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Institute
Large scale simulations running in metacomputing environments face the problem of efficient file I/O. For efficiency it is desirable to write data locally, distributed across the computing environment, and then to minimize data transfer, i.e.\ reduce remote file access. Both aspects require I/O approaches which differ from existing paradigms. For the data output of distributed simulations, one wants to use fast local parallel I/O for all participating nodes, producing a single distributed logical file, while keeping changes to the simulation code as small as possible. For reading the data file as in postprocessing and file based visualization, one wants to have efficient partial access to remote and distributed files, using a global naming scheme and efficient data caching, and again keeping the changes to the postprocessing code small. However, all available software solutions require the entire data to be staged locally (involving possible data recombination and conversion), or suffer from the performance problems of remote or distributed file systems. In this paper we show how to interface the HDF5 I/O library via its flexible Virtual File Driver layer to the Globus Data Grid. We show, that combining these two toolkits in a suitable way provides us with a new I/O framework, which allows efficient, secure, distributed and parallel file I/O in a metacomputing environment.
We present visualizations of recent supercomputer simulations from numerical relativity, exploiting the progress in visualization techniques and numerical methods also from an artistic point of view. The sequences have been compiled into a video tape, showing colliding black holes, orbiting and merging neutron stars as well as collapsing gravitational waves. In this paper we give some background information and provide a glance at the presented sequences.
Tensor Splats
(2003)
An improved general-purpose technique for the visualization of symmetric positive definite tensor fields of rank two is described. It is based on a splatting technique that is built from tiny transparent glyph primitives which are capable to incorporate the full directional information content of a tensor. The result is an information-rich image that allows to read off the preferred directions in a tensor field at each point of a three-dimensional volume or two-dimensional surface. It is useful for analyzing slices or volumes of a three-dimensional tensor field and can be overlayed with standard volume rendering or color mapping. The application of the rendering technique is demonstrated on general relativistic data and the diffusion tensor field of a human brain.