ADSP is targeted at “big data” science problems that require the scale and performance of leadership computing resources.

Objective:  Explore and improve a variety of computational methods that will help enable data-driven discoveries across all scientific disciplines on leadership-class systems. ADSP projects are expected to cover a wide variety of application domains that span experimental and observational sciences. The projects will focus on data science techniques including but not limited to uncertainty quantification, statistics, machine learning, deep learning, databases, pattern recognition, image processing, graph analytics, data mining, real-time data analysis, and complex and interactive workflows.