U-M joins NSF-funded SLATE project to simplify scientific collaboration on a massive scale

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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.

slateAt 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

Info sessions on graduate studies in computational and data sciences — Sept. 21 and 25

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Learn about graduate programs that will prepare you for success in computationally intensive fields — pizza and pop provided

  • The Ph.D. in Scientific Computing is open to all Ph.D. students who will make extensive use of large-scale computation, computational methods, or algorithms for advanced computer architectures in their studies. It is a joint degree program, with students earning a Ph.D. from their current departments, “… and Scientific Computing” — for example, “Ph.D. in Aerospace Engineering and Scientific Computing.”
  • The Graduate Certificate in Computational Discovery and Engineering trains graduate students in computationally intensive research so they can excel in interdisciplinary HPC-focused research and product development environments. The certificate is open to all students currently pursuing Master’s or Ph.D. degrees at the University of Michigan.
  • The Graduate Certificate in Data Science is focused on developing core proficiencies in data analytics:
    1) Modeling — Understanding of core data science principles, assumptions and applications;
    2) Technology — Knowledge of basic protocols for data management, processing, computation, information extraction, and visualization;
    3) Practice — Hands-on experience with real data, modeling tools, and technology resources.

Times / Locations:

Siqian Shen (IOE) to receive an Early Career Award from the Department of Energy

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siqian-shen-featuredMICDE Associate Director Siqian Shen has been selected to receive an Early Career Award for the Department of Energy Office of Science by the DoE Office of Advanced Scientific Computing Research. The objective of her proposal titled “Extreme‐Scale Stochastic Optimization and Simulation via Learning‐Enhanced Decomposition and Parallelization” is to develop an efficient and unified framework that integrates machine learning with discrete optimization and risk‐averse modeling. The models considered represent a broad class of complex decision‐making problems, where 0‐1 or continuous decisions are made before and/or after knowing multiple and potentially correlated sources of uncertainties. This research will shed new light on the traditional decomposition algorithms for high‐performance computing.

Prof. Shen was recently promoted to Associate Professor of Industrial and Operations Engineering. To learn more about her research please visit http://micde.umich.edu/faculty-member/siqian-shen/.

The Early Career Award program from the US Department of Energy is a funding opportunity for researchers in universities and DOE national laboratories to support the development of individual research programs of outstanding scientists early in their careers. For the past 8 years this program has helped stimulate research careers in the disciplines supported by the DOE Office of Science. These include Advanced Scientific Computing Research (ASCR); Biological and Environmental Research (BER); Basic Energy Sciences (BES), Fusion Energy Sciences (FES); High Energy Physics (HEP), and Nuclear Physics (NP).

U-M, SJTU research teams share $1 million for data science projects

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Five research teams from the University of Michigan and Shanghai Jiao Tong University in China are sharing $1 million to study data science and its impact on air quality, galaxy clusters, lightweight metals, financial trading and renewable energy.

Since 2009, the two universities have collaborated on a number of research projects that address challenges and opportunities in energy, biomedicine, nanotechnology and data science.

In the latest round of annual grants, the winning projects focus on data science and how it can be applied to chemistry and physics of the universe, as well as finance and economics.

For more, read the University Record article.

For descriptions of the research projects, see the MIDAS/SJTU partnership page.

SAVE THE DATE: MIDAS Annual Symposium, Oct. 11

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Please join us for the 2017 Michigan Institute for Data Science Symposium.

The keynote speaker will be Cathy O’Neil, mathematician and best-selling author of “Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy.”

Other speakers include:

  • Nadya Bliss, Director of the Global Security Initiative, Arizona State University
  • Francesca Dominici, Co-Director of the Data Science Initiative and Professor of Biostatistics, Harvard T.H. Chan School of Public Health
  • Daniela Whitten, Associate Professor of Statistics and Biostatistics, University of Washington
  • James Pennebaker, Professor of Psychology, University of Texas

More details, including how to register, will be available soon.

New Data Science Computing Platform Available to U-M Researchers

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Advanced Research Computing – Technology Services (ARC-TS) is pleased to announce an expanded data science computing platform, giving all U-M researchers new capabilities to host structured and unstructured databases, and to ingest, store, query and analyze large datasets.

The new platform features a flexible, robust and scalable database environment, and a set of data pipeline tools that can ingest and process large amounts of data from sensors, mobile devices and wearables, and other sources of streaming data. The platform leverages the advanced virtualization capabilities of ARC-TS’s Yottabyte Research Cloud (YBRC) infrastructure, and is supported by U-M’s Data Science Initiative launched in 2015. YBRC was created through a partnership between Yottabyte and ARC-TS announced last fall.

The following functionalities are immediately available:

  • Structured databases:  MySQL/MariaDB, and PostgreSQL.
  • Unstructured databases: Cassandra, MongoDB, InfluxDB, Grafana, and ElasticSearch.
  • Data ingestion: Redis, Kafka, RabbitMQ.
  • Data processing: Apache Flink, Apache Storm, Node.js and Apache NiFi.

Other types of databases can be created upon request.

These tools are offered to all researchers at the University of Michigan free of charge, provided that certain usage restrictions are not exceeded. Large-scale users who outgrow the no-cost allotment may purchase additional YBRC resources. All interested parties should contact hpc-support@umich.edu.

At this time, the YBRC platform only accepts unrestricted data. The platform is expected to accommodate restricted data within the next few months.

