Workflow Systems

Workflow Systems#

DesignSafe’s cyberinfrastructure brings together the computational power of TACC with the ease of cloud-based interfaces, allowing researchers to move seamlessly between interactive exploration and large-scale, production-level computation. Whether you’re testing a small python script inside a Jupyter notebook or deploying thousands of simulations across Stampede3, DesignSafe’s ecosystem is built to scale with you — from one core to tens of thousands.

While execution strategies describe how computation should be structured, then workflow systems describe how those strategies are implemented, automated, and managed across real computing resources.

At its heart, DesignSafe is not just a collection of tools — it is a workflow system designed to support the full life cycle of computational research:

  • developing models and scripts,

  • running and monitoring simulations,

  • managing input and output data, and

  • sharing or reproducing results.

Each of these stages may occur in a different computational environment, accessed through different interfaces, but connected by a common middleware layer that handles execution, authentication, and data transfer. This structure makes DesignSafe powerful, but it also means that understanding how jobs flow through the system is key to working efficiently and avoiding common pitfalls.

When you launch a job, the workflow system orchestrates a sequence of actions: your code or application is packaged, transferred to a compute system, queued by a scheduler, executed across one or more nodes, and finally collected and stored for postprocessing. Each of these steps occurs in a different conceptual layer of the architecture — the interface environment, the execution environment, and the API layer that connects them.

Understanding these layers helps you:

  • choose the right tool for your task (interactive vs. batch, exploratory vs. production),

  • optimize job performance and resource allocation,

  • build automated, portable workflows that scale from prototypes to production, and

  • troubleshoot or customize advanced workflows with confidence.