Ultra-scale Visualization with Open-Source Software

Berk Geveci
Seminar

Several factors are driving the growth of scientific simulations. Computational power of computer clusters is growing while the price of individual computers is decreasing. Distributed computing techniques allow thousands of computer nodes to participate in a single simulation. The benefit of this computational power is that simulations are getting more accurate and useful for predicting complex phenomena. The downside to this growth in computational power is that enormous amounts of data need to be saved and analyzed to determine the results of the simulation. The ability to generate data has outpaced our ability to save and analyze the data. This bottleneck is throttling our ability to benefit from our improved computing resources.

In this talk, I will discuss a few of Kitware's projects that aim to close the gap between simulation and analysis. The main focus will be on in-situ processing (aka co-processing). In-situ processing involves tying the visualization/analysis code with the simulation code. We have been developing tools to enable this type of processing by extending the ParaView visualization framework. I will also briefly talk about collaborative visualization using desktop and web applications as well as the analysis of dataset ensembles.