ARC-TS also operates a separate data science computing cluster available for researchers using the latest Hadoop components. This cluster also will be expanded in the near future.

XSEDE Research Allocation Requests due July 15th

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XSEDE Allocations award eligible users access to compute, visualization, and/or storage resources as well as extended support services.

XSEDE has various types of allocations from short term exploratory request to year long projects. In order to access to XSEDE resources you must have an allocation. Submit your allocation requests via the XSEDE Resource Allocation System (XRAS) in the XSEDE User Portal.

ARC-TS consultants can help researchers navigate the XSEDE resources and process. Contact them at hpc-support@umich.edu

Big Data in Transportation and Mobility symposium highlights diverse, emerging issues

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MBDH-transThe Big Data in Transportation and Mobility symposium held June 22-23, 2017, in Ann Arbor, MI brought together more than 150 data science practitioners from academia, industry and government to explore emerging issues in this expanding field.

Sponsored by the NSF-supported Midwest Big Data Hub (MBDH) and the Michigan Institute for Data Science (MIDAS), the symposium featured lightning talks from transportation research programs around the Midwest; tutorials and breakout sessions on specific issues and methods; a poster session; and a keynote address from two representatives of the Smart Columbus project: Chris Stewart, Ohio State University Associate Professor of Computer Science and Engineering, and Shoreh Elhami, GIS Manager for the city of Columbus.

Speakers and attendees came from a number of organizations from across the midwest including the University of Michigan, University of Illinois, University of Nebraska, University of North Dakota, North Dakota State University, Ohio State University, Purdue University, Denso International America, Fiat Chrysler, Ford Motor Company, General Motors, IAV Automotive Engineering and Yottabyte.  

“This was an extremely valuable opportunity to share information and ideas,” said Carol Flannagan, one of the organizers of the symposium and a researcher at MIDAS and the U-M Transportation Research Institute. “Cross-discipline and cross-institutional collaboration is crucial to the success of Big Data applications, and we took a significant step forward in that vein during this symposium.”

Topics addressed in talks, breakouts, and tutorials included:

  • New Analytic Tools for Designing and Managing Transportation Systems
  • New Mobility Options for Small and Mid-sized Cities in the Midwest
  • Automated and Connected Vehicles
  • Transforming Transportation Operations using High Performance Computing
  • On-Demand Transit
  • Using Big Data for Monitoring Bridges

At the closing session, participants outlined some areas that could be fruitful to focus on going forward, including increasing data-science literacy in the general public; diversity and workforce development in data science; public data-sharing platforms and partners; and privacy issues.

For a complete list of speakers and topics, please see the agenda. Videos of selected talks will be posted at midas.umich.edu in the coming days.

MICDE announces 2017-2018 Fellowship recipients

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MICDE is pleased to announce the recipients of the 2017-2018 MICDE Fellowships for students enrolled in the PhD in Scientific Computing or the Graduate Certificate in Computational Discovery and Engineering. We had 91 applicants from 25 departments representing 6 schools and colleges. Due to the extraordinary number of high quality applications we increased the number of fellowships from 15 to 20 awards. See our Fellowship page for more information.

AWARDEES

Diksha Dhawan, Chemistry
Negar Farzaneh, Computational Medicine & Bioinformatics
Kritika Iyer, Biomedical Engineering
Tibin John, Neuroscience
Bikash Kanungo, Mechanical Engineering
Yu-Han Kao, Epidemiology
Steven Kiyabu, Mechanical Engineering
Christiana Mavroyiakoumou, Mathematics
Ehsan Mirzakhalili, Mechanical Engineering
Colten Peterson, Climate and Space Sciences & Engineering
James Proctor, Materials Science & Engineering
Evan Rogers, Biomedical Engineering
Longxiu Tian, S. Ross School of Business
Jipu Wang, Nuclear Engineering and Radiological Sciences
Yanming Wang, Chemistry
Zhenlin Wang, Mechanical Engineering
Alicia Welden, Chemistry
Anna White, Industrial & Operations Engineering
Chia-Nan Yeh, Physics
Yiling Zhang, Industrial & Operations Engineering

HONORABLE MENTIONS

Geunyeong Byeon, Industrial & Operations Engineering
Ayoub Gouasmi, Aerospace Engineering
Joseph Kleinhenz, Physics
Jia Li, Physics
Changjiang Liu, Biophysics
Vo Nguyen, Computational Medicine & Bioinformatics
Everardo Olide, Applied Physics
Qiyun Pan, Industrial & Operations Engineering
Pengchuan Wang, Civil & Environmental Engineering
Xinzhu Wei, Ecology & Evolutionary Biology

COMPUTATIONAL SCIENCE AROUND U-M: Increasing women participation in computing education

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5 faculty members recognized for working towards increasing women participation in computing education

Four faculty members of the University of Michigan’s division of Computer Science Engineering (CSE) and one from the department of Naval Architecture and Marine Engineering (NAME) were awarded second place in the NCWIT Extension Services Transformation (NEXT) Awards. NAME lecturer Laura Alford, along CSE faculty members Dr. Mary Lou Dorf, Dr. Valeria Bertacco, Dr. Amir Kamil and Dr. William Arthur were recognized for showing outstanding achievement as clients of NCWIT Extension Services of Undergraduate Programs(ES-UP). ES-UP is”a program that helps academic departments of computing develop high-impact strategies for recruiting and retaining more women students with advice that is customized to local needs and conditions”. More…