Whitlock, BradFavre, Jean M.Meredith, Jeremy S.Torsten Kuhlen and Renato Pajarola and Kun Zhou2014-01-262014-01-262011978-3-905674-32-31727-348Xhttps://doi.org/10.2312/EGPGV/EGPGV11/101-109There is a widening gap between compute performance and the ability to store computation results. Complex scientific codes are the most affected since they must save massive files containing meshes and fields for offline analysis. Time and storage costs instead dictate that data analysis and visualization be combined with the simulations themselves, being done in situ so data are transformed to a manageable size before they are stored. Earlier approaches to in situ processing involved combining specific visualization algorithms into the simulation code, limiting flexibility. We introduce a new library which instead allows a fully-featured visualization tool, VisIt, to request data as needed from the simulation and apply visualization algorithms in situ with minimal modification to the application code.Categories and Subject Descriptors (according to ACM CCS): I.3.1 [Computer Graphics]: Hardware Architecture- Parallel processing I.3.4 [Computer Graphics]: Graphics Utilities-Application packages