MIDAS to host faculty meeting on NSF BIGDATA solicitation

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The Michigan Institute for Data Science (MIDAS) will hold a faculty meeting at noon on Thursday, January 19 (Suite 7625, School of Public Health I, 1415 Washington Heights) for the NSF 17-534 “Critical Techniques, Technologies and Methodologies for Advancing Foundations and Applications of Big Data Sciences and Engineering (BIGDATA)” solicitation.

The meeting will include an overview of the NSF solicitation, U-M Data Science Resources (MIDAS, CSCAR, ARC-TS) available to faculty responding to the NSF call, and an opportunity to network with other faculty.

MIDAS has also arranged for Sylvia Spengler, NSF CISE Program Director, to be available at 1:30 pm to answer questions regarding the BIGDATA solicitation.

We invite you to participate in the faculty meeting to share your ideas and interest in responding to this BIGDATA solicitation as well as interact with other faculty looking to respond to this funding mechanism.

For those unable to participate in person, you can join virtually using GoToMeeting:

A box lunch will be provided at the faculty meeting.  Your RSVP (https://goo.gl/forms/OYAuB8mWCOlx3fw73) is appreciated.

ARC Director Sharon Broude Geva elected vice-chair of Coalition for Academic Scientific Computing

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Sharon Broude Geva, the Director of Advanced Research Computing at the University of Michigan, has been elected vice-chair of the Coalition for Academic Scientific Computation (CASC).

Founded in 1989, CASC advocates for the use of advanced computing technology to accelerate scientific discovery for national competitiveness, global security, and economic success. The organization’s members represent 83 institutions of higher education and national labs.

The vice-chair position is one of four elected CASC executive officers. The officers work closely as a team with the director of CASC. The vice-chair also leads CASC meeting program committees, is responsible for recruitment of new members, substitutes for the chair in his or her absences, and assists with moderating CASC meetings.

Geva served as CASC secretary in 2015 and 2016. Her term as vice-chair is effective for the 2017 calendar year.

The other executive officers for 2017 are are Rajendra Bose, Chair, Columbia University; Neil Bright, Secretary, Georgia Institute of Technology; and Andrew Sherman, Treasurer, Yale University. Curt Hillegas of Princeton University is immediate past chair.

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.

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

U-M professor Quentin Stout, a veteran of all 28 Supercomputing conferences, reflects on SC through the years

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Quentin Stout and Christian Jablonowski teaching the Parallel Computing 101 tutorial at SC07.

Quentin Stout, University of Michigan Professor of Computer Science and Engineering (CSE) and Climate and Space Sciences and Engineering (CLaSP), has attended all 28 of the Supercomputing conferences since the event begin in 1988. Stout is one of less than 20 so-called “SC Perennials” to have attended every one. He, along with Christiane Jablonowski, associate professor in CLaSP, have taught the Introduction to Parallel Computing tutorial at the conference for many years and are teaching it again this year. Stout, who has been at U-M since 1984, recently answered some questions about the evolution of the field of computer science and the area of supercomputing over the decades.

Question: What was the first SC conference like, and how has it changed over the years?

Stout: The first conference, in 1988, had about 1,500 people, compared to the over 10,000 now. Its focus was on supercomputing and the large centers at DOE, NASA, NSF, etc., along with the companies that were making these systems. There were also some researchers from academia and a few industrial users. The largest supercomputer user, NSA, had people at the conference, but they didn’t have a booth and their badge listed “Fort Meade” as their affiliation.

Over the years it has greatly broadened its scope to have a much broader international focus and more participation by universities, cluster vendors of all sizes, networking, storage, commercial software, educational efforts, etc. …

Originally I went to learn more about the field, meet people, see what the emerging areas were, and learn about the latest machines. I still go for these reasons, but now machines and software are improving in a more evolutionary fashion than the somewhat revolutionary changes at the beginning. Going from serial computers to vector or parallel ones was more exciting and groundbreaking than going from 100,000 cores to 1,000,000, though the latter is still challenging. Some things have stayed the same: the parties are still good, and companies are still entering and leaving the supercomputing area. For quite some time, if I brought home a coffee mug from a company, the company would go bankrupt in a few years. More recently, IBM developed the BlueGene series of machines, and grabbed the #1 spot in the top 500 rating of machines, but then dropped out of the market because it wasn’t selling enough machines to recoup the tremendous design cost.

One thing that has happened in computing field, not just the conference, is that scientific computing has a far smaller share of the market, even if you only consider the market for large systems. There have always been large database systems in corporations, but data analytics has greatly expanded the possibilities for profit, and hence there is more investment.

Question: What do you predict for the future of supercomputing?

