User-steering of HPC workflows: state-of-the-art and future directions
Proceedings of the 2nd ACM SIGMOD Workshop on Scalable Workflow Execution Engines and Technologies
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Large-scale scientific computations are often organized as a composition of many computational tasks linked through data flow. The data that flows along this many- task computing often moves from a desktop to a high- performance environment and to a visualization environment. Keeping track of this data flow is a challenge to provenance support in high-performance Scientific Workflow Management Systems. After the completion of a computational scientific experiment, a scientist has to manually select and analyze its staged-out data, for instance, by checking inputs and outputs along computational tasks that were part of the experiment. In this paper, we present a provenance management system that describes the production and consumption relationships between data artifacts, such as files, and the computational tasks that compose the experiment. We propose a query interface that allows for scientists to browse provenance data and select the output they want to visualize using browsers or a high-resolution tiled display.