Grant: Discovery Grants Program - Individual

The state of the art in high performance computing (HPC) has been advancing rapidly with modern clusters having thousands if not tens of thousands of processors. The large number of processors and the corresponding large amount of main memory allows researchers to run very large models over a large number of time steps potentially producing many exabytes of data. This large data volume causes problems for traditional approaches to scientific visualization where the data is collected on disk during the computation and then transferred to a visualization workstation for post processing. The process of writing the data is now consuming a significant amount of HPC resources and due to the size of the data transferring it over existing computer networks to a visualization workstation is no longer feasible. The Mercury system supports the visualization of very large models by performing at least part of the visualization computations on the same cluster as the scientific computation. This approach to visualization is called in situ visualization and until recently has not received much attention in the research community, but with increased data set size it has now become an important research topic. This project investigates software architectures and tools for in situ visualization and how existing visualization techniques can be transferred to this new environment. The Mercury system is one of the first general purpose in situ visualization systems and will form the basis for many of these studies. The software and techniques produced in this research program will improve both the quality and efficiency of the visualization systems used by scientists and engineers.