Graduate Studies in Computational & Data Sciences Info Session — Jan 9 & 11

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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

There will be two sessions in January 2017:

MICDE affiliated faculty Monica Valluri (Astronomy) recognized for her outstanding research and teaching achievements

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valluriMonica Valluri, a Research Associate Professor in the Department of Astronomy, has been honored with the U-M Research Faculty Achievement Award for her outstanding research and teaching career in theoretical galaxy dynamics. She uses numerical calculations and simulations to probe galactic phenomena, including supermassive black holes and dark matter halos,two types of invisible matter whose presence is inferred primarily from their gravitational effects on stars and other visible matter.

Valluri earned a Ph.D. in astrophysics at the Indian Institute of Science in Bangalore, did postdoctoral research at Columbia University and Rutgers University, and joined the U-M faculty in 2007.

In addition to developing a more accurate method to determine the masses of SMBH, Valluri has transformed our understanding of galactic bars — elongated cigar-shaped clusters of orbiting stars that exist in many spiral galaxies, including the Milky Way. She demonstrated the traditional view of how stars move in bars is incomplete and that neglecting the effects of galactic bars can cause large errors in the measurement of black hole masses and host galaxy properties. Her work soon will be applied to data being gathered by the European Space Agency’s Gaia space observatory and is expected to verify or refute important predictions of the dominant paradigm regarding the nature of dark matter.

Valluri has published 42 journal articles. In addition to creating and teaching undergraduate astronomy and earth and space science courses, Valluri has taught at the Michigan Math and Science Scholars camp for high school students on a number of occasions. She has served on five doctoral committees and mentored 17 undergraduates. She also founded and organizes Conversations on Equity and Inclusion in Astrophysics and has served on the astronomy department’s curriculum committee and Michigan Institute for Research in Astrophysics planning committee. Valluri is chair of the American Astronomical Society Division of Dynamical Astronomy and a member of the Astronomical Society of India and International Astronomical Union.

With information from the record.umich.edu

Info Session: Data Science Services at U-M — Nov. 1

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Representatives of Consulting for Statistics, Computing and Analytics Research (CSCAR) and the U-M Library (UML) will give an overview of services that are now available to support data-intensive research on campus.  As part of the U-M Data Science Initiative, CSCAR and UML are expanding their scopes and adding capacity to support a wide range of research involving data and computation.  This includes consulting, workshops, and training designed to meet basic and advanced needs in data management and analysis, as well as specialized support for areas such as remote sensing and geospatial analyses, and a funding program for dataset acquisitions.  Many of these services are available free of charge to U-M researchers.  

This event will begin with overview presentations about CSCAR and Library system data services.  There will also be opportunities for researchers to discuss individualized partnerships with CSCAR and UML to advance specific data-intensive projects.  Faculty, staff, and students are welcome to attend.  

Time/Date: 4-5 p.m., November 1,
Location: Earl Lewis Room, Rackham Building

Research highlights: A new era in disaster research

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By Bob Brustman, U-M Civil and Environmental Engineering Department

University of Michigan researchers have received a $2.5 million NSF grant to develop a computational model that is hoped to significantly advance natural hazards engineering and disaster science.

Natural hazards engineers study earthquakes, tornadoes, hurricanes, tsunamis, landslides, and other disasters. They work to better understand the causes and effects of these phenomena on cities, homes, and infrastructure and develop strategies to save lives and mitigate damage.

Sherif El-Tawil

Sherif El-Tawil

Sherif El-Tawil, the lead PI for the project, is a structural engineer interested in how buildings behave, particularly in natural or man-made disasters. He’s developed 3D models and simulators that show precisely what happens in a building if a particular column or wall is destroyed during an extreme event.

On the project team are Jason McCormick, an earthquake engineering expert, Seymour Spence, who has expertise in wind engineering, and Benigno Aguirre, who is a social scientist interested in how people behave during catastrophes. The rest of the team includes. Vineet Kamat, Carol Menassa, and Atul Prakash, who will develop the simulation techniques used in the project.