Stout: The most “super” computers aren’t really single computers, but systems such as Google where they are continually processing a vast number of queries, answering them in fractions of a second by using sophisticated algorithms that combining myriad sources from throughout the world, all run on highly tuned systems that keep running even though they have so many components that they are always having to deal with faulty ones. The production users of supercomputers tend to submit a job, let it run for a long time, analyze the results (perhaps using sophisticated graphics), fix some errors or change some parameters, repeat. This isn’t the same as systems which are constantly ingesting data, analyzing it using algorithms that incorporate learning components, responding to increasingly complex queries. Academics, including some at U-M, are involved in this, but it is difficult to create even a scaled down version of a complete system in an academic computing center. You can view IBM’s Watson as being in this arena, and IBM is now betting that Watson will be a large part of its future.

Here’s an interesting cycle in computing: for over a decade some computational scientists and engineers have been using GPUs (graphics processing units). They are very difficult to use, and only applicable to certain types of problems, but inexpensive in terms of flops/$. However, many scientific computations require double precession arithmetic, which isn’t needed for graphics. Companies like NVIDIA, responding to the scientific computing market, began producing more expensive GPUs with double precision, and now systems such as U-M’s Flux computing cluster include GPUs on some of their boards.

However, there is a very rapidly growing demand for “deep learning.” The computationally intensive components of this can be run on GPUs relatively easily, but they don’t need double precision, just speed and plenty of parallelism. This summer NVIDIA released a new high-end chip with good double precision performance, but also added half precision, since that is all that is needed for deep learning. Deep learning might well surpass scientific computing as a GPU market.

 [NOTE: Visit the University of Michigan at SC16 at booth 1543.]


U-M prepares for SC16 conference in Salt Lake City

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University of Michigan researchers and professional research IT staff will participate in the SC16 conference in Salt Lake City from Nov. 13-17 in a number of ways, including demonstrations, presentations and tutorials. Please join us at booth 1543 if you’re at the conference, or at one of the following events:

Sunday, Nov. 13
8:30 a.m. – 5 p.m.: Quentin Stout (EECS) and Christiane Jablonowski (CLASP) will teach the “Parallel Computing 101” tutorial.

Monday, Nov. 14 through Thursday, Nov. 17
U-M will exhibit at booth #1543 alongside Michigan State University. The booth will include an ongoing demonstration of the OSiRIS networking and storage project; information on the Yottabyte Research Cloud; and a presentation on ConFlux.

Tuesday, Nov. 15
10:30 a.m.: Todd Raeker, Research Technology Consultant, ARC-TS, will give a talk on ConFlux at the NVIDIA booth (#2231).
11 a.m.: Project PI Shawn McKee (Physics) will give a presentation on OSiRIS at the U-M booth (#1543).
2:15 p.m.: Nilmini Abeyratne, a Ph.D student in computer science, will present “Low Design-Risk Checkpointing Storage Solution for Exascale Supercomputers” at the Doctoral Showcase.
1 – 5 p.m.: Todd Raeker, Research Technology Consultant, ARC-TS, will participate in the IBM Power8 University Group Meeting.
3 p.m.: Representatives from Yottabyte and ARC-TS will give a presentation on the Yottabyte Research Cloud.
3:30 – 5 p.m., Sharon Broude Geva, Director of Advanced Research Computing, will participate 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?

Wednesday, Nov. 16
10 a.m.: Representatives from Yottabyte and ARC-TS will give a presentation on the Yottabyte Research Cloud.
11 a.m.: Ben Meekhof, HPC Storage Administrator, ARC-TS, will give a presentation on OSiRIS at the U-M booth (#1543).
1 p.m.: Todd Raeker, Research Technology Consultant, ARC-TS, will give a talk on ConFlux at the U-M booth (#1543).
5:15 – 7 p.m.: Ben Meekhof, HPC Storage Administrator, ARC-TS, will present at a “Birds of a Feather” meeting on “Ceph in HPC Environments.”

Thursday, Nov. 17
11 a.m.: Project PI Shawn McKee (Physics) will give a presentation on OSiRIS at the U-M booth (#1543).
1 p.m.: Todd Raeker, Research Technology Consultant, ARC-TS, will give a talk on ConFlux at the U-M booth (#1543).

Ann Arbor Deep Learning annual event — Nov. 12

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a2-dlearn2016 is an annual event bringing together deep learning enthusiasts, researchers and practitioners from a variety of backgrounds.

MIDAS is proud to co-sponsor the event, which began last year as a collaboration between the Ann Arbor – Natural Language Processing and Machine Learning: Data, Science and Industry meetup groups.

The event will include speakers from the University of Michigan, University of Toronto, Toyota Research Institute and MDA Information Systems.

Please visit the event website for more information. Registration is required as space is limited.