Steering smog prediction

The use of computational steering for smog prediction is described. This application is representative for many underlying issues found in steering high performance applications: high computing times, large data sets, and many different input parameters. After a short description of the smog prediction model, its visualization and steering are described. The amount of computation needed to solve the governing transport equations is alarmingly high. The user has a large number of options for the display of various aspects of the simulation, and also for the interactive control of its input data. Smooth animation is very important to monitor the evolution of pollutants and for a responsive feedback to parameter changes. Here a performance of least 15 frames per second is required. We discuss techniques that allow the user to steer the numerical solver, such that an optimal tradeoff between computation speed and accuracy can be made

CSE: a modular architecture for computational steering

Computational steering is the ultimate goal of interactive simulation. Steering enables users to supervise and dynamically control the computation of an ongoing simulation. We describe CSE: a modular architecture for a computational steering environment. The kernel of the architecture is designed to be very simple, flexible and minimalistic. All higher level system functionality is pushed into modular components outside of the kernel, resulting in a rich and powerful environment. For these modular components (called satellites) a uniform user interface metaphor for users, based on a tray of cards, has been used. The card tray metaphor is very simple to understand and provides users with a simple mechanism to organize and retrieve the tools. Several applications of the environment are shown

Computational steering

The traditional cycle in simulation is to prepare input, execute a simulation, and to visualize the results as a post-processing step. However, more insight and a higher productivity can be achieved if these activities are done simultaneously. This is the underlying idea of Computational Steering: researchers change parameters of their simulation on the fly and immediately receive feedback on the effect. In this paper the Computational Steering Environment, CSE, developed at CWI is described. We discuss the requirements of computational steering environment, its relation with high performance computing and networking, and show an application of its use

Bringing computational steering to the user

Computational steering is a technique that combines simulation and visualization. The user is continuously provided with visual feedback about the state of the simulation, and can change parameters on the fly. Designers can vary parameters to optimize their product, users can detect errors in the input early, researchers can do qualitative sensitivity analyses easily. The implementation of computational steering is very tedious. It requires knowledge of the simulation, visualization, user interfacing, and data communication. In this paper we discuss an environment that enables users to implement and use computational steering effectively without much support from user interface experts. We show how the environment is applied to various applications

Computational steering in the CAVE

Scientists can gain much more insight from their simulations if they are enabled to change simulation parameters on the fly while observing the results immediately. A crucial aspect of such {em computational steering/ is an intuitive user interface. We have developed an environment that enables researchers to construct such interfaces efficiently and effectively for graphical workstations. In this paper we report on our next step towards more intuitive user-interfaces: We have modified our system for use in the CAVE. The CAVE is a projection-based virtual environment. Virtual environments are designed to provide the effect of immersion in an interactive three-dimensional computer-generated environment. We show that the use of virtual environments for computational steering interfaces can improve interaction with the simulation and immersion in the computational process. We present our system, the methods we have developed for improved 3D interaction, and describe three applications