The researchers of this newly funded project are creating a computational framework, using the Flux high performance computing cluster, that will define a set of standards for disaster researchers to use when constructing their models, enabling simulation models to work together.

El-Tawil explains: “Disaster research is a thriving area because disasters affect so many people worldwide and there is a lot we can do to reduce loss of life and damage to our civil infrastructure.”

“Lots of researchers study disasters, including engineers like me, but also social scientists, economists, doctors, and others. But all of the studies are essentially niche studies, belonging in the field of the researchers. Our objective is to develop computational standards so that social scientists, engineers, economists, doctors, first responders, and everyone else can produce simulators that interact together in a large, all-encompassing simulation of a disaster scenario. Think of it as the civilian equivalent of a war games simulator.”

el-tawil-nsf“Developing this common computational language will allow completely new studies to occur. Someone might look at the effects of an earthquake on a particular town and its citizens and then the subsequent effects of infectious diseases. With a common language, we can really examine the cascading and potentially out-of-control effects that occur during catastrophic events.”

Beyond developing the computational standards, they hope to create something like an app store through which researchers can share their simulation models and foster new collaborations and new areas of research. 

The grant also includes funding for a programmer housed at Advanced Research Computing (ARC) that will become a shared resource for the rest of campus. The Michigan Institute for Computational Discovery and Engineering (MICDE) provided support for the grant submission, and will continue to do so post-award.

The project brings together an experienced team with expertise in engineering, social science, and computer science. Six of the seven core members are from the University of Michigan and the seventh is from the University of Delaware.

Team members:

  • Benigno Aguirre, professor, Disaster Research Center, University of Delaware
  • Sherif El-Tawil, professor, Department of Civil and Environmental Engineering, University of Michigan
  • Vineet Kamat, professor, Department of Civil and Environmental Engineering, University of Michigan
  • Jason McCormick, associate professor, Department of Civil and Environmental Engineering, University of Michigan
  • Carol Menassa, associate professor, Department of Civil and Environmental Engineering, University of Michigan
  • Atul Prakash, professor, Department of Electrical Engineering and Computer Science, University of Michigan
  • Seymour Spence, assistant professor, Department of Civil and Environmental Engineering, University of Michigan

Research highlights: Running climate models in the cloud

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Xianglei Huang

Can cloud computing systems help make climate models easier to run? Assistant research scientist Xiuhong Chen and MICDE affiliated faculty Xianglei Huang, from Climate and Space Sciences and Engineering (CLASP), provide some answers to this question in an upcoming issue of Computers & Geoscience (Vol. 98, Jan. 2017, online publication link: http://dx.doi.org/10.1016/j.cageo.2016.09.014).

Teaming up with co-authors Dr. Chaoyi Jiao and Prof. Mark Flanner, also in CLASP, as well as Brock Palen and Todd Raeker from U-M’s Advanced Research Computing – Technology Services (ARC-TS), they compared the reliability and efficiency of Amazon’s Web Service – Elastic Compute 2 (AWS EC2) with U-M’s Flux high performance computing (HPC) cluster in running the Community Earth System Model (CESM), a flagship climate model in the U.S. developed by the National Center for Atmospheric Research.

The team was able to run the CESM in parallel on an AWS EC2 virtual cluster with minimal packaging and code compiling effort, finding that the AWS EC2 can render a parallelization efficiency comparable to Flux, the U-M HPC cluster, when using up to 64 cores. When using more than 64 cores, the communication time between virtual EC2 nodes exceeded the communication time in Flux.

Until now, climate and earth systems simulations had relied on numerical model suites that run on thousands of dedicated HPC cores for hours, days or weeks, depending on the size and scale of each model. Although these HPC resources have the advantage of being supported and maintained by trained IT support staff, making them easier to use them, they are expensive and not readily available to every investigator that needs them.

Furthermore, the systems within reach are sometimes not large enough to run simulations at the desired scales. Commercial cloud systems, on the other hand, are cheaper and accessible to everyone, and have grown significantly in the last few years. One potential drawback of cloud systems is that the user needs to provide and install all the software and the IT expertise needed to run the simulations’ packages.

