Most researchers who perform data analysis and visualization do so only after everything else is finished, which often means that they don't discover errors invalidating the results of their simulation until postp...
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Most researchers who perform data analysis and visualization do so only after everything else is finished, which often means that they don't discover errors invalidating the results of their simulation until postprocessing. A better approach would be to improve the integration of simulation and visualization into the entire process so that they can make adjustments along the way. This approach, called computational steering, is the capacity to control all aspects of the computational science pipeline. Recently, several tools and environments for computational steering have begun to emerge. These tools range from those that modify an application's performance characteristics, either by automated means or by user interaction, to those that modify the underlying computational application. A refined problem-solving environment should facilitate everything from algorithm development to application steering. The authors discuss some tools that provide a mechanism to integrate modeling, simulation, data analysis, and visualization.
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