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Published February 2008 | public
Book Section - Chapter

Workflow task clustering for best effort systems with Pegasus

Abstract

Many scientific workflows are composed of fine computational granularity tasks, yet they are composed of thousands of them and are data intensive in nature, thus requiring resources such as the TeraGrid to execute efficiently. In order to improve the performance of such applications, we often employ task clustering techniques to increase the computational granularity of workflow tasks. The goal is to minimize the completion time of the workflow by reducing the impact of queue wait times. In this paper, we examine the performance impact of the clustering techniques using the Pegasus workflow management system. Experiments performed using an astronomy workflow on the NCSA TeraGrid cluster show that clustering can achieve a significant reduction in the workflow completion time (up to 97%).

Additional Information

© 2008 ACM. This work was supported by NSF under OCI-0722019. We thank TeraGrid for the use of their resources.

Additional details

Created:
August 19, 2023
Modified:
October 23, 2023