Simulation Molecular - dynamics Cellular

Integrated on-they data analysis and image synthesis is one of the most dominant challenges on modern volume visualization tools. Since volume visualiza-tion algorithms are themself computationally complex and memory intensive there is hardly a chance to eeciently integrate data analysis tools on standard single processor architectures. The development and spreading of multiprocessor systems with large scale memory allow for the direct analysis and modiication of the data during the rendering process. But to eeciently integrate both tasks similar parallelization strategies and a unique data layout must be chosen. Furthermore, since more and more systems with hardware assisted processing and visualization options can be accessed across high performance networks, distributed visualization tools should beneet from these options whenever possible. In the following paper a prototyped parallel visualization environment will be exempliied in which data analysis and image synthesis are simultaneously performed on demand. The objective is to outline basic parallelization and distribution aspects which enable exible integration of diierent tasks rather than to present a concrete implementation. In this context the development and design of a unique algorithmic framework for integrated and/or distributed data analysis and image synthesis dominates the work hereafter.