Scalable Analysis Methods and In Situ Infrastructure for Extreme Scale Knowledge Discovery

This project is tackling a set of R&D research problems to produce in situ software technology and tools that will help DOE computational science projects perform accurate and timely data analysis without the need to first write data to disk for subsequent analysis. We combine software technology R&D activities with close partnerships with key DOE computational science projects so that our priorities are guided by the most pressing scientific problems and so that the results of our work are put into production use by DOE science projects on DOE high-performance computational (HPC) platforms.

The benefit to DOE science projects is the ability to perform accurate data analysis, using all available data, rather than one or fewer of every 100,000 data values. Overall, this approach will help to greatly improve the quality of science in terms of accuracy, as well as to significantly reduce the amount of time required for the data analysis activities that are a critical part of all scientific endeavors.