I/O Post- and Co-Processing for High-Order Methods

While the exascale computing era is approaching, the growing gap between computing resources and IO bandwidth for massively parallel simulations has already become a major bottleneck for the scientific discovery process. In this context, various strategies to enable and accelerate the analysis of data produced by massively parallel high-order methods are presented, with an emphasis on in-situ visualization and co-processing techniques. First, a library of parallel procedures is presented for an efficient collection of turbulence statistics within the framework of a modal discontinuous Galerkin method. Afterwards, an acoustic co-processing strategy is presented whereby sound radiation calculations are performed concurrently with CFD calculations in order to avoid the need to store prohibitive amount of data. Finally, an open-source and scalable post-hoc visualization and processing tool dedicated to the analysis of large data sets produced by high order methods is first presented. This post-hoc processing tool has then been extended to a co-processing interface which enables live in-situ visualization and analysis of high-order solutions produced by massively parallel simulations.