WfCommons: Data Collection and Runtime Experiments using Multiple Workflow Systems

Abstract

Scientific workflows have become ubiquitous across scientific fields, and their execution methods and systems continue to be the subject of research and development. Most experimental evaluations of these workflows rely on workflow instances, which can be either real-world or synthetic, to ensure relevance to current application domains or explore hypothetical/future scenarios. The WfCommons project addresses this need by providing data and tools to support such evaluations. In this paper, we present an overview of WfCommons and describe two recent developments. Firstly, we introduce a workflow execution "tracer" for Nextflow, which significantly enhances the set of real-world instances available in WfCommons. Secondly, we describe a workflow instance "translator" that enables the execution of any real-world or synthetic WfCommons workflow instance using Dask. Our contributions aim to provide researchers and practitioners with more comprehensive resources for evaluating scientific workflows.