Abstract

Researchers working on the planning, scheduling and execution of scientific workflows need access to a wide variety of scientific workflows to evaluate the performance of their implementations. We describe basic workflow structures that are composed into complex workflows by scientific communities. We provide a characterization of workflows from five diverse scientific applications, describing their composition and data and computational requirements. We also describe the effect of the size of the input datasets on the structure and execution profiles of these workflows. Finally, we describe a workflow generator that produces synthetic, parameterizable workflows that closely resemble the workflows that we characterize. We make these workflows available to the community to be used as benchmarks for evaluating various workflow systems and scheduling algorithms.