Video, slides available from U-M presentations at SC16

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Several University of Michigan researchers and research IT staff made presentations at the SC16 conference in Salt Lake City Nov. 13-17. Material from many of the talks is now available for viewing online:

  • Shawn McKee (Physics) and Ben Meekhof (ARC-TS) presented a demonstration of the Open Storage Research Infrastructure (OSiRIS) project at the U-M booth. The demonstration extended the OSiRIS network from its participating institutions in Michigan to the conference center in Utah. Meekhof also presented at a”Birds of a Feather” session on Ceph in HPC environments. More information, including slides, is available on the OSiRIS website.
  • Todd Raeker (ARC-TS) made a presentation on ConFlux, U-M’s new computational physics cluster, at the NVIDIA booth. Slides and video are available.
  • Nilmini Abeyratne, a Ph.D student in computer science, presented her project “Low Design-Risk Checkpointing Storage Solution for Exascale Supercomputers” at the Doctoral Showcase. A summary, slides, and poster can be viewed on the SC16 website.
  • Jeremy Hallum (ARC-TS) presented information on the Yottabyte Research Cloud at the U-M booth. His slides are available here.

Other U-M activity at the conference included Sharon Broude Geva, Director of Advanced Research Computing, participating in a panel titled “HPC Workforce Development: How Do We Find Them, Recruit Them, and Teach Them to Be Today’s Practitioners and Tomorrow’s Leaders?”; Quentin Stout (EECS) and Christiane Jablonowski (CLASP) teaching the “Parallel Computing 101” tutorial.

HPC maintenance scheduled for January 7 – 9

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To accommodate upgrades to software and operating systems, Flux, Armis, and their storage systems (/home and /scratch) will be unavailable starting at 9am Saturday, January 7th, returning to service on Monday, January 9th.  Additionally, external Turbo mounts will be unavailable 11pm Saturday, January 7th, until 7am Sunday, January 8th.

During this time, the following updates are planned:

  • Operating system and software updates (minor updates) on Flux and Armis.  This should not require any changes to user software or processes.
  • Resource manager and job scheduling software updates.
  • Operating system updates on Turbo.

For HPC jobs, you can use the command “maxwalltime” to discover the amount of time before the beginning of the maintenance. Jobs that cannot complete prior to the beginning of the maintenance will be able to start when the clusters are returned to service.

We will post status updates on our Twitter feed ( https://twitter.com/arcts_um ) and send an email to all HPC users when the outage has been completed.

NVIDIA accepting applications for Graduate Fellowship Program

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NVIDIA has launched its 16th Annual Graduate Fellowship Program, which awards grants and technical support to graduate students who are doing outstanding GPU-based research.

This year NVIDIA is especially seeking doctoral students pushing the envelope in artificial intelligence, deep neural networks, autonomous vehicles, and related fields. The Graduate Fellowship awards are now up to $50,000 per student. These grants will be awarded in the 2017-2018 academic year.

Since its inception in 2002, the NVIDIA Graduate Fellowship Program has awarded over 130 Ph.D. graduate students with grants that have helped accelerate their research efforts.

The NVIDIA Graduate Fellowship Program is open to applicants worldwide. The deadline for submitting applications is Jan. 16, 2017. Eligible graduate students will have already completed their first year of Ph.D. level studies in the areas of computer science, computer engineering, system architecture, electrical engineering or a related area. In addition, applicants must also be engaged in active research as part of their thesis work.

For more information on eligibility and how to apply, visit http://research.nvidia.com/relevant/graduate-fellowship-program or email fellowship@nvidia.com.

Blue Waters accepting proposals for allocations, fellowships, and undergrad internships

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The GLCPC (Great Lakes Consortium for Petascale Computation) recently posted its call for proposals. Researchers from member institutions (including the University of Michigan) are eligible to apply for a Blue Waters allocation.  The application deadline is Friday, December 2nd.  More information can be found at: http://www.greatlakesconsortium.org/2016cfp.htm

Applications are also being accepted for Blue Waters Fellowships. Applications are due February 3, 2017. More information is available at: https://bluewaters.ncsa.illinois.edu/fellowships

Applications are now being accepted for Blue Waters undergraduate internships. Applications are due February 3, 2017.  More information is available at: https://bluewaters.ncsa.illinois.edu/internships

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 exceeded the distributed computing time.

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/

Globus 101 webinar scheduled for Oct. 6

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The OU Supercomputing Center for Education & Research (OSCER) is hosting a webinar on managing research data with Globus. Globus is software-as-a-service for research data management and provides high speed, secure file transfer; file sharing directly from existing stage systems; and data publication to institutional repositories. Developed and operated by the University of Chicago, Globus has become a preferred service for moving and sharing data between and among a wide variety of storage systems at research labs, campus computing resources, and national facilities across the US. In this session, you will learn about the features of the Globus service, and how to use it to streamline your research data flows. The webinar will help you answer these questions: How can Globus help me overcome the challenges I face in moving increasingly “big” datasets? How can I share data with collaborators at other institutions more efficiently? How can I use Globus to more easily leverage large-scale computing resources, both on campus and beyond? The presentation is aimed at those new to Globus, but attendees with prior Globus experience may also benefit by learning about new and planned features.

For more information and to register: https://www.eventbrite.com/e/ou-globus-101-webinar-tickets-27272257055

New geospatial analysis and GIS support at CSCAR

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CSCAR (Consulting for Statistics, Computing and Analytics Research) is offering expanded support for geospatial analysis and geographic information systems (GIS), effective immediately.

Researchers seeking guidance in this area are encouraged to schedule an appointment by calling 764-7828.

Several members of the CSCAR staff have expertise in modeling and analysis of geospatial data, and can provide consultations on basic and advanced methods. A variety of tools including R, Matlab, Python, and Arc-GIS are supported for work in this area. The CSCAR team was recently joined by a consultant holding a PhD in Earth/Environment Sciences, specializing in GIS and remote sensing.

As a result, CSCAR is now able to support a broad range of geospatial analysis activities including GIS, geostatistics, mechanistic modeling, geospatial visualization, and large-scale geospatial data processing on Flux and other advanced infrastructure systems. New workshops in Arc-GIS and other geospatial tools will begin in November (details will appear on this website).

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

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.