Scalable Analysis Methods and In Situ Infrastructure for Extreme Scale (SENSEI)

Project Status: Active

The Sensei project is led by Wes Bethel from Lawrence Berkeley National Laboratory and involves participants from multiple laboratories and industries.  This project takes aim at a set of research challenges in enabling scientific knowledge discovery within the context of in situ processing at extreme-scale concurrency.  The work is motivated by a widening gap between Floating Point Operations Per Second  and Input/Output (I/O) capacity, a fact on current petascale and future exascale machines, which will make full-resolution I/O intensive posthoc analysis prohibitively expensive, if not impossible.  Specifically, there will be focus on new algorithms for analysis, and visualization-topological, geometric, flow field analysis, pattern detection and match suitable for use in an in situ context aimed specifically at enabling scientific knowledge discovery in several exemplar application areas of interest to the Department of Energy (DOE). 

The main project site is at

Last Updated: September 3, 2020 - 3:10 pm