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Modern High Performance Computing (HPC) applications process very large amounts of data. A critical research challenge lies in transporting input data to the HPC center from a number of distributed sources, e.g., scienti?c experiments and web repositories, etc., and of?oading the result data to geographically distributed, intermittently available end-users, often over under-provisioned connections. Such end-user data services are typically performed using point-to-point transfers that are designed for well-endowed sites and are unable to reconcile the centerâ€™s resource usage and usersâ€™ delivery deadlines, unable to adapt to changing dynamics in the end-to-end data path and are not fault-tolerant. To overcome these inef?ciencies, decentralized HPC data services are emerging as viable alternatives. In this paper, we develop and enhance such distributed data services by designing CATCH, a Cloud-based Adaptive data Transfer serviCe for HPC. CATCH leverages a bevy of cloud storage resources to orchestrate a decentralized data transport with fail-over capabilities. Our results demonstrate that CATCH is a feasible approach, and can help improve the data transfer times at the HPC center by as much as 81.1% for typical HPC workloads.
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