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:

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

[SC2] HPC resources available to U-M students

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Brock Palen, Associate Director of Advanced Research Computing-Technology Services, joined the SC2 to talk about all the high performance computing (HPC) resources available to U-M graduate and undergraduate students. A summary of his presentation is here.

Resources:

Available at/through Michigan

  1. Flux for Undergraduates: Undergraduates can use the local flux computing cluster FOR FREE! Please visit the page for more information
    • ARC-Connect: use for Jupyter notebooks and VNC (remote desktop) access of flux resources, useful for remote visualization of big data or just getting a feel for working on linux and flux.
  2. Amazon Web Services: Michigan students get $100/year in amazon web services. While not as cost-effective for some things, very good resource to be aware of.
  3. Hadoop: Michigan’s Hadoop cluster is available for free (I believe you have to apply/demonstrate a need, but you don’t have to pay if it’s accepted). This upcoming workshop will go over the basics, read more if you are interested.

Available via Grant

Brock has an up-to-date webpage linking to and detailing various resources you can apply for.

Highlights:
  1. XSEDE:
    • Startup and teaching allocations are available continuously
    • Research allocations accepts 4x/year
  2. Great Lakes Consortium:
    • Alternate way to get some time on Blue Waters
  3. Amazon/Microsoft/Google:

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2015-2016 Education Snapshot

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XSEDESummerBootCamp2016

Students at the U-M satellite site of the XSEDE 2016 Summer Bootcamp

We have over 80 students between our Ph.D. in Scientific Computing and the Graduate Certificate in Computational Discovery and Engineering. The students come from five different schools and colleges, and 30 percent are women. We also have partnered with the Multidisciplinary Design Program to offer our Masters students the experience to work on industrial projects and gain practicum credits.

Our faculty have designed two courses that are being offered for the first time: Methods and Practices of Scientific Computing in Fall 2016 and Data-Driven Analysis and Modeling of Complex Systems in Winter 2017. Methods and Practices of Scientific Computing has gathered a tremendous amount of interest, and very quickly was over-subscribed. Data-Driven Analysis and Modeling of Complex Systems is a fast paced research area that combines scientific computing with big data to improve the existing models’ accuracy and representation of physical and biological systems.

Scientific Computing Student Club social gathering

Scientific Computing Student Club social gathering

We have brought a large community of students together by sponsoring and helping found the Scientific Computing Student Club. Its goal is to become a place for all students that use or want to use high performance computing to meet, share ideas, and find peer-to-peer help. It started in February, with social gatherings, talks from expert speakers, and more. The club has nearly 200 members, including undergraduates, graduate students, and postdocs from six U-M schools and colleges.

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)

miRcore’s high school biotechnology camp a success

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GIDAS Biotechnology camp’s high school students learning about microRNA targeted predictions using Flux, with support from MICDE and U-M’s Scientific Computing Student Club members.

 

From Aug. 8-12, 2016, MICDE and ARC-TS donated a Flux allocation and computational support to miRcore and its GIDAS’ Biotechnology Camp for high school students. All the students were able to log in the cluster, and use the command line to run RNAhybrid, a tool for finding the minimum free energy hybridization of a long and a short RNA. The students learned about microRNA target predictions that complemented the camp’s wet lab experiments. Scientific Computing Student Club members Joe Paki and Blair Winograd provided support to the students.

MICDE is partnered with miRcore, a non-profit organization whose mission is to democratize medical research by building funds for microgrants to support innovative genetic research.