Introduction to Scientific Workflows

Submitter: Yuan Zhang
Submitter's Institution: Ohio Supercomputer Center
Submission Date: 2015-12-11
Description: Scientific workflows allow users to easily express multi-step computational tasks, for example retrieve data from an instrument or a database, reformat the data, and run an analysis. A scientific workflow describes the dependencies between the tasks and in most cases the workflow is described as a directed acyclic graph (DAG), where the nodes are tasks and the edges denote the task dependencies. A defining property for a scientific workflow is that it manages data flow. The tasks in a scientific workflow can be everything from short serial tasks to very large parallel tasks (MPI for example) surrounded by a large number of small, serial tasks used for pre- and post-processing.

• https://www.xsede.org/documents/161616/c23848a3-e246-4baa-a854-56910d1f1f7e
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