From the Cosmic Frontier to CERN, New Platform Stitches Together Global Science Efforts
SLATE will enable creation of new platforms for collaborative science
Today’s most ambitious scientific quests — from the cosmic radiation measurements by the South Pole Telescope to the particle physics of CERN — are multi-institutional research collaborations requiring computing environments that connect instrumentation, data, and computational resources. Because of the scale of the data and the complexity of this science, these resources are often distributed among university research computing centers, national high performance computing centers, or commercial cloud providers. This can cause scientists to spend more time on the technical aspects of computation than on discoveries and knowledge creation, while computing support staff are required to invest more effort integrating domain specific software with limited applicability beyond the community served.
With Services Layer At The Edge (SLATE), a $4 million project funded by the National Science Foundation, the University of Michigan joins a team led by the Enrico Fermi and Computation Institutes at University of Chicago to provide technology that simplifies connecting university and laboratory data center capabilities to the national cyberinfrastructure ecosystem. The University of Utah is also participating. Once installed, SLATE connects local research groups with their far-flung collaborators, allowing central research teams to automate the exchange of data, software and computing tasks among institutions without burdening local system administrators with installation and operation of highly customized scientific computing services. By stitching together these resources, SLATE will also expand the reach of domain-specific “science gateways” and multi-site research platforms.
“Science, ultimately, is a collective endeavor. Most scientists don’t work in a vacuum, they work in collaboration with their peers at other institutions,” said Shawn McKee, a co-PI on the project and director of the Center for Network and Storage-Enabled Collaborative Computational Science at the University of Michigan. “They often need to share not only data, but systems that allow execution of workflows across multiple institutions. Today, it is a very labor-intensive, manual process to stitch together data centers into platforms that provide the research computing environment required by forefront scientific discoveries.”
SLATE works by implementing “cyberinfrastructure as code”, augmenting high bandwidth science networks with a programmable “underlayment” edge platform. This platform hosts advanced services needed for higher-level capabilities such as data and software delivery, workflow services and science gateway components.
U-M has numerous roles in the project including:
- defining, procuring and configuring much of the SLATE hardware platform
- working on the advanced networking aspects (along with Utah) which includes Software Defined Networking (SDN) and Network Function Virtualization (NFV),
- developing the SLATE user interface and contributing to the core project design and implementation.
The project is similar to the OSiRIS project led by McKee, which also aims to remove bottlenecks to discovery posed by networking and data transfer infrastructure.
SLATE uses best-of-breed data center virtualization components, and where available, software defined networking, to enable automation of lifecycle management tasks by domain experts. As such, it simplifies the creation of scalable platforms that connect research teams, institutions and resources, accelerating science while reducing operational costs and development time. Since SLATE needs only commodity components, it can be used for distributed systems across all data center types and scales, thus enabling creation of ubiquitous, science-driven cyberinfrastructure.
At UChicago, the SLATE team will partner with the Research Computing Center and Information Technology Services to help the ATLAS experiment at CERN, the South Pole Telescope and the XENON dark matter search collaborations create the advanced cyberinfrastructure necessary for rapidly sharing data, computer cycles and software between partner institutions. The resulting systems will provide blueprints for national and international research platforms supporting a variety of science domains.
For example, the SLATE team will work with researchers from the Computation Institute’s Knowledge Lab to develop a hybrid platform that elastically scales computational social science applications between commercial cloud and campus HPC resources. The platform will allow researchers to use their local computational resources with the analytical tools and sensitive data shared through Knowledge Lab’s Cloud Kotta infrastructure, reducing cost and preserving data security.
“SLATE is about creating a ubiquitous cyberinfrastructure substrate for hosting, orchestrating and managing the entire lifecycle of higher level services that power scientific applications that span multiple institutions,” said Rob Gardner, a Research Professor in the Enrico Fermi Institute and Senior Fellow in the Computation Institute. “It clears a pathway for rapidly delivering capabilities to an institution, maximizing the science impact of local research IT investments.”
Many universities and research laboratories use a “Science DMZ” architecture to balance security with the ability to rapidly move large amounts of data in and out of the local network. As sciences from physics to biology to astronomy become more data-heavy, the complexity and need for these subnetworks grows rapidly, placing additional strain on local IT teams.
That stress is further compounded when local scientists join multi-institutional collaborations, often requiring the installation of specialized, domain-specific services for the sharing of compute and data resources.
With SLATE, research groups will be able to fully participate in multi-institutional collaborations and contribute resources to their collective platforms with minimal hands-on effort from their local IT team. When joining a project, the researchers and admins can select a package of software from a cloud-based service — a kind of “app store” — that allows them to connect and work with the other partners.
“Software and data can then be updated automatically by experts from the platform operations and research teams, with little to no assistance required from local IT personnel,” said Joe Breen, Senior IT Architect for Advanced Networking Initiatives at the University of Utah’s Center for High Performance Computing. “While the SLATE platform is designed to work in any data center environment, it will utilize advanced network capabilities, such as software defined overlay networks, when the devices support it.”
By reducing the technical expertise and time demands for participating in multi-institution collaborations, the SLATE platform will be especially helpful to smaller universities that lack the resources and staff of larger institutions and computing centers. The SLATE functionality can also support the development of “science gateways” which make it easier for individual researchers to connect to HPC resources such as the Open Science Grid and XSEDE.
“A central goal of SLATE is to lower the threshold for campuses and researchers to create research platforms within the national cyberinfrastructure,” Gardner said.
Initial partner sites for testing the SLATE platform and developing its architecture include New Mexico State University and Clemson University, where the focus will be creating distributed cyberinfrastructure in support of large scale bioinformatics and genomics workflows. The project will also work with the Science Gateways Community Institute, an NSF funded Scientific Software Innovation Institute, on SLATE integration to make gateways more powerful and reach more researchers and resources.
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The Computation Institute (CI), a joint initiative of the University of Chicago and Argonne National Laboratory, is an intellectual nexus for scientists and scholars pursuing multi-disciplinary research and a resource center for developing and applying innovative computational approaches. Founded in 1999, it is home to over 100 faculty, fellows, and staff researching complex, system-level problems in such areas as biomedicine, energy and climate, astronomy and astrophysics, computational economics, social sciences and molecular engineering. CI is home to diverse projects including the Center for Robust Decision Making on Climate and Energy Policy, Knowledge Lab, The Urban Center for Computation and Data and the Center for Data Science and Public Policy.
For more information, contact Dan Meisler, Communications Manager, Advanced Research Computing at U-M: dmeisler@umich.edu, 734-764-7414
The Michigan Institute for Computational Discovery & Engineering and the University of Michigan Center for Academic Innovation have partnered to launch a Massive Open Online Course (MOOC) titled Problem Solving using Computational Thinking. The idea for this MOOC arose from the team’s recognition of the ubiquity of computation. However, the developers were equally keen to distinguish this offering from MOOCs on programming, and to instead highlight how broader computational thinking also makes its presence felt in somewhat unexpected domains. The MOOC is organized in a series of real-world examples that includes how, using computational thinking, it is possible to help plan and prepare for a flu season, track human rights violations or monitor the safety of crowds. The process of computational thinking that this MOOC focuses on ranges from problem identification, through abstraction to evaluating solutions. Problem Solving using Computational Thinking seeks to introduce students and teachers to the systematic thinking needed to conceptualize a problem with the intent of eventually using some computational tools to solve it.
