National Science Foundation Sponsors $5M Federated Cloud Project

Cloud infrastructure to support engineers and scientists working with big data

Chris Burt

November 6, 2015

2 Min Read
National Science Foundation Sponsors $5M Federated Cloud Project
(Photo by Sean Gallup/Getty Images)



This article originally appeared at The WHIR

The National Science Foundation is sponsoring a $5 million project to build a federated cloud of data infrastructure building blocks to support data scientists and engineers working with big data. The project is led by Cornell Universities’ Center for Advanced Computing, and is called the Aristotle Cloud Federation.

The federated cloud will be shared by 7 science teams with over 40 global collaborators, and will be deployed at Cornell, the University of Buffalo (UB), and theUniversity of California, Santa Barbara (UCSB). The teams will study earth and atmospheric sciences, finance, chemistry, astronomy, civil engineering, genomics, and food science, which were chosen to demonstrate the value of sharing resourced and data across institutional boundaries, even with diverse data analysis requirements and cloud usage modalities.

Earlier this week the NSF announced a grant of over $5 million to establish four regional data science innovation hubs at US universities. US Ignite received $6 million from the NSF in September to support local high-speed networks.

“This award continues NSF’s multi-year strategy to stimulate exploration of scalable and sustainable data infrastructure models that facilitate collaborative research across disciplines and institutions,” said Amy Walton, Program Director, Advanced Cyberinfrastructure Division, NSF. “By experimenting with cloud usage metrics, collaborating with a commercial cloud vendor, and exploring pricing/trading allocation mechanisms, the project will provide valuable information about how the innovations work in a range of situations, and how this ‘market approach’ integrates within the larger research ecosystem.”

The project will use metrics from UB’s XDMod (XD Metrics on Demand) and UCSB’s QBETS (Queue Bounds Estimation Time Series) to make predictions about where a given workload is best run, to efficiently use the federated cloud. It involves implementing a new allocations and accounting model that allows utilization data across federated sites to be tracked and used as an exchange mechanism.

It will burst to AWS, which will collaborate with federation developers and scientists.

This first ran at

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