Mini-course: Introduction to Python — Sept. 11-14

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Asst. Prof. Emanuel Gull, Physics, is offering a mini-course introducing the Python programming language in a four-lecture series. Beginners without any programming experience as well as programmers who usually use other languages (C, C++, Fortran, Java, …) are encouraged to come; no prior knowledge of programming languages is required!

For the first two lectures we will mostly follow the book Learning Python. This book is available at our library. An earlier edition (with small differences, equivalent for all practical purposes) is available as an e-book. The second week will introduce some useful python libraries: numpyscipymatplotlib.

At the end of the first two weeks you will know enough about Python to use it for your grad class homework and your research.

Special meeting place: we will meet in 340 West Hall on Monday September 11 at 5 PM.

Please bring a laptop computer along to follow the exercises!

Syllabus (Dates & Location for Fall 2017)

  1. Monday September 11 5:00 – 6:30 PM: Welcome & Getting Started (hello.py). Location: 340 West Hall
  2. Tuesday September 12 5:00 – 6:30 PM: Numbers, Strings, Lists, Dictionaries, Tuples, Functions, Modules, Control flow. Location: 335 West Hall
  3. Wednesday September 13 5:00 – 6:30 PM: Useful Python libraries (part I): numpy, scipy, matplotlib. Location: 335 West Hall
  4. Thursday September 14 5:00 – 6:30 PM: Useful Python libraries (part 2): 3d plotting in matplotlib and exercises. Location: 335 West Hall

For more information: https://sites.lsa.umich.edu/gull-lab/teaching/physics-514-fall-2017/introduction-to-python/

 

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:

HPC training workshops begin Thursday, Sept. 21

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series of training workshops in high performance computing will be held Sept. 21 through Oct. 31, 2017, presented by CSCAR in conjunction with Advanced Research Computing – Technology Services (ARC-TS). All sessions are held at East Hall, Room B254, 530 Church St.

Introduction to the Linux command Line
This course will familiarize the student with the basics of accessing and interacting with Linux computers using the GNU/Linux operating system’s Bash shell, also known as the “command line.”
Dates: (Please sign up for only one)
• Thursday, Sept. 21, 9 a.m. – noon (full descriptionregistration)
• Thursday, Sept. 28, 9 a.m. – noon (full description | registration)
Location:
East Hall, Room B250, 530 Church St.

Introduction to the Flux cluster and batch computing
This workshop will provide a brief overview of the components of the Flux cluster, including the resource manager and scheduler, and will offer students hands-on experience.
Dates: (Please sign up for only one)
• Thursday, Sept. 28, 1 – 4 p.m. (full description | registration)
• Monday, Oct. 2, 9 a.m. – noon (full description | registration)
Location:
East Hall, Room B254, 530 Church St.

Advanced batch computing on the Flux cluster
This course will cover advanced areas of cluster computing on the Flux cluster, including common parallel programming models, dependent and array scheduling, among other topics.
Dates: (Please sign up for only one)
• Tuesday, Oct. 10, 1 – 5 p.m. (full description | registration)
• Thursday, Oct. 12, 9 a.m. – noon (full description | registration)
Location:
East Hall, Room B254, 530 Church St.

Hadoop Workshop
Learn how to process large amounts (up to terabytes) of data using SQL and/or simple programming models available in Python, Scala, and Java.
Date:
• Tuesday, Oct. 31, 1 – 5 p.m. (full description | registration)
Location:
East Hall, Room B254, 530 Church St.

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.

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.

ARC-TS seeks input on next generation HPC cluster

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The University of Michigan is beginning the process of building our next generation HPC platform, “Big House.”  Flux, the shared HPC cluster, has reached the end of its useful life. Flux has served us well for more than five years, but as we move forward with replacement, we want to make sure we’re meeting the needs of the research community.

ARC-TS will be holding a series of town halls to take input from faculty and researchers on the next HPC platform to be built by the University.  These town halls are open to anyone and will be held at:

  • College of Engineering, Johnson Room, Tuesday, June 20th, 9:00a – 10:00a
  • NCRC Bldg 300, Room 376, Wednesday, June 21st, 11:00a – 12:00p
  • LSA #2001, Tuesday, June 27th, 10:00a – 11:00a
  • 3114 Med Sci I, Wednesday, June 28th, 2:00p – 3:00p

Your input will help to ensure that U-M is on course for providing HPC, so we hope you will make time to attend one of these sessions. If you cannot attend, please email hpc-support@umich.edu with any input you want to share.

MIDAS starting research group on mobile sensor analytics

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The Michigan Institute for Data Science (MIDAS) is convening a research working group on mobile sensor analytics. Mobile sensors are taking on an increasing presence in our lives. Wearable devices allow for physiological and cognitive monitoring, and behavior modeling for health maintenance, exercise, sports, and entertainment. Sensors in vehicles measure vehicle kinematics, record driver behavior, and increase perimeter awareness. Mobile sensors are becoming essential in areas such as environmental monitoring and epidemiological tracking.

There are significant data science opportunities for theory and application in mobile sensor analytics, including real-time data collection, streaming data analysis, active on-line learning, mobile sensor networks, and energy efficient mobile computing.

Our working group welcomes researchers with interest in mobile sensor analytics in any scientific domain, including but not limited to health, transportation, smart cities, ecology and the environment.

Where and When:

Noon to 2 pm, April 13, 2017

School of Public Health I, Room 7625

Lunch provided

Agenda:

  • Brief presentations about challenges and opportunities in mobile sensor analytics (theory and application);

  • A brief presentation of a list of funding opportunities;

  • Discussion of research ideas and collaboration in the context of grant application and industry partnership.

Future Plans: Based on the interest of participants, MIDAS will alert researchers to relevant funding opportunities, hold follow-up meetings for continued discussion and team formation as ideas crystalize for grant applications, and work with the UM Business Engagement Center to bring in industry partnership.

Please RSVP.  For questions, please contact Jing Liu, Ph.D, MIDAS research specialist (ljing@umich.edu; 734-764-2750).

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 User Meetups set for October, November and December

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Users of high performance computing resources are invited to meet ARC-TS HPC operators and support staff in person at an upcoming user meeting:

  • Monday, October 17, 1:10 – 5 p.m., 2001 LSA Building (500 S. State St.)
  • Wednesday, November 9, 1 – 5 p.m., 1180 Duderstadt Center (2281 Bonisteel Blvd., North Campus)
  • Monday, December 12, 1 – 5 p.m., 4515 Biomedical Science Research Building (BSRB, 109 Zina Pitcher Pl.)

There is not a set agenda; come at anytime and stay as long as you please. You can come and talk about your use of any sort of computational resource, Flux, Armis, Hadoop, XSEDE, Amazon, or other.

Ask any questions you may have. The ARC-TS staff will work with you on your specific projects, or just show you new things that can help you optimize your research.

This is also a good time to meet other researchers doing similar work.

This is open to anyone interested; it is not limited to Flux users.

Examples of potential topics:

  • What ARC-TS services are there, and how to access them?
  • I want to do X, do you have software capable of it?
  • What is special about GPU/Xeon Phi/Accelerators?
  • Are there resources for people without budgets?
  • I want to apply for grant X, but it has certain limitations. What support can ARC-TS provide?
  • I want to learn more about the compiler and debugging?
  • I want to learn more about performance tuning, can you look at my code with me?
  • Etc.