  Workflows are critical for scientific discovery. However, the sophistication,
heterogeneity, and scale of workflows make building, testing, and optimizing
them increasingly challenging. Furthermore, their complexity and heterogeneity
make performance reproducibility hard. In this paper, we propose workflow
mini-apps as a tool to address the challenges in building and testing workflows
while controlling the fidelity of representing realworld workflows. Workflow
mini-apps are deployed and run on various HPC systems and architectures without
workflow-specific constraints. We offer insight into their design and
implementation, providing an analysis of their performance and reproducibility.
Workflow mini-apps thus advance the science of workflows by providing simple,
portable, and managed (fidelity) representations of otherwise complex and
difficult-to-control real workflows.