Chen and Huang’s work represents an important firstxiangleihuangpost2016 step in the use of cloud computing in large-scale climate simulations. Now, cloud computing systems can be considered a viable alternate option to traditional HPC clusters for computational research, potentially allowing researchers to leverage the computational power offered by a cloud environment.

This study was sponsored by the Amazon Climate Initiative through a grant awarded to Prof. Huang. The local simulation in U-M was made possible by a DoE grant awarded to Prof. Huang.

Top image: http://www.cesm.ucar.edu/

U-M, Yottabyte partner to accelerate data-intensive research

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CONTACT: Dan Meisler, ARC Communications Manager, 734-764-7414, dmeisler@umich.edu

A strategic partnership between the University of Michigan and software company Yottabyte promises to unleash a new wave of data-intensive research by providing a flexible computing cloud for complex computational analyses of sensitive and restricted data.

The Yottabyte Research Cloud will provide scientists high performance, secure and flexible computing environments that enable the analysis of sensitive data sets restricted by federal privacy laws, proprietary access agreements, or confidentiality requirements. Previously, the complexity of building secure and project-specific IT platforms often made the computational analysis of sensitive data prohibitively costly and time consuming.

The system is built on $5.5 million worth of hardware and software donated to the University by Yottabyte; U-M will provide $2 million to support delivery of services to researchers and general operations.

Brahmajee Nallamothu, professor of internal medicine, tested a pilot installation of the Yottabyte Research Cloud at the U-M Institute of Healthcare Policy and Innovation for his research on such topics as predictors of opioid use after surgery and the costs and uses of cancer screenings under the Affordable Care Act.

“We recently moved a healthcare claims database, which is multiple terabytes in size and requires a great deal of memory and fast storage to process, onto the pilot platform,” Nallamothu said. “The platform allows us to immediately increase or decrease computing resources to meet demand while permitting multiple users to access the data safely and remotely. Our previous setup relied on network storage and self-managed hardware, which was extremely inefficient compared to what we can do now.”

“The Yottabyte Research Cloud will improve research productivity by reducing the cost and time required to create the individualized, secure computing platforms that are increasingly necessary to support scientific discovery in the age of Big Data,” said Eric Michielssen, associate vice president for advanced research computing at U-M.

“With the Yottabyte Research Cloud, researchers will be able to ask more questions, faster, of the ever-expanding and massive sets of data collected for their work,” said Yottabyte CEO Paul E. Hodges, III. “We are very pleased to be a part of the diverse and challenging research environment at U-M. This partnership is a great opportunity to develop and refine computing tools that will increase the productivity of U-M’s world class researchers.”

Many U-M scientists are working on a variety of research projects that could benefit from use of the Yottabyte Research Cloud:

  • Healthcare research, for example in precision medicine, often requires working with sensitive patient information and large volumes of diverse data types. This research can yield results that positively impact patients’ lives, but often involves the analysis of millions of clinical observations that can include genomic, hospital, outpatient, pharmaceutical, laboratory and cost data. This requires a secure high performance computing ecosystem coupled to massive amounts of multi-tiered storage.
  • In the social sciences, U-M research requires secure, remote access to sensitive research data about substance abuse, mental health, and other topics.
  • Transportation researchers who mine large and sensitive datasets — for example, a 24 Terabyte dataset that includes videos of drivers’ faces and GPS traces of their journeys — also stand to benefit from the security features and computing power.
  • In learning analytics, studies of the persistence of teacher effects on student learning could benefit from the enclaves to store and analyze data that includes observational measures scored from classroom videos, and elementary and middle school students’ scores on standardized tests.
  • Researchers in brain science will be able to use the Yottabyte Research Cloud to investigate a wide range of topics including  the effects of aging on brain function and structure and how we focus our attention in the presence of distraction.

The Yottabyte Research Cloud is U-M’s first foray into software-defined infrastructure for research, allowing on-the-fly personalized configuration of any-scale computing resources, which promises to change the way traditional IT infrastructure systems are deployed across the research community.  

More about Yottabyte:  www.yottabyte.com.

