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Managing the large volumes of data produced by emerging scienti?c and engineering simulations running on leadership-class resources has become a critical challenge. The data has to be extracted off the computing nodes and transported to consumer nodes so that it can be processed, analyzed, visualized, archived, etc. Several recent research efforts have addressed datarelated challenges at different levels. One attractive approach is to of?oad expensive I/O operations to a smaller set of dedicated computing nodes known as a staging area. However, even using this approach, the data still has to be moved from the staging area to consumer nodes for processing, which continues to be a bottleneck. In this paper, we investigate an alternate approach, namely moving the data-processing code to the staging area rather than moving the data. Speci?cally, we present the ActiveSpaces framework, which provides (1) programming support for de?ning the data-processing routines to be downloaded to the staging area, and (2) run-time mechanisms for transporting binary codes associated with these routines to the staging area, executing the routines on the nodes of the staging area, and returning the results. We also present an experimen- tal performance evaluation of ActiveSpaces using applications running on the Cray XT5 at Oak Ridge National Laboratory. Finally, we use a coupled fusion application work?ow to explore the trade-offs between transporting data and transporting the code required for data processing during coupling, and we characterize the sweet spots for each option.

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