SIAM-CSE19-MS2-Coutinho.pdf

CSE simulations in high-performance computers are still costly. They often involve the selection of many computational parameters and options. The set-up of such parameters is usually a trial-and-error process even for experienced users. In this talk, we will show how to extend in-situ visualization techniques with in-transit data analysis to provide information to help control the simulations at runtime. Often, by only observing a region of interest, an experienced analyst can infer that something is not going well, deciding to stop it or change parameters. However, to do that, visual information should be complemented with information regarding the evolution of quantities of interest. We use for the simulations the libMesh library, which provides a platform for parallel, adaptive, multiphysics finite element computations. We discuss the integration of libMesh with in-situ visualization and in-transit data analysis tools. We present a parallel performance analysis showing that the overhead for both in-situ visualization and in-transit data analysis is negligible. Our tools enable monitoring the quantities of interest at runtime and steer the simulation based on the solver convergence or other data and visual information. The data analysis tool registers the provenance of the simulation data for reproducibility, including registering the runtime changes on simulation parameters.