Smartblock: An Approach To Standardizing In Situ Workflow Components

Multi-step scientific workflows have become prominent and powerful tools of data-driven scientific discovery. Run-time analytic techniques are now commonly used to mitigate the performance effects of using parallel file systems as staging areas during workflow execution. However, workflow construction and deployment for extreme-scale computing is still largely an ad hoc process with uneven support from existing tools. In this paper, we present SMARTBLOCK, an approach to designing generic, reusable components for end-to-end construction of workflows. Specifically, we demonstrate that a small set of SMARTBLOCK generic components can be reused to build a diverse set of workflows, using examples based on actual analytic processes with three well-known scientific codes. Our evaluation shows promising scaling properties as well as negligible overheads for using a modular approach over a custom, "all-in-one" solution. As extreme-scale systems incorporate data analytics on simulation data as it is generated at rates that far outstrip available I/O bandwidth, tools such as SMARTBLOCK will become increasingly valuable for defining and deploying flexible, efficient workflows.