Eran C. Withana

Effectiveness of Hybrid Workflow Systems for Computational Science

Abstract The workflow and its supporting systems are integral to computational science. Tailored to loosely coupled, and largely coarse-grained tasks, the workflow replaces the script as a way to automate the multiple steps of a large scale model. Workflow reuse has been at the subworkflow level but this restricts, over the long run, a workflow to running on the system on which it was developed. A scientist wanting to use two workflows developed by two different people and for different workflow systems will need to have access to both workflow systems. The contribution this paper makes is a qualitative and quantitative study of the tradeoffs of a hybrid workflow solution that utilizes multiple workflow systems and solutions to execute a single workflow. Our results indicate that the major tradeoffs are not in performance as much as they are in complexity.

Sigiri: uniform resource abstraction for grids and clouds

With the maturation of grid computing facilities and recent explosion of cloud computing data centers, midscale computational science has more options than ever before to satisfy computational needs. But heterogeneity brings complexity. We propose a simple abstraction for interaction with heterogeneous resource managers spanning grid and cloud computing and on features that make the tool useful for the midscale physical or natural scientist. Key strengths of the abstraction are its support for multiple standard job specification languages, preservation of direct user interaction with the service, removing the delay that can come through layers of services, and the predictable behavior under heavy loads. Copyright

Versioning for workflow evolution

Scientists working in eScience environments often use workflows to carry out their computations. Since the workflows evolve as the research itself evolves, these workflows can be a tool for tracking the evolution of the research. Scientists can trace their research and associated results through time or even go back in time to a previous stage and fork to a new branch of research. In this paper we introduce the workflow evolution framework (EVF), which is demonstrated through implementation in the Trident workflow workbench. The primary contribution of the EVF is efficient management of knowledge associated with workflow evolution. Since we believe evolution can be used for workflow attribution, our framework will motivate researchers to share their workflows and get the credit for their contributions.