Informatisches Kolloquium Sommersemester 2010
Montag, 28. Juni 2010
um 17 Uhr c.t.
Scalable In-Situ Data Extraction and Distributed Visualization
Prof. Dr.-Ing. Stephan Olbrich
Direktor des Regionalen Rechenzentrums
In the last few years, the data analysis and visualization aspect has dramatically gained in importance, since this part of the complete process chain is much more difficult to scale than the numerical cores of simulation models. 3D presentation of results of scientific computing - especially taking advantage of highly interactive virtual reality environments - has become feasible using low-cost equipment such as 3D monitors or TV sets and advanced 3D graphics cards, where the development was driven from the consumer market. In computational fluid dynamics typically 3D grids consisting of up to 1011 data points on 4000 cores can be simulated, which results in a non-stationary scenario (~104 time steps) in ~10 Petabyte raw result data. Since such an amount of data cannot be transferred or stored or explored using traditional approaches of separate post-processing, one topic of world-wide research is the development of tools to integrate data extraction in the simulation software, so-called "in-situ data extraction", and to take advantage of distributed systems for remote visualization.
We have developed a visualization middleware, which implements parallel in-situ data extraction by providing a programming library in order to minimize the sequential bottlenecks by parallelization of visualization mapping methods and to reduce the data volume by storing polygons and lines instead of raw data. Supporting synchronous, on-demand 3D presentation and interaction scenarios under bandwidth and rendering performance constraints, and nevertheless limiting the frame update time to get interactive rates, requires flexible and efficient reduction and post-filtering techniques. For this purpose, our data extraction library supports MPI-based computing environments and encapsulates a parallel implementation of vertex cluster based simplified isosurfaces, and parallel extraction of property-enhanced pathlines. These pathlines can be interactively post-filtered as part of a specialized, so-called "3D streaming server", which combines storage, filtering, and play-out of sequences of 3D scenes as a 3D movie, which can be navigated in real-time.
Kontakt: Prof. Dr. Christopher Habel
Telefon +49 40 428 83 2417