DescriptionA key trend facing extreme-scale computational science is the widening gap between computational and I/O rates, and the challenge that follows is how to best gain insight from simulation data when it is increasingly impractical to save it to persistent storage for subsequent visualization and analysis. One approach to this challenge is centered around the idea of in situ processing, where visualization and analysis processing is performed while data is still resident in memory.
The SENSEI community in situ data interface is an API that promotes code portability and reusability. From the simulation view, a developer can instrument their code with the SENSEI API and then make make use of any number of in situ infrastructures. From the methods view, a developer can write an in situ method using the SENSEI API, then expect it to run in any number of in situ infrastructures.
This tutorial presents the fundamentals of in situ data analysis and visualization leveraging this generic interface. Attendees will learn the basics of in situ analysis and visualization while being exposed to advanced analysis such as time-dependent autocorrelation and interactive monitoring and steering. We demonstrate the infrastructure coupling using ADIOS, ParaView Catalyst, GLEAN and VisIt Libsim.