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NSF-CRI: A Hierarchical Data Storage System
This project, acquiring a large-scale hierarchical storage management (HSM) system, provides access to the increasingly large datasets produced and analyzed by the members and collaborators of the Scientific Computing and Imaging (SCI) Institute at Utah. This institute creates new techniques, tools, and systems by which scientists may solve computational and imaging problems in many disciplines. The expertise utilized in addressing the problems include image and signal processing, modeling, simulation, and visualization. The work exploits the multidisciplinary mission of SCI. A large-scale HSM solution provides the ability to generate canonical datasets, accessible by researchers within SCI and many collaborators outside. The field of scientific computing is constrained by the problems posed by dataset management and storage. Dataset size and complexity has grown in parallel with available compute resource. Centralized, ready access to the modeling, simulation, and analysis data is fundamental to success. Dataset complexity grows as a product of compute resource and algorithm efficiency; while research in complex problems relies on this ever-increasing efficiency for its progress. Although computational speeds have increased dramatically, the complexity of the models produced has also increased, so that while models and simulations have improved their research effectiveness, the actual computation time needed to generate a given simulation has not declined. An advanced storage architecture helps in streamlining the workflow for a variety of data intensive research projects.

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