More about Yottabyte Research Cloud: arc-ts.umich.edu/yrc

Questions: dmeisler@umich.edu

NSF EAGER award to study new information and communication technologies in shared connected vehicles

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social_networkMICDE associate director Siqian Shen (PI) will collaborate with Co-PIs Tawanna Dillahunt and Tanya Rosenblat from U-M School of Information to conduct interdisciplinary research for a newly announced NSF EArly-concept Grant for Exploratory Research (EAGER) project.

The goal is to investigate the feasibility, challenges, and opportunities of deploying shared connected vehicles with new information and communication technologies (ICTs), to deliver goods and services in future smart & connected communities (S&CC). In taking on a living-lab approach, the study will engage industry, non-profit partners, and underserved populations in Detroit throughout each phase of the project.

The end result will be 1) improved mathematical models and efficient algorithms for optimizing resource allocation, supply-demand matching, and barrier-free vehicle & ICT operations in centralized and decentralized vehicle-and-service-sharing (V&SS) systems; 2) an articulation of the types of critical services that have the highest impact and are needed most among underserved communities (e.g., access to better healthcare or jobs).

Graduate programs in computational and data science — informational sessions Sept. 19 & 21

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Students interested in computational and data science are invited to learn about graduate programs that will prepare them for success in computationally intensive fields. Pizza and pop will be provided.

Two sessions are scheduled:

Monday, Sept. 19, 5 – 6 p.m.
Johnson Rooms, Lurie Engineering Center (North Campus)

Wednesday, Sept. 21, 5 – 6 p.m.
2001 LSA Building (Central Campus)

The sessions will address:

  • The Ph.D. in Scientific Computing, which 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, which 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. This year we will offer a new practicum option through the Multidisciplinary Design Program.
  • The Graduate Certificate in Data Science, which 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.

MICDE Fall 2016 Seminar Series speakers announced

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The Michigan Institute for Computational Discovery and Engineering (MICDE) is proud to announce its fall lineup of seminar speakers. In cooperation with academic departments across campus, the seminar series brings nationally recognized speakers to campus.

This fall’s speakers are:

Sept. 13: Nathan Kutz, Professor of Applied Mathematics, University of Washington

Sept. 22: Rob Gardner, Senior Scientist at the Computation Institute, University of Chicago

Sept. 29: Jeremy Lichstein, Assistant Professor of Biology, University of Florida

Oct. 6: Jonathan Freund, Professor of Mechanical Science and Engineering and of Aerospace Engineering, University of Illinois, Urbana-Champaign

Oct. 14: Anthony Wachs, Assistant Professor of Mathematics and of Chemical and Biological Engineering, University of British Columbia

Oct. 26: Andrea Lodi, Professor of Mathematical and Industrial Engineering, Polytechnique Montreal

Nov. 11: David Higdon, Professor of the Biocomplexity Institute, Virginia Tech

Dec. 9: Ann Almgren, Staff Scientist at the Center for Computational Sciences and Engineering, Lawrence Berkeley National Laboratories

For more information, including links to bios and abstracts as available, please visit micde.umich.edu/seminar-series/.

Students in the Graduate Certificate in Computational Discovery and Engineering program are required to attend at least half of the seminars.

Registration open for on-campus telecast of XSEDE workshop on MPI — Sept. 7-8

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U-M is hosting a telecast of a workshop on MPI (message passing interface) presented by XSEDE and the Pittsburgh Supercomputing Center.

This workshop is intended to give C and Fortran programmers a hands-on introduction to MPI programming. Attendees will leave with a working knowledge of how to write scalable codes using MPI – the standard programming tool of scalable parallel computing.

Time/Date: 11 a.m. to 5 p.m. Eastern, Wednesday, Sept. 7 and Thursday, Sept. 8

Location: Room B003E, North Campus Research Complex (NCRC), Building 16, 2800 Plymouth Rd.

Registration: Registration is required through the XSEDE website (you must create an XSEDE user account to register). Space is limited.

More information: Class website.

Contact: Simon Adorf (csadorf@umich.edu)