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Workflow task clustering for best effort systems with Pegasus
Proceedings of the 15th ACM Mardi Gras conference on From lightweight mash-ups to lambda grids: Understanding the spectrum of distributed computing requirements, applications, tools, infrastructures, interoperability, and the incremental adoption of key capabilities - MG '08
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. Indoi:10.1145/1341811.1341822 dblp:conf/mg/SinghSVDBGKM08 fatcat:bte7n5pjxzgmdpsrugxb5wtllu