Vision of the Visualisation
Cluster and Grid network distributed supercomputing and scientific visualization are a powerful combination today in scientific work. Researchers in computational science and engineering rely heavily on scientific visualization to represent solutions. Computer generated images can aid scientists and engineers to better understand the physical world such as nonlinear dynamic motion, physical and chemical interactions, genetic structures,medical examinations and surgical operations, manufacturing processes and design optimization etc. It is a goal of researchers to apply scientific visualization techniques to analyze and display the results of large scale and complex simulations carried out on high performance computers and to animate images at high speed under interactive, user control at nanometre space and nanosecond time resolution. The scientific visualization system should therefore be interactive, modular in viewing, modular in modelling, extensible by toolkit, user configurable and object oriented. The high performance computing environment of the future should make computers and networks transparent to end user. Applications will be executed on the most suitable computer on the network without user knowing where they are carried out. The ideal scientific visualization environment will be a network of graphics workstations linked to graphics supercomputers, massively parallel processors and vector supercomputers. Effective distribution of graphics computation and rendering capabilities for scientific visualization on this network of heterogeneous computers hold the key to the success of the systems.
eScience Program provides specialized computing and communication resources in support of computational science and engineering, scientific visualization, computer graphics, and other disciplines that require high-performance computing, networking, storage or graphics. Typical applications include scientific and engineering simulation, data analysis and visualization, image manipulation, and the graphic and fine design arts. Visualization generates pictures from data and allows the user to interact with these.
Scientific Visualization has evolved as a separate scientific area in the last few years and deals with the visual representation of abstract data (i.e. data bases). Often the data is missing inherent local attribution. Also quite often data in higher dimensions (compared to volume and flow visualization) has to be displayed. The main goals of Scientific visualisation are therefore the effective 2D or 3D-display of high dimensional data, as well as the possibility of useful interaction to influence the visualization or to work with the data itself. Virtual Reality (VR) is a simulation of different aspects of our reality with computers. In most cases these aspects include visual impressions and interactive reaction with the simulation. Virtual reality and visualization represent key technologies for the development of information processing. Virtual Reality and Visualization are key-technologies for communication. They enable not only the fast, meaningful and concise processing of data in a time of growing amounts of data, but also the realistic display of and the interaction with past, current and future objects and surroundings. The scientific visualization tools used by the engineer should evolve to meet the growing demands presented by large simulation data sets. Furthermore, no single visualization technique can meet each users needs and convergent to the new Visual analytics discipline.
- The resources provided by eScience (Scientific Computing Facilities) include:
- High-performance, parallel computing systems and networks
- Network data and knowledge storage
- Scientific code parallelization and optimization
- Scientific multidimensional data visualization
- High-performance and high-resolution interactive three-dimensional graphics
- Virtual collaborative environments/virtual reality
- Remote education, consulting and training
- Network-based video conferencing and collaboration tools
IRB eScience Program time line