Time Step Prioritising in Parallel Feature Extraction on Unsteady Simulation Data

Abstract

Explorative analysis of unsteady computational fluid dynamics (CFD) simulations requires a fast extraction of flow features. For time-varying data, the extraction algorithm has to be executed for each time step in the period under observation. Even when parallelised on a remote high performance computer, the user s waiting time still exceeds interactivity criteria for large data sets. Moreover, computations are generally performed in a fixed order, not taking into account the importance of partial results for the user s investigation. In this paper we propose a general method to guide parallel feature extraction on unsteady data sets in order to assist the user during the explorative analysis even though interactive response times might not be available. By re-ordering of single time step computations, the order in which features are provided is arranged according to the user s exploration process. We describe three different concepts based on typical user behaviours. Using this approach, parallel extraction of unsteady features is enhanced for arbitrary extraction methods.