Most researchers who perform data analysis and visualization do so only aft
er 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 vis
ualization into the entire process so that they can make adjustments along
the way. This approach, called computational steering, is the capacity to c
ontrol all aspects of the computational science pipeline.
Recently, several tools and environments for computational steering have be
gun to emerge. These tools range from those that modify an application's pe
rformance 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 dev
elopment to application steering.
The authors discuss some tools that provide a mechanism to integrate modeli
ng, simulation, data analysis, and visualization.