Performance evaluation is crucial to understanding the behavior of scientific workflows. In
this study, we target an emerging type of workflow, called in situ workflows. These workflows
tightly couple components such as simulation and analysis to improve overall workflow
performance. To understand the tradeoffs of various configurable parameters for coupling
these heterogeneous tasks, namely simulation stride, and component placement, separately
monitoring each component is insufficient to gain insights into the entire workflow behavior …