Addressing the petascale data challenge using in-situ analytics

Data management, processing and analysis costs are quickly dominating computational and data-enabled sciences, and are limiting the potential impacts of advanced simulations running at extreme scales on the high-end computing systems. This presentation explores how in-situ data analytics and in-transit data transformation and data manipulation can be used to address these data challenges at petascale and beyond. Specifically, this presentations describes solutions developed as part of the Rutgers Spaces Project and deployed within the ADIOS framework.