, paving the way for interactive simulation and simulation steering on massively parallel systems1.