Software Tools For Large Scale Interactive Hydrodynamic Modeling

Abstract

Developing easy-to-use software that combines components for simultaneous visualization, simulation and interaction is a great challenge. Mainly, because it involves a number of disciplines, like computational fluid dynamics, computer graphics, high-performance computing. One of the main characteristics of an interactive model is that it should provide immediate feedback to the user, for example respond to changes in model state or view settings. Features involving interaction during simulation are usually available for models with a relatively small number of computational cells and are used mainly for demonstration and educational purposes. The reason for that is that the time required to compute a single time step and render model results become significant when comparing to a simple model. It would be useful if interactive modeling would also work for models typically used in consultancy projects involving large scale simulations. This results in a number of technical challenges related to the combination of the model itself and the visualization tools (scalability, implementation of an appropriate API for control and access to the internal state). While model parallelization is increasingly addressed by the environmental modeling community, little effort has been spent on developing a highperformance interactive environment. What can we learn from the other domains where visualizations plays crucial role, such as 3D animation, gaming, virtual globes (Autodesk 3ds Max, Google Earth) that also focus on efficient interaction with 3D environments? In these domains high efficiency is usually achieved by the use of computer graphics algorithms such as surface simplification depending on current view, distance to objects, and efficient caching of the aggregated representation of object meshes. We investigate how these algorithms can be re-used in the context of interactive hydrodynamic modeling without significant changes to the model code and allowing model operation on both multi-core CPU personal computers and high-performance computer clusters.