Abstract Large-scale parallel simulations are a popular tool for investigating phenomena ranging from nuclear explosions to protein folding. These codes produce copious output that must be moved to the workstation where it will be visualized. Scientists have a variety of tools to help them with this data movement, and often have several different platforms available to them for their runs.
Scientists also control how much data is output, and how often.
To answer these questions, we built performance models for data migration approaches and verified them on parallel and sequential platforms.