Abstract The paper provides an overview of an experimental, Grid‐like computing environment, Polder, and its components. Polder offers high‐performance computing and interactive simulation facilities to computational science. It was successfully implemented on a wide‐area cluster system, the Distributed ASCI Supercomputer. An important issue is an efficient management of resources, in particular multi‐level scheduling and migration of tasks that use PVM or sockets. The system can be applied to interactive simulation, where a cluster is used for high‐performance computations, while a dedicated immersive interactive environment (CAVE) offers visualization and user interaction. Design considerations for the construction of dynamic exploration environments using such a system are discussed, in particular the use of intelligent agents for coordination. A case study of simulatedabdominal vascular reconstruction is subsequently presented: the results of computed tomography or magnetic resonance imaging of a patient are displayed in CAVE, and a surgeon can evaluate the possible treatments by performing the surgeries virtually and analysing the resulting blood flow which is simulated using the lattice‐Boltzmann method. Copyright © 2002 John Wiley & Sons, Ltd.

We present the CAVEStudy system that enables scientists to interactively steer a simulation from a virtual reality (VR) environment. No modification to the source code is necessary. CAVEStudy allows interactive and immersive analysis of a simulation running on a remote computer. Using a high-level description of the simulation, the system generates the communication layer (based on CAVERN-Soft) needed to control the execution and to gather data at runtime. We describe three case-studies implemented with CAVEStudy: soccer simulation, diode laser simulation and molecular dynamics.

We discuss the use of virtual reality (VR) techniques for interaction between humans and a multi-agent system in the context of RoboCup. The goal of RoboCup is to let teams of cooperating autonomous agents play a soccer match, using either robots or simulated players. We use RoboCup to study distributed collaborative applications, which allow multiple users at different geographic locations to cooperate, by interacting in real time through a shared simulation program. Our objective is to construct a VR environment in which humans at different locations can play along with a running RoboCup simulation in a natural way. The simulation system consists of the Soccer Server and a set of processes modeling the players. The server keeps track of the state of the game: provides the players with information on the game, and enforces the rules. The players request state information and autonomously calculate a behavior, sending the server commands that consist of accelerations, turns and kicks. The server discretizes time into slots, only one command is executed per time slot. We have developed a 3D visualization system that allows a user in a CAVE to interact with the soccer simulation software.

The anterior surface of the eye ('cornea') is extremely important for good sight. Instruments measuring corneal shape conventionally visualize the surface characteristics by mapping the instantaneous radius of curvature onto a rainbow colour scale. This technique is known to have important drawbacks. Firstly, not corneal shape itself is visualized, but rather second order surface properties. Secondly, the type of colouring produces well documented artifacts. We discuss visualization techniques for a more direct representation of the data. In a three part display, shape deviations are presented as a height surface in one window, height lines superimposed over the input image in another, and a colour mapped representation of the mean normal radius of curvature in a third. With the aid of some typical examples, it is shown that these visualizations are easy to interpret by the physician and overcome the limitations of the conventional techniques.

We present a system where visualization and the control of the simulation are integrated to facilitate interactive exploration and modeling of large data sets. The system was developed to estimate properties of the atmosphere of Venus from comparison between measured and simulated data. Reuse of results, distributed computing, and multiple views on the data were the major ingredients to create an effective environment.