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Cornell University to develop federated cloud

David Lifka, Director of the Cornell University Center for Advanced Computing will lead the project

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Sonal Desai
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MUMBAI, INDIA: Cornell University will lead a five-year, $5 million project sponsored by the National Science Foundation (NSF) to build a federated cloud.

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Known as the Aristotle Cloud Federation, the cloud will comprise data infrastructure building blocks (DIBBs) designed to support scientists and engineers requiring flexible workflows and analysis tools for large-scale data sets.

The cloud will be deployed at Cornell University (CU), the University at Buffalo (UB), and the University of California, Santa Barbara (UCSB) and shared by seven science teams with over forty global collaborators.

David Lifka, Director of the Cornell University Center for Advanced Computing (CAC) will lead the project with colleagues Tom Furlani, Director of the UB Center for Computational Research, and Rich Wolski, Professor of Computer Science at UCSB.

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By Using XDMoD data and cloud-embedded performance monitors, QBETS will make it possible to predict the effects of federated work-sharing policies on user experience, both in the DIBBs cloud and in the Amazon Web Services (AWS) cloud.

Federation components, documentation, and best practices will be provided to the national community with the information to create customized virtual machine instances, leverage resources at federated sites, burst to AWS, access, move, and share large-scale data, and deploy new cloud federations.

Initial users like earth and atmospheric sciences, finance, chemistry, astronomy, civil engineering, genomics, and food science were selected based on the diversity of their data analysis requirements and cloud usage modalities, the university said in a prepared statement.

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Their use cases will demonstrate the value of sharing resources and data across institutional boundaries. The overarching goal is optimizing time to science—the actual time it takes a researcher to obtain their scientific results. The elasticity provided by sharing resources means researchers don’t have to wait for local resources to become available to get their science started.

“We plan to use Aristotle to exploit cloud-based parallelism and perform asynchronous, interactive analysis of complex environmental models that generate thousands of data files" said Patrick Reed, a Cornell University Civil and Environmental Engineering researcher who collaborates with University of North Carolina, Chapel Hill and Penn State engineers.

“We will use Aristotle to enhance our decision management tools so that we can solve problems of increasing complexity such as helping cities to better manage their drought risks,” he said.

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According to Varun Chandola, a Computer Science and Engineering researcher at the UB, massive troves of geospatial data such as earth observation and climate simulations are scattered around the world within the data archives of researchers, government, and the private sector.

Chandola is working with colleagues at NASA Ames and several universities on streamlining the integrated visualization and analysis of geo-data, said, “We plan to use Aristotle to develop a cloud-based solution that allows researchers to seamlessly integrate heterogeneous geo-data from a variety of sources into a cloud-based analysis engine."

“Research scientists and their collaborators are gathering sensor data and scientific images to optimize food productivity and security,” said Kate McCurdy, Director of the Sedgwick Reserve, a 5,896 acre nature reserve in California. “The scientists wish to combine this data with images taken by the general public and stored in commercial clouds,” she explained.

“By combining campus clouds and commercial cloud services, the federated cloud approach implemented by Aristotle will provide the data structure we need.”

“Sharing cloud computing and storage assets between institutions and bursting to commercial clouds is definitely a model worth a serious trial,” said Robert A Buhrman, Senior Vice Provost for Research at Cornell. “Creating federated clouds has the potential to increase multi-institutional and multi-disciplinary research collaborations, enhance data-driven insights, and reduce capital expenditures.”

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