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Workflow computations have become a major programming paradigm for scientific applications. However, acquiring enough computational resources to execute a workflow poses a challenge in a batch queue controlled resource due to the space-sharing nature of the resource management policy. This paper introduces a scheduling technique that aggregates a workflow application into several subcomponents. It then uses the batch queue to acquire resources for each subcomponent, overlapping resource provisioning overhead (wait time) of one with the execution of others. We implemented a prototype of this technique and tested it using five high performance computing centers job submission logs. The results show that our approach can eliminate as much as 70% of the wait time over more traditional techniques that request resources for individual workflow nodes or that acquire all the resources for the whole workflow at once.