Abstract: It is well known that as high-performance computing applications have grown, I/O has become a bottleneck, which has required scientists to turn to in situ tools for data exploration. The focus of this exploration has typically been on simulation data. However, applications also produce ephemeral data that is optionally written to disk for post hoc analysis, but not otherwise saved or used by the application in subsequent time steps. An example of ephemeral data is run-time performance data.

In this talk I will present the infrastructure implemented for efficiently collecting this and other data within the Uintah framework, which has been coupled to VisIt’s in situ toolkit for analysis and visualization. This collection and coupling allows performance data to be visualized by using a ​“simulation viewpoint” and ​“machine viewpoint,” giving insight previously not possible. As part this coupling, we take advantage of VisIt’s custom user interface to create a ​“simulation dashboard” that allows for in situ computational steering and visual debugging allowing for improvements in the development and simulation workflow.

Bio: Allen Sanderson, Ph.D., is a research scientist at the University of Utah’s Scientific Computing and Imaging Institute. His interest lies in visualization and analysis of large data coming from application areas ranging from plasma physics to combustion. Recently, he has focused on new ways to use in situ data analysis and visualization, which often has him working directly on the science application infrastructure.