Published November 16, 2015
The U.S. National Science Foundation (NSF) is underwriting a five-year, $5-million project to build the Aristotle Cloud Federation, a federated cloud of data infrastructure building blocks (DIBBs) that will support scientists and engineers requiring elastic workflows and analysis tools for large-scale data sets.
The federated 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.
Initial users of the cloud federation—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. 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.
Metrics provided by UB's XDMoD (XD Metrics on Demand) and UCSB's QBETS (Queue Bounds Estimation Time Series) will enable researchers and administrators to make informed decisions about when to use federated resources outside their institutions.
“Cloud-based systems are rapidly becoming a key component in the support of research programs in academe and industry. By adding cloud metrics to XDMoD, researchers and senior leaders will be able to obtain detailed operational metrics of cloud systems in order to improve the efficiency of jobs run on the cloud, as well as measure overall cloud performance,” said Furlani. “Efficient use of federated clouds requires the ability to make predictions about where a workload will run best,” added Wolski. “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.”
"The goal of the Aristotle Cloud Federation is to develop a federated cloud model that encourages and rewards institutions for sharing large-scale data analysis resources that can be expanded internally with common, incremental building blocks and externally through meaningful collaborations with other institutions, commercial clouds, and NSF cloud resources," said project PI Lifka. The project name—Aristotle—was chosen because Aristotle’s concept “the whole is greater than the sum of its parts” reflects the multi-institutional synergy and collaborations that the federation aspires to create.
The project will implement a new allocations and accounting model that will allow institutional administrators to track utilization across federated sites and use this data as an exchange mechanism between partner sites. This data will demonstrate the potential benefits of sharing institutional resources such as deploying local infrastructure that is right-sized for steady state usage rather than irregular peak loads.
Federation components, documentation, and best practices developed in this grant will be provided to the national community with the information necessary 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.
Cloud provider AWS will collaborate with the federation developers and scientists. “We are excited to work with the Aristotle team to provide cost-effective and scalable infrastructure that helps accelerate the time to science," said Jamie Kinney, Senior Manager Scientific Computing, Amazon Web Services, Inc.
More coverage is available on these technical websites:
Cloud Strategy Magazine
Digitilisation World (UK)
Government Computing News
Next Generation Communications
Scientific Computing Magazine