Intuitive Computational Steering Using Ascent and Trame

Large-scale scientific simulations that run on high-performance computing resources are typically executed in batch mode, where jobs are queued and run once sufficient resources become available. Visualization and analysis of simulation data can be performed post hoc or in situ, but in both cases, scientists typically do not gain insights until after the simulation has completed. Recently, bidirectional steering capabilities integrated into in situ libraries have enabled scientists to investigate and control simulations during runtime. In this paper, we present our work on developing a bridge between Ascent (a flyweight in situ processing and visualization library) and Trame (a web-based framework for developing interactive visualizations) to create a means for domain users to intuitively steer large-scale simulations. We demonstrate the effectiveness of web-based, user-friendly, customizable steering through three real-world use cases involving large-scale production simulations.