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Grid and Internet Computing have proved their worth executing large-scale bag-of-task class applications. Numerous middlewares have been developed to manage their execution in either dedicated environments or opportunistic and shared ad-hoc grids. While job dependencies are now being resolved by middleware capable of scheduling workflows, these environments have yet to be shown beneficial for message passing parallel applications. Obtaining high performance in these widely available environments without rewriting existing parallel applications is of up most importance to e-Science . The key to an efficient solution may be an alternative execution model and the efficient dynamic scheduling of application processes. This paper presents a hierarchical scheme for dynamically scheduling parallel DAG applications across a set of non-dedicated heterogeneous resources. In order to efficiently tackle process dependencies and adapt to varying system characteristics, dynamic schedulers are distributed within the application and operate in a collaborative and pro-active fashion to keep overheads low.

On the Feasibility of Dynamically Scheduling DAG Applications on Shared Heterogeneous Systems