MRI: Acquisition of CASTOR: A High-Performance Communication and Storage Backbone for Data-Intensive Science and Engineering Computing

This project, adding high performance interconnections and true data-intensive storage facilities, involves a high performance communication and storage backbone, named CASTOR. With the interconnections, this backbone enables achievement of the full benefits of the grid strategy to support data-intensive research in diverse disciplines. Major campus facilities will be linked by a 10Gigabit/s network and supported by 24 Terabyte storage systems. CASTOR's high performance links are well matched to those of Florida Lambda Rail and National Lambda Rail. Serving the following research domains, High Energy Physics, Chemical Physics and Material Science, Coastal and Estuarine Modeling, Medical Physics, and Computational Biology, the new infrastructure will also serve Computer Science and Engineering on data-intensive, high-performance grids. CASTOR is expected to strengthen the collaboration between multidisciplinary teams across the institution and provide a unique resource for the projects in which the researchers participate. The infrastructure provides a unique resource for applications that require storing, processing, and communicating very large-scale data sets at very high speeds. Reflecting real-world scenarios, the work involves the following technologies:

* Grid Computing,

* Distributed Storage, and

* Advanced Networking.

The first involves the development innovative middleware techniques that complement and extend virtualization of physical information resources to hide infrastructure heterogeneity and allow applications to execute on grid-enabled resources with user control and interaction from various web-based interfaces. The second provides a trial version of the grid environment to operate queries, providing a proof-of-concept for deployment in larger systems. CASTOR serves as an 'ideal sandbox' to develop and test algorithms suitable for a distributed data pipeline. The last enables experiments in a research network operating at ultra-high speeds and multiple domains, hence contributes to enrich projects.