Online Monitoring and Computational Steering of Massive Parallel CFD Simulations

Abstract

Due to tremendous improvements of high-performance computing resources as well as numerical advances computational simulations became a common tool for modern engineers. Nowadays, simulation of complex physics is more and more substituting a large amount of physical experiments. While the vast compute power of large-scale high-performance systems enabled for simulating more complex numerical equations, handling the ever increasing amount of data with spatial and temporal resolution burdens new challenges to scientists. Huge hardware and energy costs desire for effcient utilization of high-performance systems. However, increasing complexity of simulations raises the risk of failing simulations resulting in a single simulation to be restarted multiple times. Computational Steering is a promising approach to interact with running simulations which could prevent simulation crashes. The large amount of data expands gaps in the amount of data that can be calculated and the amount of data that can be processed. Extreme-scale simulations produce more data that can even be stored. In this thesis, I propose several methods that enhance the process of steering, exploring, visualizing, and analyzing ongoing numerical simulations.